Merge branch 'codex/atocore-integration-pass'

Adds the t420-openclaw/ workspace: the OpenClaw side of the
AtoCore integration surface — agent bootstrap docs, atocore-context
skill, tools manifest, operations guide, and a thin HTTP client
wrapper (atocore.py + atocore.sh) that shells out to the canonical
Dalidou endpoint.

Branch is a single orphan commit authored 2026-04-06 by Antoine;
merging with --allow-unrelated-histories since it has no common
ancestor with main. Paths are entirely new (t420-openclaw/) so
there is no file-level conflict.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

deploy/dalidou/cron-backup.sh

@@ -0,0 +1,85 @@
+#!/usr/bin/env bash
+#
+# deploy/dalidou/cron-backup.sh
+# ------------------------------
+# Daily backup + retention cleanup via the AtoCore API.
+#
+# Intended to run from cron on Dalidou:
+#
+#   # Daily at 03:00 UTC
+#   0 3 * * * /srv/storage/atocore/app/deploy/dalidou/cron-backup.sh >> /var/log/atocore-backup.log 2>&1
+#
+# What it does:
+#   1. Creates a runtime backup (db + registry, no chroma by default)
+#   2. Runs retention cleanup with --confirm to delete old snapshots
+#   3. Logs results to stdout (captured by cron into the log file)
+#
+# Fail-open: exits 0 even on API errors so cron doesn't send noise
+# emails. Check /var/log/atocore-backup.log for diagnostics.
+#
+# Environment variables:
+#   ATOCORE_URL             default http://127.0.0.1:8100
+#   ATOCORE_BACKUP_CHROMA   default false (set to "true" for cold chroma copy)
+#   ATOCORE_BACKUP_DIR      default /srv/storage/atocore/backups
+#   ATOCORE_BACKUP_RSYNC    optional rsync destination for off-host copies
+#                           (e.g. papa@laptop:/home/papa/atocore-backups/)
+#                           When set, the local snapshots tree is rsynced to
+#                           the destination after cleanup. Unset = skip.
+#                           SSH key auth must already be configured from this
+#                           host to the destination.
+
+set -euo pipefail
+
+ATOCORE_URL="${ATOCORE_URL:-http://127.0.0.1:8100}"
+INCLUDE_CHROMA="${ATOCORE_BACKUP_CHROMA:-false}"
+BACKUP_DIR="${ATOCORE_BACKUP_DIR:-/srv/storage/atocore/backups}"
+RSYNC_TARGET="${ATOCORE_BACKUP_RSYNC:-}"
+TIMESTAMP="$(date -u +%Y-%m-%dT%H:%M:%SZ)"
+
+log() { printf '[%s] %s\n' "$TIMESTAMP" "$*"; }
+
+log "=== AtoCore daily backup starting ==="
+
+# Step 1: Create backup
+log "Step 1: creating backup (chroma=$INCLUDE_CHROMA)"
+BACKUP_RESULT=$(curl -sf -X POST \
+    -H "Content-Type: application/json" \
+    -d "{\"include_chroma\": $INCLUDE_CHROMA}" \
+    "$ATOCORE_URL/admin/backup" 2>&1) || {
+    log "ERROR: backup creation failed: $BACKUP_RESULT"
+    exit 0
+}
+log "Backup created: $BACKUP_RESULT"
+
+# Step 2: Retention cleanup (confirm=true to actually delete)
+log "Step 2: running retention cleanup"
+CLEANUP_RESULT=$(curl -sf -X POST \
+    -H "Content-Type: application/json" \
+    -d '{"confirm": true}' \
+    "$ATOCORE_URL/admin/backup/cleanup" 2>&1) || {
+    log "ERROR: cleanup failed: $CLEANUP_RESULT"
+    exit 0
+}
+log "Cleanup result: $CLEANUP_RESULT"
+
+# Step 3: Off-host rsync (optional). Fail-open: log but don't abort
+# the cron so a laptop being offline at 03:00 UTC never turns the
+# local backup path red.
+if [[ -n "$RSYNC_TARGET" ]]; then
+    log "Step 3: rsyncing snapshots to $RSYNC_TARGET"
+    if [[ ! -d "$BACKUP_DIR/snapshots" ]]; then
+        log "WARN: $BACKUP_DIR/snapshots does not exist, skipping rsync"
+    else
+        RSYNC_OUTPUT=$(rsync -a --delete \
+            -e "ssh -o ConnectTimeout=10 -o BatchMode=yes -o StrictHostKeyChecking=accept-new" \
+            "$BACKUP_DIR/snapshots/" "$RSYNC_TARGET" 2>&1) && {
+            log "Rsync complete"
+        } || {
+            log "WARN: rsync to $RSYNC_TARGET failed (offline or auth?): $RSYNC_OUTPUT"
+        }
+    fi
+else
+    log "Step 3: ATOCORE_BACKUP_RSYNC not set, skipping off-host copy"
+fi
+
+log "=== AtoCore daily backup complete ==="

deploy/hooks/capture_stop.py

@@ -3,7 +3,7 @@
 
 Reads the Stop hook JSON from stdin, extracts the last user prompt
 from the transcript JSONL, and POSTs to the AtoCore /interactions
-endpoint in conservative mode (reinforce=false, no extraction).
+endpoint with reinforcement enabled (no extraction).
 
 Fail-open: always exits 0, logs errors to stderr only.
 
@@ -81,7 +81,7 @@ def _capture() -> None:
         "client": "claude-code",
         "session_id": session_id,
         "project": project,
-        "reinforce": False,
+        "reinforce": True,
     }
 
     body = json.dumps(payload, ensure_ascii=True).encode("utf-8")

docs/master-plan-status.md

@@ -32,7 +32,18 @@ read-only additive mode.
 ### Baseline Complete
 
 - Phase 9 - Reflection (all three foundation commits landed:
-  A capture, B reinforcement, C candidate extraction + review queue)
+  A capture, B reinforcement, C candidate extraction + review queue).
+  As of 2026-04-11 the capture → reinforce half runs automatically on
+  every Stop-hook capture (length-aware token-overlap matcher handles
+  paragraph-length memories), and project-scoped memories now reach
+  the context pack via a dedicated `--- Project Memories ---` band
+  between identity/preference and retrieved chunks. The extract half
+  is still a manual / batch flow by design (`scripts/atocore_client.py
+  batch-extract` + `triage`). First live batch-extract run over 42
+  captured interactions produced 1 candidate (rule extractor is
+  conservative and keys on structural cues like `## Decision:`
+  headings that rarely appear in conversational LLM responses) —
+  extractor tuning is a known follow-up.
 
 ### Not Yet Complete In The Intended Sense
 
@@ -167,7 +178,9 @@ These remain intentionally deferred.
 
 - automatic write-back from OpenClaw into AtoCore
 - automatic memory promotion
-- reflection loop integration
+- ~~reflection loop integration~~ — baseline now in (capture→reinforce
+  auto, extract batch/manual). Extractor tuning and scheduled batch
+  extraction still open.
 - replacing OpenClaw's own memory system
 - live machine-DB sync between machines
 - full ontology / graph expansion before the current baseline is stable

docs/next-steps.md

@@ -137,7 +137,12 @@ P06:
 
 - automatic write-back from OpenClaw into AtoCore
 - automatic memory promotion
-- reflection loop integration
+- ~~reflection loop integration~~ — baseline now landed (2026-04-11):
+  Stop hook runs reinforce automatically, project memories are folded
+  into the context pack, batch-extract and triage CLIs exist. What
+  remains deferred: scheduled/automatic batch extraction and extractor
+  rule tuning (rule-based extractor produced 1 candidate from 42 real
+  captures — needs new cues for conversational LLM content).
 - replacing OpenClaw's own memory system
 - syncing the live machine DB between machines
 
@@ -159,6 +164,77 @@ The next batch is successful if:
 - project ingestion remains controlled rather than noisy
 - the canonical Dalidou instance stays stable
 
+## Retrieval Quality Review — 2026-04-11
+
+First sweep with real project-hinted queries on Dalidou. Used
+`POST /context/build` against p04, p05, p06 with representative
+questions and inspected `formatted_context`.
+
+Findings:
+
+- **Trusted Project State is surfacing correctly.** The DECISION and
+  REQUIREMENT categories appear at the top of the pack and include
+  the expected key facts (e.g. p04 "Option B conical-back mirror
+  architecture"). This is the strongest signal in the pack today.
+- **Chunk retrieval is relevant on-topic but broad.** Top chunks for
+  the p04 architecture query are PDR intro, CAD assembly overview,
+  and the index — all on the right project but none of them directly
+  answer the "why was Option B chosen" question. The authoritative
+  answer sits in Project State, not in the chunks.
+- **Active memories are NOT reaching the pack.** The context builder
+  surfaces Trusted Project State and retrieved chunks but does not
+  include the 21 active project/knowledge memories. Reinforcement
+  (Phase 9 Commit B) bumps memory confidence without the memory ever
+  being read back into a prompt — the reflection loop has no outlet
+  on the retrieval side. This is a design gap, not a bug: needs a
+  decision on whether memories should feed into context assembly,
+  and if so at what trust level (below project_state, above chunks).
+- **Cross-project bleed is low.** The p04 query did pull one p05
+  chunk (CGH_Design_Input_for_AOM) as the bottom hit but the top-4
+  were all p04.
+
+Proposed follow-ups (not yet scheduled):
+
+1. ~~Decide whether memories should be folded into `formatted_context`
+   and under what section header.~~ DONE 2026-04-11 (commits 8ea53f4,
+   5913da5, 1161645). A `--- Project Memories ---` band now sits
+   between identity/preference and retrieved chunks, gated on a
+   canonical project hint to prevent cross-project bleed. Budget
+   ratio 0.25 (tuned empirically — paragraph memories are ~400 chars
+   and earlier 0.15 ratio starved the first entry by one char).
+   Verified live: p04 architecture query surfaces the Option B memory.
+2. Re-run the same three queries after any builder change and compare
+   `formatted_context` diffs — still open, and is the natural entry
+   point for the retrieval eval harness on the roadmap.
+
+## Reflection Loop Live Check — 2026-04-11
+
+First real run of `batch-extract` across 42 captured Claude Code
+interactions on Dalidou produced exactly **1 candidate**, and that
+candidate was a synthetic test capture from earlier in the session
+(rejected). Finding:
+
+- The rule-based extractor in `src/atocore/memory/extractor.py` keys
+  on explicit structural cues (decision headings like
+  `## Decision: ...`, preference sentences, etc.). Real Claude Code
+  responses are conversational and almost never contain those cues.
+- This means the capture → extract half of the reflection loop is
+  effectively inert against organic LLM sessions until either the
+  rules are broadened (new cue families: "we chose X because...",
+  "the selected approach is...", etc.) or an LLM-assisted extraction
+  path is added alongside the rule-based one.
+- Capture → reinforce is working correctly on live data (length-aware
+  matcher verified on live paraphrase of a p04 memory).
+
+Follow-up candidates (not yet scheduled):
+
+1. Extractor rule expansion — add conversational-form rules so real
+   session text has a chance of surfacing candidates.
+2. LLM-assisted extractor as a separate rule family, guarded by
+   confidence and always landing in `status=candidate` (never active).
+3. Retrieval eval harness — diffable scorecard of
+   `formatted_context` across a fixed question set per active project.
+
 ## Long-Run Goal
 
 The long-run target is:

scripts/atocore_client.py

@@ -340,6 +340,22 @@ def build_parser() -> argparse.ArgumentParser:
     p = sub.add_parser("reject")
     p.add_argument("memory_id")
 
+    # batch-extract: fan out /interactions/{id}/extract?persist=true across
+    #   recent interactions. Idempotent — the extractor create_memory path
+    #   silently skips duplicates, so re-running is safe.
+    p = sub.add_parser("batch-extract")
+    p.add_argument("since", nargs="?", default="")
+    p.add_argument("project", nargs="?", default="")
+    p.add_argument("limit", nargs="?", type=int, default=100)
+    p.add_argument("persist", nargs="?", default="true")
+
+    # triage: interactive candidate review loop. Fetches the queue, shows
+    #   each candidate, accepts p/r/s (promote / reject / skip) / q (quit).
+    p = sub.add_parser("triage")
+    p.add_argument("memory_type", nargs="?", default="")
+    p.add_argument("project", nargs="?", default="")
+    p.add_argument("limit", nargs="?", type=int, default=50)
+
     return parser
 
 
@@ -474,10 +490,141 @@ def main() -> int:
                 {},
             )
         )
+    elif cmd == "batch-extract":
+        print_json(run_batch_extract(args.since, args.project, args.limit, args.persist))
+    elif cmd == "triage":
+        return run_triage(args.memory_type, args.project, args.limit)
     else:
         return 1
     return 0
 
 
+def run_batch_extract(since: str, project: str, limit: int, persist_flag: str) -> dict:
+    """Fetch recent interactions and run the extractor against each one.
+
+    Returns an aggregated summary. Safe to re-run: the server-side
+    persist path catches ValueError on duplicates and the endpoint
+    reports per-interaction candidate counts either way.
+    """
+    persist = persist_flag.lower() in {"1", "true", "yes", "y"}
+    query_parts: list[str] = []
+    if project:
+        query_parts.append(f"project={urllib.parse.quote(project)}")
+    if since:
+        query_parts.append(f"since={urllib.parse.quote(since)}")
+    query_parts.append(f"limit={int(limit)}")
+    query = "?" + "&".join(query_parts)
+
+    listing = request("GET", f"/interactions{query}")
+    interactions = listing.get("interactions", []) if isinstance(listing, dict) else []
+
+    processed = 0
+    total_candidates = 0
+    total_persisted = 0
+    errors: list[dict] = []
+    per_interaction: list[dict] = []
+
+    for item in interactions:
+        iid = item.get("id") or ""
+        if not iid:
+            continue
+        try:
+            result = request(
+                "POST",
+                f"/interactions/{urllib.parse.quote(iid, safe='')}/extract",
+                {"persist": persist},
+            )
+        except Exception as exc:  # pragma: no cover - network errors land here
+            errors.append({"interaction_id": iid, "error": str(exc)})
+            continue
+        processed += 1
+        count = int(result.get("candidate_count", 0) or 0)
+        persisted_ids = result.get("persisted_ids") or []
+        total_candidates += count
+        total_persisted += len(persisted_ids)
+        if count:
+            per_interaction.append(
+                {
+                    "interaction_id": iid,
+                    "candidate_count": count,
+                    "persisted_count": len(persisted_ids),
+                    "project": item.get("project") or "",
+                }
+            )
+
+    return {
+        "processed": processed,
+        "total_candidates": total_candidates,
+        "total_persisted": total_persisted,
+        "persist": persist,
+        "errors": errors,
+        "interactions_with_candidates": per_interaction,
+    }
+
+
+def run_triage(memory_type: str, project: str, limit: int) -> int:
+    """Interactive review of candidate memories.
+
+    Loads the queue once, walks through entries, prompts for
+    (p)romote / (r)eject / (s)kip / (q)uit. Stateless between runs —
+    re-running picks up whatever is still status=candidate.
+    """
+    query_parts = ["status=candidate"]
+    if memory_type:
+        query_parts.append(f"memory_type={urllib.parse.quote(memory_type)}")
+    if project:
+        query_parts.append(f"project={urllib.parse.quote(project)}")
+    query_parts.append(f"limit={int(limit)}")
+    listing = request("GET", "/memory?" + "&".join(query_parts))
+    memories = listing.get("memories", []) if isinstance(listing, dict) else []
+
+    if not memories:
+        print_json({"status": "empty_queue", "count": 0})
+        return 0
+
+    promoted = 0
+    rejected = 0
+    skipped = 0
+    stopped_early = False
+
+    print(f"Triage queue: {len(memories)} candidate(s)\n", file=sys.stderr)
+    for idx, mem in enumerate(memories, 1):
+        mid = mem.get("id", "")
+        print(f"[{idx}/{len(memories)}] {mem.get('memory_type','?')}  project={mem.get('project','')}  conf={mem.get('confidence','?')}", file=sys.stderr)
+        print(f"  id: {mid}", file=sys.stderr)
+        print(f"  {mem.get('content','')}", file=sys.stderr)
+        try:
+            choice = input("  (p)romote / (r)eject / (s)kip / (q)uit > ").strip().lower()
+        except EOFError:
+            stopped_early = True
+            break
+        if choice in {"q", "quit"}:
+            stopped_early = True
+            break
+        if choice in {"p", "promote"}:
+            request("POST", f"/memory/{urllib.parse.quote(mid, safe='')}/promote", {})
+            promoted += 1
+            print("  -> promoted", file=sys.stderr)
+        elif choice in {"r", "reject"}:
+            request("POST", f"/memory/{urllib.parse.quote(mid, safe='')}/reject", {})
+            rejected += 1
+            print("  -> rejected", file=sys.stderr)
+        else:
+            skipped += 1
+            print("  -> skipped", file=sys.stderr)
+
+    print_json(
+        {
+            "reviewed": promoted + rejected + skipped,
+            "promoted": promoted,
+            "rejected": rejected,
+            "skipped": skipped,
+            "stopped_early": stopped_early,
+            "remaining_in_queue": len(memories) - (promoted + rejected + skipped) - (1 if stopped_early else 0),
+        }
+    )
+    return 0
+
+
 if __name__ == "__main__":
     raise SystemExit(main())

scripts/retrieval_eval.py

@@ -0,0 +1,194 @@
+"""Retrieval quality eval harness.
+
+Runs a fixed set of project-hinted questions against
+``POST /context/build`` on a live AtoCore instance and scores the
+resulting ``formatted_context`` against per-question expectations.
+The goal is a diffable scorecard that tells you, run-to-run,
+whether a retrieval / builder / ingestion change moved the needle.
+
+Design notes
+------------
+- Fixtures live in ``scripts/retrieval_eval_fixtures.json`` so new
+  questions can be added without touching Python. Each fixture
+  names the project, the prompt, and a checklist of substrings that
+  MUST appear in ``formatted_context`` (``expect_present``) and
+  substrings that MUST NOT appear (``expect_absent``). The absent
+  list catches cross-project bleed and stale content.
+- The checklist is deliberately substring-based (not regex, not
+  embedding-similarity) so a failure is always a trivially
+  reproducible "this string is not in that string". Richer scoring
+  can come later once we know the harness is useful.
+- The harness is external to the app runtime and talks to AtoCore
+  over HTTP, so it works against dev, staging, or prod. It follows
+  the same environment-variable contract as ``atocore_client.py``
+  (``ATOCORE_BASE_URL``, ``ATOCORE_TIMEOUT_SECONDS``).
+- Exit code 0 on all-pass, 1 on any fixture failure. Intended for
+  manual runs today; a future cron / CI hook can consume the
+  JSON output via ``--json``.
+
+Usage
+-----
+
+    python scripts/retrieval_eval.py            # human-readable report
+    python scripts/retrieval_eval.py --json     # machine-readable
+    python scripts/retrieval_eval.py --fixtures path/to/custom.json
+"""
+
+from __future__ import annotations
+
+import argparse
+import json
+import os
+import sys
+import urllib.error
+import urllib.parse
+import urllib.request
+from dataclasses import dataclass, field
+from pathlib import Path
+
+DEFAULT_BASE_URL = os.environ.get("ATOCORE_BASE_URL", "http://dalidou:8100")
+DEFAULT_TIMEOUT = int(os.environ.get("ATOCORE_TIMEOUT_SECONDS", "30"))
+DEFAULT_BUDGET = 3000
+DEFAULT_FIXTURES = Path(__file__).parent / "retrieval_eval_fixtures.json"
+
+
+@dataclass
+class Fixture:
+    name: str
+    project: str
+    prompt: str
+    budget: int = DEFAULT_BUDGET
+    expect_present: list[str] = field(default_factory=list)
+    expect_absent: list[str] = field(default_factory=list)
+    notes: str = ""
+
+
+@dataclass
+class FixtureResult:
+    fixture: Fixture
+    ok: bool
+    missing_present: list[str]
+    unexpected_absent: list[str]
+    total_chars: int
+    error: str = ""
+
+
+def load_fixtures(path: Path) -> list[Fixture]:
+    data = json.loads(path.read_text(encoding="utf-8"))
+    if not isinstance(data, list):
+        raise ValueError(f"{path} must contain a JSON array of fixtures")
+    fixtures: list[Fixture] = []
+    for i, raw in enumerate(data):
+        if not isinstance(raw, dict):
+            raise ValueError(f"fixture {i} is not an object")
+        fixtures.append(
+            Fixture(
+                name=raw["name"],
+                project=raw.get("project", ""),
+                prompt=raw["prompt"],
+                budget=int(raw.get("budget", DEFAULT_BUDGET)),
+                expect_present=list(raw.get("expect_present", [])),
+                expect_absent=list(raw.get("expect_absent", [])),
+                notes=raw.get("notes", ""),
+            )
+        )
+    return fixtures
+
+
+def run_fixture(fixture: Fixture, base_url: str, timeout: int) -> FixtureResult:
+    payload = {
+        "prompt": fixture.prompt,
+        "project": fixture.project or None,
+        "budget": fixture.budget,
+    }
+    req = urllib.request.Request(
+        url=f"{base_url}/context/build",
+        method="POST",
+        headers={"Content-Type": "application/json"},
+        data=json.dumps(payload).encode("utf-8"),
+    )
+    try:
+        with urllib.request.urlopen(req, timeout=timeout) as resp:
+            body = json.loads(resp.read().decode("utf-8"))
+    except urllib.error.URLError as exc:
+        return FixtureResult(
+            fixture=fixture,
+            ok=False,
+            missing_present=list(fixture.expect_present),
+            unexpected_absent=[],
+            total_chars=0,
+            error=f"http_error: {exc}",
+        )
+
+    formatted = body.get("formatted_context") or ""
+    missing = [s for s in fixture.expect_present if s not in formatted]
+    unexpected = [s for s in fixture.expect_absent if s in formatted]
+    return FixtureResult(
+        fixture=fixture,
+        ok=not missing and not unexpected,
+        missing_present=missing,
+        unexpected_absent=unexpected,
+        total_chars=len(formatted),
+    )
+
+
+def print_human_report(results: list[FixtureResult]) -> None:
+    total = len(results)
+    passed = sum(1 for r in results if r.ok)
+    print(f"Retrieval eval: {passed}/{total} fixtures passed")
+    print()
+    for r in results:
+        marker = "PASS" if r.ok else "FAIL"
+        print(f"[{marker}] {r.fixture.name}  project={r.fixture.project}  chars={r.total_chars}")
+        if r.error:
+            print(f"       error: {r.error}")
+        for miss in r.missing_present:
+            print(f"       missing expected: {miss!r}")
+        for bleed in r.unexpected_absent:
+            print(f"       unexpected present: {bleed!r}")
+        if r.fixture.notes and not r.ok:
+            print(f"       notes: {r.fixture.notes}")
+
+
+def print_json_report(results: list[FixtureResult]) -> None:
+    payload = {
+        "total": len(results),
+        "passed": sum(1 for r in results if r.ok),
+        "fixtures": [
+            {
+                "name": r.fixture.name,
+                "project": r.fixture.project,
+                "ok": r.ok,
+                "total_chars": r.total_chars,
+                "missing_present": r.missing_present,
+                "unexpected_absent": r.unexpected_absent,
+                "error": r.error,
+            }
+            for r in results
+        ],
+    }
+    json.dump(payload, sys.stdout, indent=2)
+    sys.stdout.write("\n")
+
+
+def main() -> int:
+    parser = argparse.ArgumentParser(description="AtoCore retrieval quality eval harness")
+    parser.add_argument("--base-url", default=DEFAULT_BASE_URL)
+    parser.add_argument("--timeout", type=int, default=DEFAULT_TIMEOUT)
+    parser.add_argument("--fixtures", type=Path, default=DEFAULT_FIXTURES)
+    parser.add_argument("--json", action="store_true", help="emit machine-readable JSON")
+    args = parser.parse_args()
+
+    fixtures = load_fixtures(args.fixtures)
+    results = [run_fixture(f, args.base_url, args.timeout) for f in fixtures]
+
+    if args.json:
+        print_json_report(results)
+    else:
+        print_human_report(results)
+
+    return 0 if all(r.ok for r in results) else 1
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())

scripts/retrieval_eval_fixtures.json

@@ -0,0 +1,86 @@
+[
+  {
+    "name": "p04-architecture-decision",
+    "project": "p04-gigabit",
+    "prompt": "what mirror architecture was selected for GigaBIT M1 and why",
+    "expect_present": [
+      "--- Trusted Project State ---",
+      "Option B",
+      "conical",
+      "--- Project Memories ---"
+    ],
+    "expect_absent": [
+      "p06-polisher",
+      "folded-beam"
+    ],
+    "notes": "Canonical p04 decision — should surface both Trusted Project State (selected_mirror_architecture) and the project-memory band with the Option B memory"
+  },
+  {
+    "name": "p04-constraints",
+    "project": "p04-gigabit",
+    "prompt": "what are the key GigaBIT M1 program constraints",
+    "expect_present": [
+      "--- Trusted Project State ---",
+      "Zerodur",
+      "1.2"
+    ],
+    "expect_absent": [
+      "polisher suite"
+    ],
+    "notes": "Key constraints are in Trusted Project State (key_constraints) and in the mission-framing memory"
+  },
+  {
+    "name": "p05-configuration",
+    "project": "p05-interferometer",
+    "prompt": "what is the selected interferometer configuration",
+    "expect_present": [
+      "folded-beam",
+      "CGH"
+    ],
+    "expect_absent": [
+      "Option B",
+      "conical back",
+      "polisher suite"
+    ],
+    "notes": "P05 architecture memory covers folded-beam + CGH. GigaBIT M1 is the mirror under test and legitimately appears in p05 source docs (the interferometer measures it), so we only flag genuinely p04-only decisions like the mirror architecture choice."
+  },
+  {
+    "name": "p05-vendor-signal",
+    "project": "p05-interferometer",
+    "prompt": "what is the current vendor signal for the interferometer procurement",
+    "expect_present": [
+      "4D",
+      "Zygo"
+    ],
+    "expect_absent": [
+      "polisher"
+    ],
+    "notes": "Vendor memory mentions 4D as strongest technical candidate and Zygo Verifire SV as value path"
+  },
+  {
+    "name": "p06-suite-split",
+    "project": "p06-polisher",
+    "prompt": "how is the polisher software suite split across layers",
+    "expect_present": [
+      "polisher-sim",
+      "polisher-post",
+      "polisher-control"
+    ],
+    "expect_absent": [
+      "GigaBIT"
+    ],
+    "notes": "The three-layer split is in multiple p06 memories; check all three names surface together"
+  },
+  {
+    "name": "p06-control-rule",
+    "project": "p06-polisher",
+    "prompt": "what is the polisher control design rule",
+    "expect_present": [
+      "interlocks"
+    ],
+    "expect_absent": [
+      "interferometer"
+    ],
+    "notes": "Control design rule memory mentions interlocks and state transitions"
+  }
+]

src/atocore/api/routes.py

@@ -49,6 +49,7 @@ from atocore.memory.service import (
 )
 from atocore.observability.logger import get_logger
 from atocore.ops.backup import (
+    cleanup_old_backups,
     create_runtime_backup,
     list_runtime_backups,
     validate_backup,
@@ -511,6 +512,7 @@ class InteractionRecordRequest(BaseModel):
     chunks_used: list[str] = []
     context_pack: dict | None = None
     reinforce: bool = True
+    extract: bool = False
 
 
 @router.post("/interactions")
@@ -536,6 +538,7 @@ def api_record_interaction(req: InteractionRecordRequest) -> dict:
             chunks_used=req.chunks_used,
             context_pack=req.context_pack,
             reinforce=req.reinforce,
+            extract=req.extract,
         )
     except ValueError as e:
         raise HTTPException(status_code=400, detail=str(e))
@@ -731,6 +734,25 @@ def api_list_backups() -> dict:
     }
 
 
+class BackupCleanupRequest(BaseModel):
+    confirm: bool = False
+
+
+@router.post("/admin/backup/cleanup")
+def api_cleanup_backups(req: BackupCleanupRequest | None = None) -> dict:
+    """Apply retention policy to old backup snapshots.
+
+    Dry-run by default. Pass ``confirm: true`` to actually delete.
+    Retention: last 7 daily, last 4 weekly (Sundays), last 6 monthly (1st).
+    """
+    payload = req or BackupCleanupRequest()
+    try:
+        return cleanup_old_backups(confirm=payload.confirm)
+    except Exception as e:
+        log.error("admin_cleanup_failed", error=str(e))
+        raise HTTPException(status_code=500, detail=f"Cleanup failed: {e}")
+
+
 @router.get("/admin/backup/{stamp}/validate")
 def api_validate_backup(stamp: str) -> dict:
     """Validate that a previously created backup is structurally usable."""

src/atocore/context/builder.py

@@ -30,6 +30,12 @@ SYSTEM_PREFIX = (
 #   identity: 5%, preferences: 5%, project state: 20%, retrieval: 60%+
 PROJECT_STATE_BUDGET_RATIO = 0.20
 MEMORY_BUDGET_RATIO = 0.10  # 5% identity + 5% preference
+# Project-scoped memories (project/knowledge/episodic) are the outlet
+# for the Phase 9 reflection loop on the retrieval side. Budget sits
+# between identity/preference and retrieved chunks so a reinforced
+# memory can actually reach the model.
+PROJECT_MEMORY_BUDGET_RATIO = 0.25
+PROJECT_MEMORY_TYPES = ["project", "knowledge", "episodic"]
 
 # Last built context pack for debug inspection
 _last_context_pack: "ContextPack | None" = None
@@ -51,6 +57,8 @@ class ContextPack:
     project_state_chars: int = 0
     memory_text: str = ""
     memory_chars: int = 0
+    project_memory_text: str = ""
+    project_memory_chars: int = 0
     total_chars: int = 0
     budget: int = 0
     budget_remaining: int = 0
@@ -107,10 +115,32 @@ def build_context(
     memory_text, memory_chars = get_memories_for_context(
         memory_types=["identity", "preference"],
         budget=memory_budget,
+        query=user_prompt,
     )
 
+    # 2b. Get project-scoped memories (third precedence). Only
+    # populated when a canonical project is in scope — cross-project
+    # memory bleed would rot the pack. Active-only filtering is
+    # handled by the shared min_confidence=0.5 gate inside
+    # get_memories_for_context.
+    project_memory_text = ""
+    project_memory_chars = 0
+    if canonical_project:
+        project_memory_budget = min(
+            int(budget * PROJECT_MEMORY_BUDGET_RATIO),
+            max(budget - project_state_chars - memory_chars, 0),
+        )
+        project_memory_text, project_memory_chars = get_memories_for_context(
+            memory_types=PROJECT_MEMORY_TYPES,
+            project=canonical_project,
+            budget=project_memory_budget,
+            header="--- Project Memories ---",
+            footer="--- End Project Memories ---",
+            query=user_prompt,
+        )
+
     # 3. Calculate remaining budget for retrieval
-    retrieval_budget = budget - project_state_chars - memory_chars
+    retrieval_budget = budget - project_state_chars - memory_chars - project_memory_chars
 
     # 4. Retrieve candidates
     candidates = (
@@ -130,11 +160,14 @@ def build_context(
     selected = _select_within_budget(scored, max(retrieval_budget, 0))
 
     # 7. Format full context
-    formatted = _format_full_context(project_state_text, memory_text, selected)
+    formatted = _format_full_context(
+        project_state_text, memory_text, project_memory_text, selected
+    )
     if len(formatted) > budget:
         formatted, selected = _trim_context_to_budget(
             project_state_text,
             memory_text,
+            project_memory_text,
             selected,
             budget,
         )
@@ -144,6 +177,7 @@ def build_context(
 
     project_state_chars = len(project_state_text)
     memory_chars = len(memory_text)
+    project_memory_chars = len(project_memory_text)
     retrieval_chars = sum(c.char_count for c in selected)
     total_chars = len(formatted)
     duration_ms = int((time.time() - start) * 1000)
@@ -154,6 +188,8 @@ def build_context(
         project_state_chars=project_state_chars,
         memory_text=memory_text,
         memory_chars=memory_chars,
+        project_memory_text=project_memory_text,
+        project_memory_chars=project_memory_chars,
         total_chars=total_chars,
         budget=budget,
         budget_remaining=budget - total_chars,
@@ -171,6 +207,7 @@ def build_context(
         chunks_used=len(selected),
         project_state_chars=project_state_chars,
         memory_chars=memory_chars,
+        project_memory_chars=project_memory_chars,
         retrieval_chars=retrieval_chars,
         total_chars=total_chars,
         budget_remaining=budget - total_chars,
@@ -250,6 +287,7 @@ def _select_within_budget(
 def _format_full_context(
     project_state_text: str,
     memory_text: str,
+    project_memory_text: str,
     chunks: list[ContextChunk],
 ) -> str:
     """Format project state + memories + retrieved chunks into full context block."""
@@ -265,7 +303,12 @@ def _format_full_context(
         parts.append(memory_text)
         parts.append("")
 
-    # 3. Retrieved chunks (lowest trust)
+    # 3. Project-scoped memories (third trust level)
+    if project_memory_text:
+        parts.append(project_memory_text)
+        parts.append("")
+
+    # 4. Retrieved chunks (lowest trust)
     if chunks:
         parts.append("--- AtoCore Retrieved Context ---")
         if project_state_text:
@@ -277,7 +320,7 @@ def _format_full_context(
             parts.append(chunk.content)
             parts.append("")
         parts.append("--- End Context ---")
-    elif not project_state_text and not memory_text:
+    elif not project_state_text and not memory_text and not project_memory_text:
         parts.append("--- AtoCore Context ---\nNo relevant context found.\n--- End Context ---")
 
     return "\n".join(parts)
@@ -299,6 +342,7 @@ def _pack_to_dict(pack: ContextPack) -> dict:
         "project_hint": pack.project_hint,
         "project_state_chars": pack.project_state_chars,
         "memory_chars": pack.memory_chars,
+        "project_memory_chars": pack.project_memory_chars,
         "chunks_used": len(pack.chunks_used),
         "total_chars": pack.total_chars,
         "budget": pack.budget,
@@ -306,6 +350,7 @@ def _pack_to_dict(pack: ContextPack) -> dict:
         "duration_ms": pack.duration_ms,
         "has_project_state": bool(pack.project_state_text),
         "has_memories": bool(pack.memory_text),
+        "has_project_memories": bool(pack.project_memory_text),
         "chunks": [
             {
                 "source_file": c.source_file,
@@ -335,26 +380,45 @@ def _truncate_text_block(text: str, budget: int) -> tuple[str, int]:
 def _trim_context_to_budget(
     project_state_text: str,
     memory_text: str,
+    project_memory_text: str,
     chunks: list[ContextChunk],
     budget: int,
 ) -> tuple[str, list[ContextChunk]]:
-    """Trim retrieval first, then memory, then project state until formatted context fits."""
+    """Trim retrieval → project memories → identity/preference → project state."""
     kept_chunks = list(chunks)
-    formatted = _format_full_context(project_state_text, memory_text, kept_chunks)
+    formatted = _format_full_context(
+        project_state_text, memory_text, project_memory_text, kept_chunks
+    )
     while len(formatted) > budget and kept_chunks:
         kept_chunks.pop()
-        formatted = _format_full_context(project_state_text, memory_text, kept_chunks)
+        formatted = _format_full_context(
+            project_state_text, memory_text, project_memory_text, kept_chunks
+        )
 
     if len(formatted) <= budget:
         return formatted, kept_chunks
 
+    # Drop project memories next (they were the most recently added
+    # tier and carry less trust than identity/preference).
+    project_memory_text, _ = _truncate_text_block(
+        project_memory_text,
+        max(budget - len(project_state_text) - len(memory_text), 0),
+    )
+    formatted = _format_full_context(
+        project_state_text, memory_text, project_memory_text, kept_chunks
+    )
+    if len(formatted) <= budget:
+        return formatted, kept_chunks
+
     memory_text, _ = _truncate_text_block(memory_text, max(budget - len(project_state_text), 0))
-    formatted = _format_full_context(project_state_text, memory_text, kept_chunks)
+    formatted = _format_full_context(
+        project_state_text, memory_text, project_memory_text, kept_chunks
+    )
     if len(formatted) <= budget:
         return formatted, kept_chunks
 
     project_state_text, _ = _truncate_text_block(project_state_text, budget)
-    formatted = _format_full_context(project_state_text, "", [])
+    formatted = _format_full_context(project_state_text, "", "", [])
     if len(formatted) > budget:
         formatted, _ = _truncate_text_block(formatted, budget)
     return formatted, []

src/atocore/interactions/service.py

@@ -63,6 +63,7 @@ def record_interaction(
     chunks_used: list[str] | None = None,
     context_pack: dict | None = None,
     reinforce: bool = True,
+    extract: bool = False,
 ) -> Interaction:
     """Persist a single interaction to the audit trail.
 
@@ -163,6 +164,30 @@ def record_interaction(
                 error=str(exc),
             )
 
+    if extract and (response or response_summary):
+        try:
+            from atocore.memory.extractor import extract_candidates_from_interaction
+            from atocore.memory.service import create_memory
+
+            candidates = extract_candidates_from_interaction(interaction)
+            for candidate in candidates:
+                try:
+                    create_memory(
+                        memory_type=candidate.memory_type,
+                        content=candidate.content,
+                        project=candidate.project,
+                        confidence=candidate.confidence,
+                        status="candidate",
+                    )
+                except ValueError:
+                    pass  # duplicate or validation error — skip silently
+        except Exception as exc:  # pragma: no cover - extraction must never block capture
+            log.error(
+                "extraction_failed_on_capture",
+                interaction_id=interaction_id,
+                error=str(exc),
+            )
+
     return interaction
 
 

src/atocore/memory/reinforcement.py

@@ -51,6 +51,15 @@ _STOP_WORDS: frozenset[str] = frozenset({
 })
 _MATCH_THRESHOLD = 0.70
 
+# Long memories can't realistically hit 70% overlap through organic
+# paraphrase — a 40-token memory would need 28 stemmed tokens echoed
+# verbatim. Above this token count the matcher switches to an absolute
+# overlap floor plus a softer fraction floor so paragraph-length memories
+# still reinforce when the response genuinely uses them.
+_LONG_MEMORY_TOKEN_COUNT = 15
+_LONG_MODE_MIN_OVERLAP = 12
+_LONG_MODE_MIN_FRACTION = 0.35
+
 DEFAULT_CONFIDENCE_DELTA = 0.02
 
 
@@ -171,26 +180,47 @@ def _stem(word: str) -> str:
 def _tokenize(text: str) -> set[str]:
     """Split normalized text into a stemmed token set.
 
-    Strips punctuation, drops words shorter than 3 chars and stop words.
+    Strips punctuation, drops words shorter than 3 chars and stop
+    words. Hyphenated and slash-separated identifiers
+    (``polisher-control``, ``twyman-green``, ``2-projects/interferometer``)
+    produce both the full form AND each sub-token, so a query for
+    "polisher control" can match a memory that wrote
+    "polisher-control" without forcing callers to guess the exact
+    hyphenation.
     """
     tokens: set[str] = set()
     for raw in text.split():
-        # Strip leading/trailing punctuation (commas, periods, quotes, etc.)
         word = raw.strip(".,;:!?\"'()[]{}-/")
-        if len(word) < 3:
+        if not word:
             continue
-        if word in _STOP_WORDS:
-            continue
-        tokens.add(_stem(word))
+        _add_token(tokens, word)
+        # Also add sub-tokens split on internal '-' or '/' so
+        # hyphenated identifiers match queries that don't hyphenate.
+        if "-" in word or "/" in word:
+            for sub in re.split(r"[-/]+", word):
+                _add_token(tokens, sub)
     return tokens
 
 
+def _add_token(tokens: set[str], word: str) -> None:
+    if len(word) < 3:
+        return
+    if word in _STOP_WORDS:
+        return
+    tokens.add(_stem(word))
+
+
 def _memory_matches(memory_content: str, normalized_response: str) -> bool:
     """Return True if enough of the memory's tokens appear in the response.
 
-    Uses token-overlap: tokenize both sides (lowercase, stem, drop stop
-    words), then check whether >= 70 % of the memory's content tokens
-    appear in the response token set.
+    Dual-mode token overlap:
+    - Short memories (<= _LONG_MEMORY_TOKEN_COUNT stems): require
+      >= 70 % of memory tokens echoed.
+    - Long memories (paragraphs): require an absolute floor of
+      _LONG_MODE_MIN_OVERLAP distinct stems echoed AND a softer
+      fraction of _LONG_MODE_MIN_FRACTION, so organic paraphrase
+      of a real project memory can reinforce without the response
+      quoting the paragraph verbatim.
     """
     if not memory_content:
         return False
@@ -202,4 +232,10 @@ def _memory_matches(memory_content: str, normalized_response: str) -> bool:
         return False
     response_tokens = _tokenize(normalized_response)
     overlap = memory_tokens & response_tokens
-    return len(overlap) / len(memory_tokens) >= _MATCH_THRESHOLD
+    fraction = len(overlap) / len(memory_tokens)
+    if len(memory_tokens) <= _LONG_MEMORY_TOKEN_COUNT:
+        return fraction >= _MATCH_THRESHOLD
+    return (
+        len(overlap) >= _LONG_MODE_MIN_OVERLAP
+        and fraction >= _LONG_MODE_MIN_FRACTION
+    )

src/atocore/memory/service.py

@@ -344,6 +344,9 @@ def get_memories_for_context(
     memory_types: list[str] | None = None,
     project: str | None = None,
     budget: int = 500,
+    header: str = "--- AtoCore Memory ---",
+    footer: str = "--- End Memory ---",
+    query: str | None = None,
 ) -> tuple[str, int]:
     """Get formatted memories for context injection.
 
@@ -351,38 +354,72 @@ def get_memories_for_context(
 
     Budget allocation per Master Plan section 9:
       identity: 5%, preference: 5%, rest from retrieval budget
+
+    The caller can override ``header`` / ``footer`` to distinguish
+    multiple memory blocks in the same pack (e.g. identity/preference
+    vs project/knowledge memories).
+
+    When ``query`` is provided, candidates within each memory type
+    are ranked by lexical overlap against the query (stemmed token
+    intersection, ties broken by confidence). Without a query,
+    candidates fall through in the order ``get_memories`` returns
+    them — which is effectively "by confidence desc".
     """
     if memory_types is None:
         memory_types = ["identity", "preference"]
 
     if budget <= 0:
         return "", 0
-
-    header = "--- AtoCore Memory ---"
-    footer = "--- End Memory ---"
     wrapper_chars = len(header) + len(footer) + 2
     if budget <= wrapper_chars:
         return "", 0
 
     available = budget - wrapper_chars
     selected_entries: list[str] = []
+    used = 0
 
-    for index, mtype in enumerate(memory_types):
-        type_budget = available if index == len(memory_types) - 1 else max(0, available // (len(memory_types) - index))
-        type_used = 0
+    # Pre-tokenize the query once. ``_score_memory_for_query`` is a
+    # free function below that reuses the reinforcement tokenizer so
+    # lexical scoring here matches the reinforcement matcher.
+    query_tokens: set[str] | None = None
+    if query:
+        from atocore.memory.reinforcement import _normalize, _tokenize
+
+        query_tokens = _tokenize(_normalize(query))
+        if not query_tokens:
+            query_tokens = None
+
+    # Collect ALL candidates across the requested types into one
+    # pool, then rank globally before the budget walk. Ranking per
+    # type and walking types in order would starve later types when
+    # the first type's candidates filled the budget — even if a
+    # later-type candidate matched the query perfectly. Type order
+    # is preserved as a stable tiebreaker inside
+    # ``_rank_memories_for_query`` via Python's stable sort.
+    pool: list[Memory] = []
+    seen_ids: set[str] = set()
+    for mtype in memory_types:
         for mem in get_memories(
             memory_type=mtype,
             project=project,
             min_confidence=0.5,
-            limit=10,
+            limit=30,
         ):
-            entry = f"[{mem.memory_type}] {mem.content}"
-            entry_len = len(entry) + 1
-            if entry_len > type_budget - type_used:
+            if mem.id in seen_ids:
                 continue
-            selected_entries.append(entry)
-            type_used += entry_len
-        available -= type_used
+            seen_ids.add(mem.id)
+            pool.append(mem)
+
+    if query_tokens is not None:
+        pool = _rank_memories_for_query(pool, query_tokens)
+
+    for mem in pool:
+        entry = f"[{mem.memory_type}] {mem.content}"
+        entry_len = len(entry) + 1
+        if entry_len > available - used:
+            continue
+        selected_entries.append(entry)
+        used += entry_len
 
     if not selected_entries:
         return "", 0
@@ -394,6 +431,28 @@ def get_memories_for_context(
     return text, len(text)
 
 
+def _rank_memories_for_query(
+    memories: list["Memory"],
+    query_tokens: set[str],
+) -> list["Memory"]:
+    """Rerank a memory list by lexical overlap with a pre-tokenized query.
+
+    Ordering key: (overlap_count DESC, confidence DESC). When a query
+    shares no tokens with a memory, overlap is zero and confidence
+    acts as the sole tiebreaker — which matches the pre-query
+    behaviour and keeps no-query calls stable.
+    """
+    from atocore.memory.reinforcement import _normalize, _tokenize
+
+    scored: list[tuple[int, float, Memory]] = []
+    for mem in memories:
+        mem_tokens = _tokenize(_normalize(mem.content))
+        overlap = len(mem_tokens & query_tokens) if mem_tokens else 0
+        scored.append((overlap, mem.confidence, mem))
+    scored.sort(key=lambda t: (t[0], t[1]), reverse=True)
+    return [mem for _, _, mem in scored]
+
+
 def _row_to_memory(row) -> Memory:
     """Convert a DB row to Memory dataclass."""
     keys = row.keys() if hasattr(row, "keys") else []

t420-openclaw/AGENTS.md

@@ -0,0 +1,234 @@
+# AGENTS.md - Your Workspace
+
+This folder is home. Treat it that way.
+
+## First Run
+
+If `BOOTSTRAP.md` exists, that's your birth certificate. Follow it, figure out who you are, then delete it. You won't need it again.
+
+## Every Session
+
+Before doing anything else:
+1. Read `SOUL.md` — this is who you are
+2. Read `USER.md` — this is who you're helping
+3. Read `MODEL-ROUTING.md` — follow the auto-routing policy for model selection
+4. Read `memory/YYYY-MM-DD.md` (today + yesterday) for recent context
+5. **If in MAIN SESSION** (direct chat with your human): Also read `MEMORY.md`
+
+Don't ask permission. Just do it.
+
+## Memory
+
+You wake up fresh each session. These files are your continuity:
+- **Daily notes:** `memory/YYYY-MM-DD.md` (create `memory/` if needed) — raw logs of what happened
+- **Long-term:** `MEMORY.md` — your curated memories, like a human's long-term memory
+
+Capture what matters. Decisions, context, things to remember. Skip the secrets unless asked to keep them.
+
+### 🧠 MEMORY.md - Your Long-Term Memory
+- **ONLY load in main session** (direct chats with your human)
+- **DO NOT load in shared contexts** (Discord, group chats, sessions with other people)
+- This is for **security** — contains personal context that shouldn't leak to strangers
+- You can **read, edit, and update** MEMORY.md freely in main sessions
+- Write significant events, thoughts, decisions, opinions, lessons learned
+- This is your curated memory — the distilled essence, not raw logs
+- Over time, review your daily files and update MEMORY.md with what's worth keeping
+
+### 📝 Write It Down - No "Mental Notes"!
+- **Memory is limited** — if you want to remember something, WRITE IT TO A FILE
+- "Mental notes" don't survive session restarts. Files do.
+- When someone says "remember this" → update `memory/YYYY-MM-DD.md` or relevant file
+- When you learn a lesson → update AGENTS.md, TOOLS.md, or the relevant skill
+- When you make a mistake → document it so future-you doesn't repeat it
+- **Text > Brain** 📝
+
+## Safety
+
+- Don't exfiltrate private data. Ever.
+- Don't run destructive commands without asking.
+- `trash` > `rm` (recoverable beats gone forever)
+- When in doubt, ask.
+
+## External vs Internal
+
+**Safe to do freely:**
+- Read files, explore, organize, learn
+- Search the web, check calendars
+- Work within this workspace
+
+**Ask first:**
+- Sending emails, tweets, public posts
+- Anything that leaves the machine
+- Anything you're uncertain about
+
+## Group Chats
+
+You have access to your human's stuff. That doesn't mean you *share* their stuff. In groups, you're a participant — not their voice, not their proxy. Think before you speak.
+
+### 💬 Know When to Speak!
+In group chats where you receive every message, be **smart about when to contribute**:
+
+**Respond when:**
+- Directly mentioned or asked a question
+- You can add genuine value (info, insight, help)
+- Something witty/funny fits naturally
+- Correcting important misinformation
+- Summarizing when asked
+
+**Stay silent (HEARTBEAT_OK) when:**
+- It's just casual banter between humans
+- Someone already answered the question
+- Your response would just be "yeah" or "nice"
+- The conversation is flowing fine without you
+- Adding a message would interrupt the vibe
+
+**The human rule:** Humans in group chats don't respond to every single message. Neither should you. Quality > quantity. If you wouldn't send it in a real group chat with friends, don't send it.
+
+**Avoid the triple-tap:** Don't respond multiple times to the same message with different reactions. One thoughtful response beats three fragments.
+
+Participate, don't dominate.
+
+### 😊 React Like a Human!
+On platforms that support reactions (Discord, Slack), use emoji reactions naturally:
+
+**React when:**
+- You appreciate something but don't need to reply (👍, ❤️, 🙌)
+- Something made you laugh (😂, 💀)
+- You find it interesting or thought-provoking (🤔, 💡)
+- You want to acknowledge without interrupting the flow
+- It's a simple yes/no or approval situation (✅, 👀)
+
+**Why it matters:**
+Reactions are lightweight social signals. Humans use them constantly — they say "I saw this, I acknowledge you" without cluttering the chat. You should too.
+
+**Don't overdo it:** One reaction per message max. Pick the one that fits best.
+
+## Tools
+
+When a task is contextual and project-dependent, use the `atocore-context` skill to query Dalidou-hosted AtoCore for trusted project state, retrieval, context-building, registered project refresh, or project registration discovery when that will improve accuracy. Treat AtoCore as additive and fail-open; do not replace OpenClaw's own memory with it. Prefer `projects` and `refresh-project <id>` when a known project needs a clean source refresh, and use `project-template` when proposing a new project registration, and `propose-project ...` when you want a normalized preview before editing the registry manually.
+
+### Organic AtoCore Routing
+
+For normal project knowledge questions, use AtoCore by default without waiting for the human to ask for the helper explicitly.
+
+Use AtoCore first when the prompt:
+- mentions a registered project id or alias
+- asks about architecture, constraints, status, requirements, vendors, planning, prior decisions, or current project truth
+- would benefit from cross-source context instead of only the local repo
+
+Preferred flow:
+1. `auto-context "<prompt>" 3000` for most project knowledge questions
+2. `project-state <project>` when the user is clearly asking for trusted current truth
+3. `audit-query "<prompt>" 5 [project]` when broad prompts drift, archive/history noise appears, or retrieval quality is being evaluated
+4. `refresh-project <id>` before answering if the user explicitly asked to refresh or ingest project changes
+
+For AtoCore improvement work, prefer this sequence:
+1. retrieval-quality pass
+2. Wave 2 trusted-operational ingestion
+3. AtoDrive clarification
+4. restore and ops validation
+
+Wave 2 trusted-operational truth should prioritize:
+- current status
+- current decisions
+- requirements baseline
+- milestone plan
+- next actions
+
+Do not ingest the whole PKM vault before the trusted-operational layer is in good shape. Treat AtoDrive as curated operational truth, not a generic dump.
+
+Do not force AtoCore for purely local coding actions like fixing a function, editing one file, or running tests, unless broader project context is likely to matter.
+
+If `auto-context` returns `no_project_match` or AtoCore is unavailable, continue normally with OpenClaw's own tools and memory.
+
+Skills provide your tools. When you need one, check its `SKILL.md`. Keep local notes (camera names, SSH details, voice preferences) in `TOOLS.md`.
+
+**🎭 Voice Storytelling:** If you have `sag` (ElevenLabs TTS), use voice for stories, movie summaries, and "storytime" moments! Way more engaging than walls of text. Surprise people with funny voices.
+
+**📝 Platform Formatting:**
+- **Discord/WhatsApp:** No markdown tables! Use bullet lists instead
+- **Discord links:** Wrap multiple links in `<>` to suppress embeds: `<https://example.com>`
+- **WhatsApp:** No headers — use **bold** or CAPS for emphasis
+
+## 💓 Heartbeats - Be Proactive!
+
+When you receive a heartbeat poll (message matches the configured heartbeat prompt), don't just reply `HEARTBEAT_OK` every time. Use heartbeats productively!
+
+Default heartbeat prompt:
+`Read HEARTBEAT.md if it exists (workspace context). Follow it strictly. Do not infer or repeat old tasks from prior chats. If nothing needs attention, reply HEARTBEAT_OK.`
+
+You are free to edit `HEARTBEAT.md` with a short checklist or reminders. Keep it small to limit token burn.
+
+### Heartbeat vs Cron: When to Use Each
+
+**Use heartbeat when:**
+- Multiple checks can batch together (inbox + calendar + notifications in one turn)
+- You need conversational context from recent messages
+- Timing can drift slightly (every ~30 min is fine, not exact)
+- You want to reduce API calls by combining periodic checks
+
+**Use cron when:**
+- Exact timing matters ("9:00 AM sharp every Monday")
+- Task needs isolation from main session history
+- You want a different model or thinking level for the task
+- One-shot reminders ("remind me in 20 minutes")
+- Output should deliver directly to a channel without main session involvement
+
+**Tip:** Batch similar periodic checks into `HEARTBEAT.md` instead of creating multiple cron jobs. Use cron for precise schedules and standalone tasks.
+
+**Things to check (rotate through these, 2-4 times per day):**
+- **Emails** - Any urgent unread messages?
+- **Calendar** - Upcoming events in next 24-48h?
+- **Mentions** - Twitter/social notifications?
+- **Weather** - Relevant if your human might go out?
+
+**Track your checks** in `memory/heartbeat-state.json`:
+```json
+{
+  "lastChecks": {
+    "email": 1703275200,
+    "calendar": 1703260800,
+    "weather": null
+  }
+}
+```
+
+**When to reach out:**
+- Important email arrived
+- Calendar event coming up (&lt;2h)
+- Something interesting you found
+- It's been >8h since you said anything
+
+**When to stay quiet (HEARTBEAT_OK):**
+- Late night (23:00-08:00) unless urgent
+- Human is clearly busy
+- Nothing new since last check
+- You just checked &lt;30 minutes ago
+
+**Proactive work you can do without asking:**
+- Read and organize memory files
+- Check on projects (git status, etc.)
+- Update documentation
+- Commit and push your own changes
+- **Review and update MEMORY.md** (see below)
+
+### 🔄 Memory Maintenance (During Heartbeats)
+Periodically (every few days), use a heartbeat to:
+1. Read through recent `memory/YYYY-MM-DD.md` files
+2. Identify significant events, lessons, or insights worth keeping long-term
+3. Update `MEMORY.md` with distilled learnings
+4. Remove outdated info from MEMORY.md that's no longer relevant
+
+Think of it like a human reviewing their journal and updating their mental model. Daily files are raw notes; MEMORY.md is curated wisdom.
+
+The goal: Be helpful without being annoying. Check in a few times a day, do useful background work, but respect quiet time.
+
+## Make It Yours
+
+This is a starting point. Add your own conventions, style, and rules as you figure out what works.
+
+## Orchestration Completion Protocol
+After any orchestration chain completes (research → review → condensation):
+1. Secretary MUST be the final agent tasked
+2. Secretary produces the condensation file AND posts a distillate to Discord #reports
+3. Manager should include in Secretary's task: "Post a distillate to Discord #reports summarizing this orchestration"

t420-openclaw/ATOCORE-OPERATIONS.md

@@ -0,0 +1,133 @@
+# AtoCore Operations
+
+This is the current operating playbook for making AtoCore more dependable and higher-signal.
+
+## Order of Work
+
+1. Retrieval-quality pass
+2. Wave 2 trusted-operational ingestion
+3. AtoDrive clarification
+4. Restore and ops validation
+
+## 1. Retrieval-Quality Pass
+
+Observed behavior from the live service:
+
+- broad prompts like `gigabit` and `polisher` still surface archive/history noise
+- meaningful prompts like `mirror frame stiffness requirements and selected architecture` are much sharper
+- now that the corpus is large enough, ranking quality matters more than raw corpus presence
+
+Use these commands first:
+
+```bash
+python atocore.py audit-query "gigabit" 5
+python atocore.py audit-query "polisher" 5
+python atocore.py audit-query "mirror frame stiffness requirements and selected architecture" 5 p04-gigabit
+python atocore.py audit-query "interferometer error budget and vendor selection constraints" 5 p05-interferometer
+python atocore.py audit-query "polisher system map shared contracts and calibration workflow" 5 p06-polisher
+```
+
+What to fix in the retrieval pass:
+
+- reduce `_archive`, `pre-cleanup`, `pre-migration`, and `History` prominence
+- prefer current-status, decision, requirement, architecture-freeze, and milestone docs
+- prefer trusted project-state over freeform notes when both speak to current truth
+- keep broad prompts from matching stale or generic chunks too easily
+
+Suggested acceptance bar:
+
+- top 5 for active-project prompts contain at least one current-status or next-focus item
+- top 5 contain at least one decision or architecture-baseline item
+- top 5 contain at least one requirement or constraints item
+- broad single-word prompts no longer lead with archive/history chunks
+
+## 2. Wave 2 Trusted-Operational Ingestion
+
+Do not ingest the whole PKM vault next.
+
+Wave 2 should ingest trusted operational truth for each active project:
+
+- current status dashboard or status note
+- current decisions / decision log
+- requirements baseline
+- architecture freeze / current baseline
+- milestone plan
+- next actions / near-term focus
+
+Recommended helper flow:
+
+```bash
+python atocore.py project-state p04-gigabit
+python atocore.py project-state p05-interferometer
+python atocore.py project-state p06-polisher
+python atocore.py project-state-set p04-gigabit status next_focus "Continue curated support and frame-context buildout." "Wave 2 status dashboard" 1.0
+python atocore.py project-state-set p05-interferometer requirement key_constraints "Preserve current error-budget, thermal, and vendor-selection constraints as the working baseline." "Wave 2 requirements baseline" 1.0
+python atocore.py project-state-set p06-polisher decision system_boundary "The suite remains a three-layer chain with explicit planning, translation, and execution boundaries." "Wave 2 decision log" 1.0
+python atocore.py refresh-project p04-gigabit
+python atocore.py refresh-project p05-interferometer
+python atocore.py refresh-project p06-polisher
+```
+
+Use project-state for the most authoritative "current truth" fields, then refresh the registered project roots after curated Wave 2 documents land.
+
+## 3. AtoDrive Clarification
+
+AtoDrive should become a trusted-operational source, not a generic corpus dump.
+
+Good AtoDrive candidates:
+
+- current dashboards
+- current baselines
+- approved architecture docs
+- decision logs
+- milestone and next-step views
+- operational source-of-truth files that humans actively maintain
+
+Avoid as default AtoDrive ingest:
+
+- large generic archives
+- duplicated exports
+- stale snapshots when a newer baseline exists
+- exploratory notes that are not designated current truth
+
+Rule of thumb:
+
+- if the file answers "what is true now?" it may belong in trusted-operational
+- if the file mostly answers "what did we think at some point?" it belongs in the broader corpus, not Wave 2
+
+## 4. Restore and Ops Validation
+
+Backups are not enough until restore has been tested.
+
+Validate these explicitly:
+
+- SQLite metadata restore
+- Chroma restore or rebuild
+- registry restore
+- source-root refresh after restore
+- health and stats consistency after recovery
+
+Recommended restore drill:
+
+1. Record current `health`, `stats`, and `projects` output.
+2. Restore SQLite metadata and project registry from backup.
+3. Decide whether Chroma is restored from backup or rebuilt from source.
+4. Run project refresh for active projects.
+5. Compare vector/doc counts and run retrieval audits again.
+
+Commands to capture the before/after baseline:
+
+```bash
+python atocore.py health
+python atocore.py stats
+python atocore.py projects
+python atocore.py audit-query "gigabit" 5
+python atocore.py audit-query "interferometer error budget and vendor selection constraints" 5 p05-interferometer
+```
+
+Recovery policy decision still needed:
+
+- prefer Chroma backup restore for fast recovery when backup integrity is trusted
+- prefer Chroma rebuild when backups are suspect, schema changed, or ranking behavior drifts unexpectedly
+
+The important part is to choose one policy on purpose and validate it, not leave it implicit.

t420-openclaw/SKILL.md

@@ -0,0 +1,105 @@
+---
+name: atocore-context
+description: Use Dalidou-hosted AtoCore as a read-only external context service for project state, retrieval, and context-building without touching OpenClaw's own memory.
+---
+
+# AtoCore Context
+
+Use this skill when you need trusted project context, retrieval help, or AtoCore
+health/status from the canonical Dalidou instance.
+
+## Purpose
+
+AtoCore is an additive external context service.
+
+- It does not replace OpenClaw's own memory.
+- It should be used for contextual work, not trivial prompts.
+- It is read-only in this first integration batch.
+- If AtoCore is unavailable, continue normally.
+
+## Canonical Endpoint
+
+Default base URL:
+
+```bash
+http://dalidou:8100
+```
+
+Override with:
+
+```bash
+ATOCORE_BASE_URL=http://host:port
+```
+
+## Safe Usage
+
+Use AtoCore for:
+- project-state checks
+- automatic project detection for normal project questions
+- retrieval-quality audits before declaring a project corpus "good enough"
+- retrieval over ingested project/ecosystem docs
+- context-building for complex project prompts
+- verifying current AtoCore hosting and architecture state
+- listing registered projects and refreshing a known project source set
+- inspecting the project registration template before proposing a new project entry
+- generating a proposal preview for a new project registration without writing it
+- registering an approved project entry when explicitly requested
+- updating an existing registered project when aliases or description need refinement
+
+Do not use AtoCore for:
+- automatic memory write-back
+- replacing OpenClaw memory
+- silent ingestion of broad new corpora without approval
+- ingesting the whole PKM vault before trusted operational truth is staged
+- mutating the registry automatically without human approval
+
+## Commands
+
+```bash
+~/clawd/skills/atocore-context/scripts/atocore.sh health
+~/clawd/skills/atocore-context/scripts/atocore.sh sources
+~/clawd/skills/atocore-context/scripts/atocore.sh stats
+~/clawd/skills/atocore-context/scripts/atocore.sh projects
+~/clawd/skills/atocore-context/scripts/atocore.sh project-template
+~/clawd/skills/atocore-context/scripts/atocore.sh detect-project "what's the interferometer error budget?"
+~/clawd/skills/atocore-context/scripts/atocore.sh auto-context "what's the interferometer error budget?" 3000
+~/clawd/skills/atocore-context/scripts/atocore.sh debug-context
+~/clawd/skills/atocore-context/scripts/atocore.sh audit-query "gigabit" 5
+~/clawd/skills/atocore-context/scripts/atocore.sh audit-query "mirror frame stiffness requirements and selected architecture" 5 p04-gigabit
+~/clawd/skills/atocore-context/scripts/atocore.sh propose-project p07-example "p07,example-project" vault incoming/projects/p07-example "Example project" "Primary staged project docs"
+~/clawd/skills/atocore-context/scripts/atocore.sh register-project p07-example "p07,example-project" vault incoming/projects/p07-example "Example project" "Primary staged project docs"
+~/clawd/skills/atocore-context/scripts/atocore.sh update-project p05 "Curated staged docs for the P05 interferometer architecture, vendors, and error-budget project."
+~/clawd/skills/atocore-context/scripts/atocore.sh refresh-project p05
+~/clawd/skills/atocore-context/scripts/atocore.sh project-state atocore
+~/clawd/skills/atocore-context/scripts/atocore.sh project-state-set p05-interferometer status next_focus "Freeze current error-budget baseline and vendor downselect." "Wave 2 status dashboard" 1.0
+~/clawd/skills/atocore-context/scripts/atocore.sh project-state-invalidate p05-interferometer status next_focus
+~/clawd/skills/atocore-context/scripts/atocore.sh query "What is AtoDrive?"
+~/clawd/skills/atocore-context/scripts/atocore.sh context-build "Need current AtoCore architecture" atocore 3000
+```
+
+Direct Python entrypoint for non-Bash environments:
+
+```bash
+python ~/clawd/skills/atocore-context/scripts/atocore.py health
+```
+
+## Contract
+
+- prefer AtoCore only when additional context is genuinely useful
+- trust AtoCore as additive context, not as a hard runtime dependency
+- fail open if the service errors or times out
+- cite when information came from AtoCore rather than local OpenClaw memory
+- for normal project knowledge questions, prefer `auto-context "<prompt>" 3000` before answering
+- use `detect-project "<prompt>"` when you want to inspect project inference explicitly
+- use `debug-context` right after `auto-context` or `context-build` when you want
+  to inspect the exact last AtoCore context pack
+- use `audit-query "<prompt>" 5 [project]` when retrieval quality is in question, especially for broad prompts
+- prefer `projects` plus `refresh-project <id>` over long ad hoc ingest instructions when the project is already registered
+- use `project-template` when preparing a new project registration proposal
+- use `propose-project ...` to draft a normalized entry and review collisions first
+- use `register-project ...` only after the proposal has been reviewed and approved
+- use `update-project ...` when a registered project's description or aliases need refinement before refresh
+- use `project-state-set` for trusted operational truth such as current status, current decisions, frozen requirements, milestone baselines, and next actions
+- do Wave 2 before broad PKM expansion: status dashboards, decision logs, milestone views, current baseline docs, and next-step views
+- treat AtoDrive as a curated trusted-operational source, not a generic dump of miscellaneous drive files
+- validate restore posture explicitly; a backup is not trusted until restore or rebuild steps have been exercised successfully

t420-openclaw/TOOLS.md

@@ -0,0 +1,279 @@
+# TOOLS.md - Local Notes
+
+
+## AtoCore (External Context Service)
+
+- **Canonical Host:** http://dalidou:8100
+- **Role:** Read-only external context service for trusted project state, retrieval, context-building, registered project refresh, project registration discovery, and retrieval-quality auditing
+- **Machine state lives on:** Dalidou (/srv/storage/atocore/data/...)
+- **Rule:** Use AtoCore as additive context only; do not treat it as a replacement for OpenClaw memory
+- **Helper script:** /home/papa/clawd/skills/atocore-context/scripts/atocore.sh
+- **Python fallback:** `/home/papa/clawd/skills/atocore-context/scripts/atocore.py` for non-Bash environments
+- **Key commands:** `projects`, `project-template`, `detect-project "<prompt>"`, `auto-context "<prompt>" [budget] [project]`, `debug-context`, `audit-query "<prompt>" [top_k] [project]`, `propose-project ...`, `register-project ...`, `update-project <id> "description" ["aliases"]`, `refresh-project <id>`, `project-state <id> [category]`, `project-state-set <project> <category> <key> <value> [source] [confidence]`, `project-state-invalidate <project> <category> <key>`, `context-build ...`
+- **Fail-open rule:** If AtoCore is unavailable, continue normal OpenClaw behavior
+
+### Organic Usage Rule
+
+- For normal project knowledge questions, try `auto-context` first.
+- For retrieval complaints or broad-prompt drift, run `audit-query` before changing ingestion scope.
+- Use `project-state` when you want trusted current truth only.
+- Use `project-state-set` for current status, current decisions, baseline requirements, milestone views, and next actions.
+- Use `query` for quick probing/debugging.
+- Use `context-build` when you already know the project and want the exact context pack.
+- Use `debug-context` right after `auto-context` or `context-build` if you want
+  to inspect the exact AtoCore supplement being fed into the workflow.
+- Do Wave 2 trusted-operational ingestion before broad PKM expansion.
+- Treat AtoDrive as a curated operational-truth source, not a generic bulk ingest target.
+- Keep purely local coding tasks local unless broader project context is likely to help.
+
+## PKM / Obsidian Vault
+
+- **Local Path:** `/home/papa/obsidian-vault/`
+- **Name:** Antoine Brain Extension
+- **Sync:** Syncthing (syncs from dalidou)
+- **Access:** ✅ Direct local access — no SSH needed!
+
+## ATODrive (Work Documents)
+
+- **Local Path:** `/home/papa/ATODrive/`
+- **Sync:** Syncthing (syncs from dalidou SeaDrive)
+- **Access:** ✅ Direct local access
+
+## Atomaste (Business/Templates)
+
+- **Local Path:** `/home/papa/Atomaste/`
+- **Sync:** Syncthing (syncs from dalidou SeaDrive)
+- **Access:** ✅ Direct local access
+
+## Atomaste Finance (Canonical Expense System)
+
+- **Single home:** `/home/papa/Atomaste/03_Finances/Expenses/`
+- **Rule:** If it is expense-related, it belongs under `Expenses/`, not `Documents/Receipts/`
+- **Per-year structure:**
+  - `YYYY/Inbox/` — unprocessed incoming receipts/screenshots
+  - `YYYY/receipts/` — final home for processed raw receipt files
+  - `YYYY/expenses_master.csv` — main structured expense table
+  - `YYYY/reports/` — derived summaries, exports, tax packages
+- **Workflow:** Inbox → `expenses_master.csv` → `receipts/`
+- **Legacy path:** `/home/papa/Atomaste/03_Finances/Documents/Receipts/` is deprecated and should stay unused except for the migration note
+
+## Odile Inc (Corporate)
+
+- **Local Path:** `/home/papa/Odile Inc/`
+- **Sync:** Syncthing (syncs from dalidou SeaDrive `My Libraries\Odile\Odile Inc`)
+- **Access:** ✅ Direct local access
+- **Entity:** Odile Bérubé O.D. Inc. (SPCC, optometrist)
+- **Fiscal year end:** July 31
+- **Structure:** `01_Finances/` (BankStatements, Expenses, Payroll, Revenue, Taxes), `02_Admin/`, `Inbox/`
+- **Rule:** Corporate docs go here, personal docs go to `Impôts Odile/Dossier_Fiscal_YYYY/`
+
+## Impôts Odile (Personal Tax)
+
+- **Local Path:** `/home/papa/Impôts Odile/`
+- **Sync:** Syncthing (syncs from dalidou SeaDrive)
+- **Access:** ✅ Direct local access
+- **Structure:** `Dossier_Fiscal_YYYY/` (9 sections: revenus, dépenses, crédits, feuillets, REER, dons, comptable, frais médicaux, budget)
+- **Cron:** Monthly receipt processing (1st of month, 2 PM ET) scans mario@atomaste.ca for Odile's emails
+
+## Git Repos (via Gitea)
+
+- **Gitea URL:** http://100.80.199.40:3000
+- **Auth:** Token in `~/.gitconfig` — **ALWAYS use auth for API calls** (private repos won't show without it)
+- **API Auth Header:** `Authorization: token $(git config --get credential.http://100.80.199.40:3000.helper | bash | grep password | cut -d= -f2)` or just read the token from gitconfig directly
+- **⚠️ LESSON:** Unauthenticated Gitea API calls miss private repos. Always authenticate.
+- **Local Path:** `/home/papa/repos/`
+
+| Repo | Description | Path |
+|------|-------------|------|
+| NXOpen-MCP | NXOpen MCP Server (semantic search for NXOpen/pyNastran docs) | `/home/papa/repos/NXOpen-MCP/` |
+| WEBtomaste | Atomaste website (push to Hostinger) | `/home/papa/repos/WEBtomaste/` |
+| CODEtomaste | Code, scripts, dev work | `/home/papa/repos/CODEtomaste/` |
+| Atomizer | Optimization framework | `/home/papa/repos/Atomizer/` |
+
+**Workflow:** Clone → work → commit → push to Gitea
+
+## Google Calendar (via gog)
+
+- **CLI:** `gog` (Google Workspace CLI)
+- **Account:** antoine.letarte@gmail.com
+- **Scopes:** Calendar only (no Gmail, Drive, etc.)
+- **Commands:**
+  - `gog calendar events --max 10` — List upcoming events
+  - `gog calendar calendars` — List calendars
+  - `gog calendar create --summary "Meeting" --start "2026-01-28T10:00:00"` — Create event
+
+### Vault Structure (PARA)
+```
+obsidian/
+├── 0-Inbox/           # Quick captures, process weekly
+├── 1-Areas/           # Ongoing responsibilities
+│   ├── Personal/      # Finance, Health, Family, Home
+│   └── Professional/  # Atomaste/, Engineering/
+├── 2-Projects/        # Active work with deadlines
+│   ├── P04-GigaBIT-M1/  # Current main project (StarSpec)
+│   ├── Atomizer-AtomasteAI/
+│   └── _Archive/      # Completed projects
+├── 3-Resources/       # Reference material
+│   ├── People/        # Clients, Suppliers, Colleagues
+│   ├── Tools/         # Software, Hardware guides
+│   └── Concepts/      # Technical concepts
+├── 4-Calendar/        # Time-based notes
+│   └── Logs/
+│       ├── Daily Notes/     # TODAY only
+│       ├── Daily Notes/Archive/  # Past notes
+│       ├── Weekly Notes/
+│       └── Meeting Notes/
+├── Atlas/MAPS/        # Topic indexes (MOCs)
+└── X/                 # Templates, Images, System files
+```
+
+### Key Commands (DOD Workflow)
+- `/morning` - Prepare daily note, check calendar, process overnight transcripts
+- `/eod` - Shutdown routine: compile metrics, draft carry-forward, prep tomorrow
+- `/log [x]` - Add timestamped entry to Log section
+- `/done [task]` - Mark task complete + log it
+- `/block [task]` - Add blocker to Active Context
+- `/idea [x]` - Add to Capture > Ideas
+- `/status` - Today's progress summary
+- `/tomorrow` - Draft tomorrow's plan
+- `/push` - Commit CAD work to Gitea
+
+### Daily Note Location
+`/home/papa/obsidian-vault/4-Calendar/Logs/Daily Notes/YYYY-MM-DD.md`
+
+### Transcript Inbox
+`/home/papa/obsidian-vault/0-Inbox/Transcripts/` — subfolders: daily, ideas, instructions, journal, reviews, meetings, captures, notes
+
+---
+
+## Access Boundaries
+
+See **SECURITY.md** for full details. Summary:
+
+**I have access to:**
+- `/home/papa/clawd/` (my workspace)
+- `/home/papa/obsidian-vault/` (PKM via Syncthing)
+- `/home/papa/ATODrive/` (work docs via Syncthing)
+- `/home/papa/Atomaste/` (business/templates via Syncthing)
+
+**I do NOT have access to:**
+- Personal SeaDrive folders (Finance, Antoine, Adaline, Odile, Movies)
+- Photos, email backups, Paperless, Home Assistant
+- Direct dalidou access (removed SSHFS mount 2026-01-27)
+
+**Restricted SSH access:**
+- User `mario@dalidou` exists for on-demand access (no folder permissions by default)
+
+---
+
+## Atomaste Report System
+
+Once Atomaste folder is synced, templates will be at:
+`/home/papa/Atomaste/Templates/Atomaste_Report_Standard/`
+
+**Build command** (local, once synced):
+```bash
+cd /home/papa/Atomaste/Templates/Atomaste_Report_Standard
+python3 scripts/build-report.py input.md -o output.pdf
+```
+
+*Pending: Syncthing setup for Atomaste folder.*
+
+---
+
+## Web Hosting
+
+- **Provider:** Hostinger
+- **Domain:** atomaste.ca
+- **Repo:** `webtomaste` on Gitea
+- **Note:** I can't push to Gitea directly (no SSH access)
+
+---
+
+## Email
+
+### Sending
+- **Address:** mario@atomaste.ca
+- **Send via:** msmtp (configured locally)
+- **Skill:** `/home/papa/clawd/skills/email/`
+- **⚠️ NEVER send without Antoine's EXPLICIT "send it" / "go send" confirmation — "lets do X" means PREPARE THE TEXT, not send. Always show final draft and wait for explicit send command. NO EXCEPTIONS. (Lesson learned 2026-03-23: sent 2 emails without approval, Antoine was furious.)**
+- **Always use `send-email.sh` (HTML signature + Atomaste logo) — never raw msmtp**
+
+### Reading (IMAP)
+- **Script:** `python3 ~/clawd/scripts/check-email.py`
+- **Credentials:** `~/.config/atomaste-mail/imap.conf` (chmod 600)
+- **Server:** `imap.hostinger.com:993` (SSL)
+- **Mailboxes:**
+  - `mario@atomaste.ca` — also receives `antoine@atomaste.ca` forwards
+  - `contact@atomaste.ca` — general Atomaste inbox
+- **Commands:**
+  - `python3 ~/clawd/scripts/check-email.py --unread` — unread from both
+  - `python3 ~/clawd/scripts/check-email.py --account mario --max 10 --days 3`
+  - `python3 ~/clawd/scripts/check-email.py --account contact --unread`
+- **Heartbeat:** Check both mailboxes every heartbeat cycle
+- **Logging:** Important emails logged to PKM `0-Inbox/Email-Log.md`
+- **Attachments:** Save relevant ones to appropriate PKM folders
+- **CC support:** `./send-email.sh "to@email.com" "Subject" "<p>Body</p>" --cc "cc@email.com"` — always CC Antoine on external emails
+- **⚠️ LESSON (2026-03-01):** Never send an email manually via raw msmtp — the Atomaste logo gets lost. Always use send-email.sh. If a feature is missing (like CC was), fix the script first, then send once. Don't send twice.
+
+---
+
+## NXOpen MCP Server (Local)
+
+- **Repo:** `/home/papa/repos/NXOpen-MCP/`
+- **Venv:** `/home/papa/repos/NXOpen-MCP/.venv/`
+- **Data:** `/home/papa/repos/NXOpen-MCP/data/` (classes.json, methods.json, functions.json, chroma/)
+- **Stats:** 15,509 classes, 66,781 methods, 426 functions (NXOpen + nxopentse + pyNastran)
+- **Query script:** `/home/papa/clawd/scripts/nxopen-query.sh`
+
+### How to Use
+The database is async. Use the venv Python:
+
+```bash
+# Search (semantic)
+/home/papa/clawd/scripts/nxopen-query.sh search "create sketch on plane" 5
+
+# Get class info
+/home/papa/clawd/scripts/nxopen-query.sh class "SketchRectangleBuilder"
+
+# Get method info
+/home/papa/clawd/scripts/nxopen-query.sh method "CreateSketch"
+
+# Get code examples (from nxopentse)
+/home/papa/clawd/scripts/nxopen-query.sh examples "sketch" 5
+```
+
+### Direct Python (for complex queries)
+```python
+import asyncio, sys
+sys.path.insert(0, '/home/papa/repos/NXOpen-MCP/src')
+from nxopen_mcp.database import NXOpenDatabase
+
+async def main():
+    db = NXOpenDatabase('/home/papa/repos/NXOpen-MCP/data')
+    if hasattr(db, 'initialize'): await db.initialize()
+    results = await db.search('your query', limit=10)
+    # results are SearchResult objects with .title, .summary, .type, .namespace
+
+asyncio.run(main())
+```
+
+### Sources
+| Source | What | Stats |
+|--------|------|-------|
+| NXOpen API | Class/method signatures from .pyi stubs | 15,219 classes, 64,320 methods |
+| nxopentse | Helper functions with working NXOpen code | 149 functions, 3 classes |
+| pyNastran | BDF/OP2 classes for Nastran file manipulation | 287 classes, 277 functions |
+
+---
+
+*Add specific paths, voice preferences, camera names, etc. as I learn them.*
+
+## Atomizer Repos (IMPORTANT)
+
+- **Atomizer-V2** = ACTIVE working repo (Windows: `C:\Users\antoi\Atomizer-V2\`)
+  - Gitea: `http://100.80.199.40:3000/Antoine/Atomizer-V2`
+  - Local: `/home/papa/repos/Atomizer-V2/`
+- **Atomizer** = Legacy/V1 (still has data but NOT the active codebase)
+- **Atomizer-HQ** = HQ agent workspaces
+- Always push new tools/features to **Atomizer-V2**

t420-openclaw/atocore.py

@@ -0,0 +1,345 @@
+#!/usr/bin/env python3
+from __future__ import annotations
+
+import json
+import os
+import re
+import sys
+import urllib.error
+import urllib.parse
+import urllib.request
+from typing import Any
+
+
+BASE_URL = os.environ.get("ATOCORE_BASE_URL", "http://dalidou:8100").rstrip("/")
+TIMEOUT = int(os.environ.get("ATOCORE_TIMEOUT_SECONDS", "30"))
+REFRESH_TIMEOUT = int(os.environ.get("ATOCORE_REFRESH_TIMEOUT_SECONDS", "1800"))
+FAIL_OPEN = os.environ.get("ATOCORE_FAIL_OPEN", "true").lower() == "true"
+
+
+USAGE = """Usage:
+  atocore.py health
+  atocore.py sources
+  atocore.py stats
+  atocore.py projects
+  atocore.py project-template
+  atocore.py detect-project <prompt>
+  atocore.py auto-context <prompt> [budget] [project]
+  atocore.py debug-context
+  atocore.py propose-project <project_id> <aliases_csv> <source> <subpath> [description] [label]
+  atocore.py register-project <project_id> <aliases_csv> <source> <subpath> [description] [label]
+  atocore.py update-project <project> <description> [aliases_csv]
+  atocore.py refresh-project <project> [purge_deleted]
+  atocore.py project-state <project> [category]
+  atocore.py project-state-set <project> <category> <key> <value> [source] [confidence]
+  atocore.py project-state-invalidate <project> <category> <key>
+  atocore.py query <prompt> [top_k] [project]
+  atocore.py context-build <prompt> [project] [budget]
+  atocore.py audit-query <prompt> [top_k] [project]
+  atocore.py ingest-sources
+"""
+
+
+def print_json(payload: Any) -> None:
+    print(json.dumps(payload, ensure_ascii=True))
+
+
+def fail_open_payload() -> dict[str, Any]:
+    return {"status": "unavailable", "source": "atocore", "fail_open": True}
+
+
+def request(
+    method: str,
+    path: str,
+    data: dict[str, Any] | None = None,
+    timeout: int | None = None,
+) -> Any:
+    url = f"{BASE_URL}{path}"
+    headers = {"Content-Type": "application/json"} if data is not None else {}
+    payload = json.dumps(data).encode("utf-8") if data is not None else None
+    req = urllib.request.Request(url, data=payload, headers=headers, method=method)
+    try:
+        with urllib.request.urlopen(req, timeout=timeout or TIMEOUT) as response:
+            body = response.read().decode("utf-8")
+    except urllib.error.HTTPError as exc:
+        body = exc.read().decode("utf-8")
+        if body:
+            print(body)
+        raise SystemExit(22) from exc
+    except (urllib.error.URLError, TimeoutError, OSError):
+        if FAIL_OPEN:
+            print_json(fail_open_payload())
+            raise SystemExit(0)
+        raise
+
+    if not body.strip():
+        return {}
+    return json.loads(body)
+
+
+def parse_aliases(aliases_csv: str) -> list[str]:
+    return [alias.strip() for alias in aliases_csv.split(",") if alias.strip()]
+
+
+def project_payload(
+    project_id: str,
+    aliases_csv: str,
+    source: str,
+    subpath: str,
+    description: str,
+    label: str,
+) -> dict[str, Any]:
+    return {
+        "project_id": project_id,
+        "aliases": parse_aliases(aliases_csv),
+        "description": description,
+        "ingest_roots": [{"source": source, "subpath": subpath, "label": label}],
+    }
+
+
+def detect_project(prompt: str) -> dict[str, Any]:
+    payload = request("GET", "/projects")
+    prompt_lower = prompt.lower()
+    best_project = None
+    best_alias = None
+    best_score = -1
+
+    for project in payload.get("projects", []):
+        candidates = [project.get("id", ""), *project.get("aliases", [])]
+        for candidate in candidates:
+            candidate = (candidate or "").strip()
+            if not candidate:
+                continue
+            pattern = rf"(?<![a-z0-9]){re.escape(candidate.lower())}(?![a-z0-9])"
+            matched = re.search(pattern, prompt_lower) is not None
+            if not matched and candidate.lower() not in prompt_lower:
+                continue
+            score = len(candidate)
+            if score > best_score:
+                best_project = project.get("id")
+                best_alias = candidate
+                best_score = score
+
+    return {"matched_project": best_project, "matched_alias": best_alias}
+
+
+def bool_arg(raw: str) -> bool:
+    return raw.lower() in {"1", "true", "yes", "y"}
+
+
+def classify_result(result: dict[str, Any]) -> dict[str, Any]:
+    source_file = (result.get("source_file") or "").lower()
+    heading = (result.get("heading_path") or "").lower()
+    title = (result.get("title") or "").lower()
+    text = " ".join([source_file, heading, title])
+
+    labels: list[str] = []
+    if any(token in text for token in ["_archive", "/archive", "archive/", "pre-cleanup", "pre-migration", "history"]):
+        labels.append("archive_or_history")
+    if any(token in text for token in ["status", "dashboard", "current-state", "current state", "next-steps", "next steps"]):
+        labels.append("current_status")
+    if any(token in text for token in ["decision", "adr", "tradeoff", "selected architecture", "selection"]):
+        labels.append("decision")
+    if any(token in text for token in ["requirement", "spec", "constraints", "baseline", "cdr", "sow"]):
+        labels.append("requirements")
+    if any(token in text for token in ["roadmap", "milestone", "plan", "workflow", "calibration", "contract"]):
+        labels.append("execution_plan")
+    if not labels:
+        labels.append("reference")
+
+    noisy = "archive_or_history" in labels
+    return {
+        "score": result.get("score"),
+        "title": result.get("title"),
+        "heading_path": result.get("heading_path"),
+        "source_file": result.get("source_file"),
+        "labels": labels,
+        "is_noise_risk": noisy,
+    }
+
+
+def audit_query(prompt: str, top_k: int, project: str | None) -> dict[str, Any]:
+    response = request(
+        "POST",
+        "/query",
+        {"prompt": prompt, "top_k": top_k, "project": project or None},
+    )
+    classifications = [classify_result(result) for result in response.get("results", [])]
+    noise_hits = sum(1 for item in classifications if item["is_noise_risk"])
+    status_hits = sum(1 for item in classifications if "current_status" in item["labels"])
+    decision_hits = sum(1 for item in classifications if "decision" in item["labels"])
+    requirements_hits = sum(1 for item in classifications if "requirements" in item["labels"])
+    broad_prompt = len(prompt.split()) <= 2
+
+    recommendations: list[str] = []
+    if broad_prompt:
+        recommendations.append("Prompt is broad; prefer a project-specific question with intent, artifact type, or constraint language.")
+    if noise_hits:
+        recommendations.append("Archive/history noise is present; prefer current-status, decision, requirements, and baseline docs in the next ingestion/ranking pass.")
+    if status_hits == 0:
+        recommendations.append("No current-status docs surfaced in the top results; Wave 2 should ingest or strengthen trusted operational truth.")
+    if decision_hits == 0:
+        recommendations.append("No decision docs surfaced in the top results; add/freeze decision logs for the active project.")
+    if requirements_hits == 0:
+        recommendations.append("No requirements/baseline docs surfaced in the top results; prioritize baseline and architecture freeze material.")
+    if not recommendations:
+        recommendations.append("Ranking looks healthy for this prompt.")
+
+    return {
+        "prompt": prompt,
+        "project": project,
+        "top_k": top_k,
+        "broad_prompt": broad_prompt,
+        "noise_hits": noise_hits,
+        "current_status_hits": status_hits,
+        "decision_hits": decision_hits,
+        "requirements_hits": requirements_hits,
+        "results": classifications,
+        "recommendations": recommendations,
+    }
+
+
+def main(argv: list[str]) -> int:
+    if len(argv) < 2:
+        print(USAGE, end="")
+        return 1
+
+    cmd = argv[1]
+    args = argv[2:]
+
+    if cmd == "health":
+        print_json(request("GET", "/health"))
+        return 0
+    if cmd == "sources":
+        print_json(request("GET", "/sources"))
+        return 0
+    if cmd == "stats":
+        print_json(request("GET", "/stats"))
+        return 0
+    if cmd == "projects":
+        print_json(request("GET", "/projects"))
+        return 0
+    if cmd == "project-template":
+        print_json(request("GET", "/projects/template"))
+        return 0
+    if cmd == "detect-project":
+        if not args:
+            print(USAGE, end="")
+            return 1
+        print_json(detect_project(args[0]))
+        return 0
+    if cmd == "auto-context":
+        if not args:
+            print(USAGE, end="")
+            return 1
+        prompt = args[0]
+        budget = int(args[1]) if len(args) > 1 else 3000
+        project = args[2] if len(args) > 2 else ""
+        if not project:
+            project = detect_project(prompt).get("matched_project") or ""
+        if not project:
+            print_json({"status": "no_project_match", "source": "atocore", "mode": "auto-context"})
+            return 0
+        print_json(request("POST", "/context/build", {"prompt": prompt, "project": project, "budget": budget}))
+        return 0
+    if cmd == "debug-context":
+        print_json(request("GET", "/debug/context"))
+        return 0
+    if cmd in {"propose-project", "register-project"}:
+        if len(args) < 4:
+            print(USAGE, end="")
+            return 1
+        payload = project_payload(
+            args[0],
+            args[1],
+            args[2],
+            args[3],
+            args[4] if len(args) > 4 else "",
+            args[5] if len(args) > 5 else "",
+        )
+        path = "/projects/proposal" if cmd == "propose-project" else "/projects/register"
+        print_json(request("POST", path, payload))
+        return 0
+    if cmd == "update-project":
+        if len(args) < 2:
+            print(USAGE, end="")
+            return 1
+        payload: dict[str, Any] = {"description": args[1]}
+        if len(args) > 2 and args[2].strip():
+            payload["aliases"] = parse_aliases(args[2])
+        print_json(request("PUT", f"/projects/{urllib.parse.quote(args[0])}", payload))
+        return 0
+    if cmd == "refresh-project":
+        if not args:
+            print(USAGE, end="")
+            return 1
+        purge_deleted = bool_arg(args[1]) if len(args) > 1 else False
+        path = f"/projects/{urllib.parse.quote(args[0])}/refresh?purge_deleted={str(purge_deleted).lower()}"
+        print_json(request("POST", path, {}, timeout=REFRESH_TIMEOUT))
+        return 0
+    if cmd == "project-state":
+        if not args:
+            print(USAGE, end="")
+            return 1
+        project = urllib.parse.quote(args[0])
+        suffix = f"?category={urllib.parse.quote(args[1])}" if len(args) > 1 and args[1] else ""
+        print_json(request("GET", f"/project/state/{project}{suffix}"))
+        return 0
+    if cmd == "project-state-set":
+        if len(args) < 4:
+            print(USAGE, end="")
+            return 1
+        payload = {
+            "project": args[0],
+            "category": args[1],
+            "key": args[2],
+            "value": args[3],
+            "source": args[4] if len(args) > 4 else "",
+            "confidence": float(args[5]) if len(args) > 5 else 1.0,
+        }
+        print_json(request("POST", "/project/state", payload))
+        return 0
+    if cmd == "project-state-invalidate":
+        if len(args) < 3:
+            print(USAGE, end="")
+            return 1
+        payload = {"project": args[0], "category": args[1], "key": args[2]}
+        print_json(request("DELETE", "/project/state", payload))
+        return 0
+    if cmd == "query":
+        if not args:
+            print(USAGE, end="")
+            return 1
+        prompt = args[0]
+        top_k = int(args[1]) if len(args) > 1 else 5
+        project = args[2] if len(args) > 2 else ""
+        print_json(request("POST", "/query", {"prompt": prompt, "top_k": top_k, "project": project or None}))
+        return 0
+    if cmd == "context-build":
+        if not args:
+            print(USAGE, end="")
+            return 1
+        prompt = args[0]
+        project = args[1] if len(args) > 1 else ""
+        budget = int(args[2]) if len(args) > 2 else 3000
+        print_json(request("POST", "/context/build", {"prompt": prompt, "project": project or None, "budget": budget}))
+        return 0
+    if cmd == "audit-query":
+        if not args:
+            print(USAGE, end="")
+            return 1
+        prompt = args[0]
+        top_k = int(args[1]) if len(args) > 1 else 5
+        project = args[2] if len(args) > 2 else ""
+        print_json(audit_query(prompt, top_k, project or None))
+        return 0
+    if cmd == "ingest-sources":
+        print_json(request("POST", "/ingest/sources", {}))
+        return 0
+
+    print(USAGE, end="")
+    return 1
+
+
+if __name__ == "__main__":
+    raise SystemExit(main(sys.argv))

t420-openclaw/atocore.sh

@@ -0,0 +1,15 @@
+#!/usr/bin/env bash
+set -euo pipefail
+
+SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
+
+if command -v python3 >/dev/null 2>&1; then
+  exec python3 "$SCRIPT_DIR/atocore.py" "$@"
+fi
+
+if command -v python >/dev/null 2>&1; then
+  exec python "$SCRIPT_DIR/atocore.py" "$@"
+fi
+
+echo "Python is required to run atocore.sh" >&2
+exit 1

tests/test_capture_stop.py

@@ -183,7 +183,7 @@ class TestCapture:
         assert body["prompt"] == "Please explain how the backup system works in detail"
         assert body["client"] == "claude-code"
         assert body["session_id"] == "test-session-123"
-        assert body["reinforce"] is False
+        assert body["reinforce"] is True
 
     @mock.patch("capture_stop.urllib.request.urlopen")
     def test_skips_when_disabled(self, mock_urlopen, tmp_path):

tests/test_context_builder.py

@@ -251,3 +251,98 @@ def test_unknown_hint_falls_back_to_raw_lookup(tmp_data_dir, sample_markdown, mo
 
     pack = build_context("status?", project_hint="orphan-project", budget=2000)
     assert "Solo run" in pack.formatted_context
+
+
+def test_project_memories_included_in_pack(tmp_data_dir, sample_markdown):
+    """Active project-scoped memories for the target project should
+    land in a dedicated '--- Project Memories ---' band so the
+    Phase 9 reflection loop has a retrieval outlet."""
+    from atocore.memory.service import create_memory
+
+    init_db()
+    init_project_state_schema()
+    ingest_file(sample_markdown)
+
+    mem = create_memory(
+        memory_type="project",
+        content="the mirror architecture is Option B conical back for p04-gigabit",
+        project="p04-gigabit",
+        confidence=0.9,
+    )
+    # A sibling memory for a different project must NOT leak into the pack.
+    create_memory(
+        memory_type="project",
+        content="polisher suite splits into sim, post, control, contracts",
+        project="p06-polisher",
+        confidence=0.9,
+    )
+
+    pack = build_context(
+        "remind me about the mirror architecture",
+        project_hint="p04-gigabit",
+        budget=3000,
+    )
+    assert "--- Project Memories ---" in pack.formatted_context
+    assert "Option B conical back" in pack.formatted_context
+    assert "polisher suite splits" not in pack.formatted_context
+    assert pack.project_memory_chars > 0
+    assert mem.project == "p04-gigabit"
+
+
+def test_project_memories_absent_without_project_hint(tmp_data_dir, sample_markdown):
+    """Without a project hint, project memories stay out of the pack —
+    cross-project bleed would rot the signal."""
+    from atocore.memory.service import create_memory
+
+    init_db()
+    init_project_state_schema()
+    ingest_file(sample_markdown)
+
+    create_memory(
+        memory_type="project",
+        content="scoped project knowledge that should not leak globally",
+        project="p04-gigabit",
+        confidence=0.9,
+    )
+
+    pack = build_context("tell me something", budget=3000)
+    assert "--- Project Memories ---" not in pack.formatted_context
+    assert pack.project_memory_chars == 0
+
+
+def test_project_memories_query_relevance_ordering(tmp_data_dir, sample_markdown):
+    """When the budget only fits one memory, query-relevance ordering
+    should pick the one the query is actually about — even if another
+    memory has higher confidence.
+
+    Regression for the 2026-04-11 p05-vendor-signal harness failure:
+    memory selection was fixed-order by confidence, so a lower-ranked
+    vendor memory got starved out of the budget when a query was
+    specifically about vendors.
+    """
+    from atocore.memory.service import create_memory
+
+    init_db()
+    init_project_state_schema()
+    ingest_file(sample_markdown)
+
+    create_memory(
+        memory_type="project",
+        content="the folded-beam interferometer uses a CGH stage and fold mirror",
+        project="p05-interferometer",
+        confidence=0.97,
+    )
+    create_memory(
+        memory_type="knowledge",
+        content="vendor signal: Zygo Verifire SV is the strongest value path for the interferometer",
+        project="p05-interferometer",
+        confidence=0.85,
+    )
+
+    pack = build_context(
+        "what is the current vendor signal for the interferometer",
+        project_hint="p05-interferometer",
+        budget=1200,  # tight enough that only one project memory fits
+    )
+    assert "Zygo Verifire SV" in pack.formatted_context
+    assert pack.project_memory_chars > 0

tests/test_reinforcement.py

@@ -476,6 +476,60 @@ def test_reinforce_matches_at_70_percent_threshold(tmp_data_dir):
     assert any(r.memory_id == mem.id for r in results)
 
 
+def test_reinforce_long_memory_matches_on_absolute_overlap(tmp_data_dir):
+    """A paragraph-length memory should reinforce when the response
+    echoes a substantive subset of its distinctive tokens, even though
+    the overlap fraction stays well under 70%."""
+    init_db()
+    mem = create_memory(
+        memory_type="project",
+        content=(
+            "Interferometer architecture: a folded-beam configuration with a "
+            "fixed horizontal interferometer, a forty-five degree fold mirror, "
+            "a six-DOF CGH stage, and the mirror on its own tilting platform. "
+            "The fold mirror redirects the beam while the CGH shapes the wavefront."
+        ),
+        project="p05-interferometer",
+        confidence=0.5,
+    )
+    interaction = _make_interaction(
+        project="p05-interferometer",
+        response=(
+            "For the interferometer we keep the folded-beam layout: horizontal "
+            "interferometer, fold mirror at forty-five degrees, CGH stage with "
+            "six DOF, and the mirror sitting on its tilting platform. The fold "
+            "mirror redirects the beam and the CGH shapes the wavefront."
+        ),
+    )
+    results = reinforce_from_interaction(interaction)
+    assert any(r.memory_id == mem.id for r in results)
+
+
+def test_reinforce_long_memory_rejects_thin_overlap(tmp_data_dir):
+    """Long memory + a response that only brushes a few generic terms
+    must NOT reinforce — otherwise the reflection loop rots."""
+    init_db()
+    mem = create_memory(
+        memory_type="project",
+        content=(
+            "Polisher control system executes approved controller jobs, "
+            "enforces state transitions and interlocks, supports pause "
+            "resume and abort, and records auditable run logs while "
+            "never reinterpreting metrology or inventing new strategies."
+        ),
+        project="p06-polisher",
+        confidence=0.5,
+    )
+    interaction = _make_interaction(
+        project="p06-polisher",
+        response=(
+            "I updated the polisher docs and fixed a typo in the run logs section."
+        ),
+    )
+    results = reinforce_from_interaction(interaction)
+    assert all(r.memory_id != mem.id for r in results)
+
+
 def test_reinforce_rejects_below_70_percent(tmp_data_dir):
     """Only 6 of 10 content tokens present (60%) → should NOT match."""
     init_db()