feat: Phase 5F/5G/5H — graduation, conflicts, MCP engineering tools

The population move + the safety net + the universal consumer hookup,
all shipped together. This is where the engineering graph becomes
genuinely useful against the real 262-memory corpus.

5F: Memory → Entity graduation (THE population move)
- src/atocore/engineering/_graduation_prompt.py: stdlib-only shared
  prompt module mirroring _llm_prompt.py pattern (container + host
  use same system prompt, no drift)
- scripts/graduate_memories.py: host-side batch driver that asks
  claude-p "does this memory describe a typed entity?" and creates
  entity candidates with source_refs pointing back to the memory
- promote_entity() now scans source_refs for memory:* prefix; if
  found, flips source memory to status='graduated' with
  graduated_to_entity_id forward pointer + writes memory_audit row
- GET /admin/graduation/stats exposes graduation rate for dashboard

5G: Sync conflict detection on entity promote
- src/atocore/engineering/conflicts.py: detect_conflicts_for_entity()
  runs on every active promote. V1 checks 3 slot kinds narrowly to
  avoid false positives:
  * component.material (multiple USES_MATERIAL edges)
  * component.part_of (multiple PART_OF edges)
  * requirement.name (duplicate active Requirements in same project)
- Conflicts + members persist via the tables built in 5A
- Fires a "warning" alert via Phase 4 framework
- Deduplicates: same (slot_kind, slot_key) won't get a new row
- resolve_conflict(action="dismiss|supersede_others|no_action"):
  supersede_others marks non-winner members as status='superseded'
- GET /admin/conflicts + POST /admin/conflicts/{id}/resolve

5H: MCP + context pack integration
- scripts/atocore_mcp.py: 7 new engineering tools exposed to every
  MCP-aware client (Claude Desktop, Claude Code, Cursor, Zed):
  * atocore_engineering_map (Q-001/004 system tree)
  * atocore_engineering_gaps (Q-006/009/011 killer queries — THE
    director's question surfaced as a built-in tool)
  * atocore_engineering_requirements_for_component (Q-005)
  * atocore_engineering_decisions (Q-008)
  * atocore_engineering_changes (Q-013 — reads entity audit log)
  * atocore_engineering_impact (Q-016 BFS downstream)
  * atocore_engineering_evidence (Q-017 inbound provenance)
- MCP tools total: 14 (7 memory/state/health + 7 engineering)
- context/builder.py _build_engineering_context now appends a compact
  gaps summary ("Gaps: N orphan reqs, M risky decisions, K unsupported
  claims") so every project-scoped LLM call sees "what we're missing"

Tests: 341 → 356 (15 new):
- 5F: graduation prompt parses positive/negative decisions, rejects
  unknown entity types, tolerates markdown fences; promote_entity
  marks source memory graduated with forward pointer; entity without
  memory refs promotes cleanly
- 5G: component.material + component.part_of + requirement.name
  conflicts detected; clean component triggers nothing; dedup works;
  supersede_others resolution marks losers; dismiss leaves both
  active; end-to-end promote triggers detection
- 5H: graduation user message includes project + type + content

No regressions across the 341 prior tests. The MCP server now answers
"which p05 requirements aren't satisfied?" directly from any Claude
session — no user prompt engineering, no context hacks.

Next to kick off from user: run graduation script on Dalidou to
populate the graph from 262 existing memories:
  ssh papa@dalidou 'cd /srv/storage/atocore/app && PYTHONPATH=src \
    python3 scripts/graduate_memories.py --project p05-interferometer --limit 30 --dry-run'

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
This commit is contained in:
2026-04-17 07:53:03 -04:00
parent 53b71639ad
commit 3316ff99f9
8 changed files with 1425 additions and 7 deletions

View File

@@ -243,6 +243,197 @@ def _tool_health(args: dict) -> str:
return f"AtoCore healthy: sha={sha} vectors={vectors} env={env}"
# --- Phase 5H: Engineering query tools ---
def _tool_system_map(args: dict) -> str:
"""Q-001 + Q-004: subsystem/component tree for a project."""
project = (args.get("project") or "").strip()
if not project:
return "Error: 'project' is required."
result, err = safe_call(
http_get, f"/engineering/projects/{urllib.parse.quote(project)}/systems"
)
if err:
return f"Engineering query failed: {err}"
subs = result.get("subsystems", []) or []
orphans = result.get("orphan_components", []) or []
if not subs and not orphans:
return f"No subsystems or components registered for {project}."
lines = [f"System map for {project}:"]
for s in subs:
lines.append(f"\n[{s['name']}] — {s.get('description') or '(no description)'}")
for c in s.get("components", []):
mats = ", ".join(c.get("materials", [])) or "-"
lines.append(f"{c['name']} (materials: {mats})")
if orphans:
lines.append(f"\nOrphan components (not attached to any subsystem):")
for c in orphans:
lines.append(f"{c['name']}")
return "\n".join(lines)
def _tool_gaps(args: dict) -> str:
"""Q-006 + Q-009 + Q-011: find coverage gaps. Director's most-used query."""
project = (args.get("project") or "").strip()
if not project:
return "Error: 'project' is required."
result, err = safe_call(
http_get, f"/engineering/gaps",
params={"project": project},
)
if err:
return f"Gap query failed: {err}"
orphan = result.get("orphan_requirements", {})
risky = result.get("risky_decisions", {})
unsup = result.get("unsupported_claims", {})
counts = f"{orphan.get('count',0)}/{risky.get('count',0)}/{unsup.get('count',0)}"
lines = [f"Coverage gaps for {project} (orphan reqs / risky decisions / unsupported claims: {counts}):\n"]
if orphan.get("count", 0):
lines.append(f"ORPHAN REQUIREMENTS ({orphan['count']}) — no component claims to satisfy:")
for g in orphan.get("gaps", [])[:10]:
lines.append(f"{g['name']}: {(g.get('description') or '')[:120]}")
lines.append("")
if risky.get("count", 0):
lines.append(f"RISKY DECISIONS ({risky['count']}) — based on flagged assumptions:")
for g in risky.get("gaps", [])[:10]:
lines.append(f"{g['decision_name']} (assumption: {g['assumption_name']}{g['assumption_status']})")
lines.append("")
if unsup.get("count", 0):
lines.append(f"UNSUPPORTED CLAIMS ({unsup['count']}) — no Result entity backs them:")
for g in unsup.get("gaps", [])[:10]:
lines.append(f"{g['name']}: {(g.get('description') or '')[:120]}")
if orphan.get("count", 0) == 0 and risky.get("count", 0) == 0 and unsup.get("count", 0) == 0:
lines.append("✓ No gaps detected — every requirement satisfied, no flagged assumptions, all claims have evidence.")
return "\n".join(lines)
def _tool_requirements_for(args: dict) -> str:
"""Q-005: requirements that a component satisfies."""
component_id = (args.get("component_id") or "").strip()
if not component_id:
return "Error: 'component_id' is required."
result, err = safe_call(
http_get, f"/engineering/components/{urllib.parse.quote(component_id)}/requirements"
)
if err:
return f"Query failed: {err}"
reqs = result.get("requirements", []) or []
if not reqs:
return "No requirements associated with this component."
lines = [f"Component satisfies {len(reqs)} requirement(s):"]
for r in reqs:
lines.append(f"{r['name']}: {(r.get('description') or '')[:150]}")
return "\n".join(lines)
def _tool_decisions_affecting(args: dict) -> str:
"""Q-008: decisions affecting a project or subsystem."""
project = (args.get("project") or "").strip()
subsystem = args.get("subsystem_id") or args.get("subsystem") or ""
if not project:
return "Error: 'project' is required."
params = {"project": project}
if subsystem:
params["subsystem"] = subsystem
result, err = safe_call(http_get, "/engineering/decisions", params=params)
if err:
return f"Query failed: {err}"
decisions = result.get("decisions", []) or []
if not decisions:
scope = f"subsystem {subsystem}" if subsystem else f"project {project}"
return f"No decisions recorded for {scope}."
scope = f"subsystem {subsystem}" if subsystem else project
lines = [f"{len(decisions)} decision(s) affecting {scope}:"]
for d in decisions:
lines.append(f"{d['name']}: {(d.get('description') or '')[:150]}")
return "\n".join(lines)
def _tool_recent_changes(args: dict) -> str:
"""Q-013: what changed recently in the engineering graph."""
project = (args.get("project") or "").strip()
since = args.get("since") or ""
limit = int(args.get("limit") or 20)
if not project:
return "Error: 'project' is required."
params = {"project": project, "limit": limit}
if since:
params["since"] = since
result, err = safe_call(http_get, "/engineering/changes", params=params)
if err:
return f"Query failed: {err}"
changes = result.get("changes", []) or []
if not changes:
return f"No entity changes in {project} since {since or '(all time)'}."
lines = [f"Recent changes in {project} ({len(changes)}):"]
for c in changes:
lines.append(
f" [{c['timestamp'][:16]}] {c['action']:10s} "
f"[{c.get('entity_type','?')}] {c.get('entity_name','?')} "
f"by {c.get('actor','?')}"
)
return "\n".join(lines)
def _tool_impact(args: dict) -> str:
"""Q-016: impact of changing an entity (downstream BFS)."""
entity = (args.get("entity_id") or args.get("entity") or "").strip()
if not entity:
return "Error: 'entity_id' is required."
max_depth = int(args.get("max_depth") or 3)
result, err = safe_call(
http_get, "/engineering/impact",
params={"entity": entity, "max_depth": max_depth},
)
if err:
return f"Query failed: {err}"
root = result.get("root") or {}
impacted = result.get("impacted", []) or []
if not impacted:
return f"Nothing downstream of [{root.get('entity_type','?')}] {root.get('name','?')}."
lines = [
f"Changing [{root.get('entity_type')}] {root.get('name')} "
f"would affect {len(impacted)} entity(ies) (max depth {max_depth}):"
]
for i in impacted[:25]:
indent = " " * i.get("depth", 1)
lines.append(f"{indent}→ [{i['entity_type']}] {i['name']} (via {i['relationship']})")
if len(impacted) > 25:
lines.append(f" ... and {len(impacted)-25} more")
return "\n".join(lines)
def _tool_evidence(args: dict) -> str:
"""Q-017: evidence chain for an entity."""
entity = (args.get("entity_id") or args.get("entity") or "").strip()
if not entity:
return "Error: 'entity_id' is required."
result, err = safe_call(http_get, "/engineering/evidence", params={"entity": entity})
if err:
return f"Query failed: {err}"
root = result.get("root") or {}
chain = result.get("evidence_chain", []) or []
lines = [f"Evidence for [{root.get('entity_type','?')}] {root.get('name','?')}:"]
if not chain:
lines.append(" (no inbound provenance edges)")
else:
for e in chain:
lines.append(
f" {e['via']} ← [{e['source_type']}] {e['source_name']}: "
f"{(e.get('source_description') or '')[:100]}"
)
refs = result.get("direct_source_refs") or []
if refs:
lines.append(f"\nDirect source_refs: {refs[:5]}")
return "\n".join(lines)
TOOLS = [
{
"name": "atocore_context",
@@ -358,6 +549,121 @@ TOOLS = [
"inputSchema": {"type": "object", "properties": {}},
"handler": _tool_health,
},
# --- Phase 5H: Engineering knowledge graph tools ---
{
"name": "atocore_engineering_map",
"description": (
"Get the subsystem/component tree for an engineering project. "
"Returns the full system architecture: subsystems, their components, "
"materials, and any orphan components not attached to a subsystem. "
"Use when the user asks about project structure or system design."
),
"inputSchema": {
"type": "object",
"properties": {
"project": {"type": "string", "description": "Project id (e.g. p04-gigabit)"},
},
"required": ["project"],
},
"handler": _tool_system_map,
},
{
"name": "atocore_engineering_gaps",
"description": (
"Find coverage gaps in a project's engineering graph: orphan "
"requirements (no component satisfies them), risky decisions "
"(based on flagged assumptions), and unsupported claims (no "
"Result evidence). This is the director's most useful query — "
"answers 'what am I forgetting?' in seconds."
),
"inputSchema": {
"type": "object",
"properties": {
"project": {"type": "string"},
},
"required": ["project"],
},
"handler": _tool_gaps,
},
{
"name": "atocore_engineering_requirements_for_component",
"description": "List the requirements a specific component claims to satisfy (Q-005).",
"inputSchema": {
"type": "object",
"properties": {
"component_id": {"type": "string"},
},
"required": ["component_id"],
},
"handler": _tool_requirements_for,
},
{
"name": "atocore_engineering_decisions",
"description": (
"Decisions that affect a project, optionally scoped to a specific "
"subsystem. Use when the user asks 'what did we decide about X?'"
),
"inputSchema": {
"type": "object",
"properties": {
"project": {"type": "string"},
"subsystem_id": {"type": "string", "description": "optional subsystem entity id"},
},
"required": ["project"],
},
"handler": _tool_decisions_affecting,
},
{
"name": "atocore_engineering_changes",
"description": (
"Recent changes to the engineering graph for a project: which "
"entities were created/promoted/rejected/updated, by whom, when. "
"Use for 'what changed recently?' type questions."
),
"inputSchema": {
"type": "object",
"properties": {
"project": {"type": "string"},
"since": {"type": "string", "description": "ISO timestamp; optional"},
"limit": {"type": "integer", "minimum": 1, "maximum": 200, "default": 20},
},
"required": ["project"],
},
"handler": _tool_recent_changes,
},
{
"name": "atocore_engineering_impact",
"description": (
"Impact analysis: what's downstream of a given entity. BFS over "
"outbound relationships up to max_depth. Use to answer 'what would "
"break if I change X?'"
),
"inputSchema": {
"type": "object",
"properties": {
"entity_id": {"type": "string"},
"max_depth": {"type": "integer", "minimum": 1, "maximum": 5, "default": 3},
},
"required": ["entity_id"],
},
"handler": _tool_impact,
},
{
"name": "atocore_engineering_evidence",
"description": (
"Evidence chain for an entity: what supports it? Walks inbound "
"SUPPORTS / EVIDENCED_BY / DESCRIBED_BY / VALIDATED_BY / ANALYZED_BY "
"edges. Use for 'how do we know X is true?' type questions."
),
"inputSchema": {
"type": "object",
"properties": {
"entity_id": {"type": "string"},
},
"required": ["entity_id"],
},
"handler": _tool_evidence,
},
]

View File

@@ -0,0 +1,237 @@
#!/usr/bin/env python3
"""Phase 5F — Memory → Entity graduation batch pass.
Takes active memories, asks claude-p whether each describes a typed
engineering entity, and creates entity candidates for the ones that do.
Each candidate carries source_refs back to its source memory so human
review can trace provenance.
Human reviews the entity candidates via /admin/triage (same UI as memory
triage). When a candidate is promoted, a post-promote hook marks the source
memory as `graduated` and sets `graduated_to_entity_id` for traceability.
This is THE population move: without it, the engineering graph stays sparse
and the killer queries (Q-006/009/011) have nothing to find gaps in.
Usage:
python3 scripts/graduate_memories.py --base-url http://127.0.0.1:8100 \\
--project p05-interferometer --limit 20
# Dry run (don't create entities, just show decisions):
python3 scripts/graduate_memories.py --project p05-interferometer --dry-run
# Process all active memories across all projects (big run):
python3 scripts/graduate_memories.py --limit 200
Host-side because claude CLI lives on Dalidou, not in the container.
"""
from __future__ import annotations
import argparse
import json
import os
import shutil
import subprocess
import sys
import tempfile
import time
import urllib.error
import urllib.request
from typing import Any
# Make src/ importable so we can reuse the stdlib-only prompt module
_SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__))
_SRC_DIR = os.path.abspath(os.path.join(_SCRIPT_DIR, "..", "src"))
if _SRC_DIR not in sys.path:
sys.path.insert(0, _SRC_DIR)
from atocore.engineering._graduation_prompt import ( # noqa: E402
GRADUATION_PROMPT_VERSION,
SYSTEM_PROMPT,
build_user_message,
parse_graduation_output,
)
DEFAULT_BASE_URL = os.environ.get("ATOCORE_BASE_URL", "http://127.0.0.1:8100")
DEFAULT_MODEL = os.environ.get("ATOCORE_LLM_EXTRACTOR_MODEL", "sonnet")
DEFAULT_TIMEOUT_S = float(os.environ.get("ATOCORE_GRADUATION_TIMEOUT_S", "90"))
_sandbox_cwd = None
def get_sandbox_cwd() -> str:
"""Temp cwd so claude CLI doesn't auto-discover project CLAUDE.md files."""
global _sandbox_cwd
if _sandbox_cwd is None:
_sandbox_cwd = tempfile.mkdtemp(prefix="ato-graduate-")
return _sandbox_cwd
def api_get(base_url: str, path: str) -> dict:
req = urllib.request.Request(f"{base_url}{path}")
with urllib.request.urlopen(req, timeout=15) as resp:
return json.loads(resp.read().decode("utf-8"))
def api_post(base_url: str, path: str, body: dict | None = None) -> dict:
data = json.dumps(body or {}).encode("utf-8")
req = urllib.request.Request(
f"{base_url}{path}", method="POST",
headers={"Content-Type": "application/json"}, data=data,
)
with urllib.request.urlopen(req, timeout=15) as resp:
return json.loads(resp.read().decode("utf-8"))
def graduate_one(memory: dict, model: str, timeout_s: float) -> dict[str, Any] | None:
"""Ask claude whether this memory describes a typed entity.
Returns None on any failure (parse error, timeout, exit!=0).
Applies retry+pacing to match the pattern in auto_triage/batch_extract.
"""
if not shutil.which("claude"):
return None
user_msg = build_user_message(
memory_content=memory.get("content", "") or "",
memory_project=memory.get("project", "") or "",
memory_type=memory.get("memory_type", "") or "",
)
args = [
"claude", "-p",
"--model", model,
"--append-system-prompt", SYSTEM_PROMPT,
"--disable-slash-commands",
user_msg,
]
last_error = ""
for attempt in range(3):
if attempt > 0:
time.sleep(2 ** attempt)
try:
completed = subprocess.run(
args, capture_output=True, text=True,
timeout=timeout_s, cwd=get_sandbox_cwd(),
encoding="utf-8", errors="replace",
)
except subprocess.TimeoutExpired:
last_error = "timeout"
continue
except Exception as exc:
last_error = f"subprocess error: {exc}"
continue
if completed.returncode == 0:
return parse_graduation_output(completed.stdout or "")
stderr = (completed.stderr or "").strip()[:200]
last_error = f"exit_{completed.returncode}: {stderr}" if stderr else f"exit_{completed.returncode}"
print(f" ! claude failed after 3 tries: {last_error}", file=sys.stderr)
return None
def create_entity_candidate(
base_url: str,
decision: dict,
memory: dict,
) -> str | None:
"""Create an entity candidate with source_refs pointing at the memory."""
try:
result = api_post(base_url, "/entities", {
"entity_type": decision["entity_type"],
"name": decision["name"],
"project": memory.get("project", "") or "",
"description": decision["description"],
"properties": {
"graduated_from_memory": memory["id"],
"proposed_relationships": decision["relationships"],
"prompt_version": GRADUATION_PROMPT_VERSION,
},
"status": "candidate",
"confidence": decision["confidence"],
"source_refs": [f"memory:{memory['id']}"],
})
return result.get("id")
except Exception as e:
print(f" ! entity create failed: {e}", file=sys.stderr)
return None
def main() -> None:
parser = argparse.ArgumentParser(description="Graduate active memories into entity candidates")
parser.add_argument("--base-url", default=DEFAULT_BASE_URL)
parser.add_argument("--model", default=DEFAULT_MODEL)
parser.add_argument("--project", default=None, help="Only graduate memories in this project")
parser.add_argument("--limit", type=int, default=50, help="Max memories to process")
parser.add_argument("--min-confidence", type=float, default=0.3,
help="Skip memories with confidence below this (they're probably noise)")
parser.add_argument("--dry-run", action="store_true", help="Show decisions without creating entities")
args = parser.parse_args()
# Fetch active memories
query = "status=active"
query += f"&limit={args.limit}"
if args.project:
query += f"&project={args.project}"
result = api_get(args.base_url, f"/memory?{query}")
memories = result.get("memories", [])
# Filter by min_confidence + skip already-graduated
memories = [m for m in memories
if m.get("confidence", 0) >= args.min_confidence
and m.get("status") != "graduated"]
print(f"graduating: {len(memories)} memories project={args.project or '(all)'} "
f"model={args.model} dry_run={args.dry_run}")
graduated = 0
skipped = 0
errors = 0
entities_created: list[str] = []
for i, mem in enumerate(memories, 1):
if i > 1:
time.sleep(0.5) # light pacing, matches auto_triage
mid = mem["id"]
label = f"[{i:3d}/{len(memories)}] {mid[:8]} [{mem.get('memory_type','?')}]"
decision = graduate_one(mem, args.model, DEFAULT_TIMEOUT_S)
if decision is None:
print(f" ERROR {label} (graduate_one returned None)")
errors += 1
continue
if not decision.get("graduate"):
reason = decision.get("reason", "(no reason)")
print(f" skip {label} {reason}")
skipped += 1
continue
etype = decision["entity_type"]
ename = decision["name"]
nrel = len(decision.get("relationships", []))
if args.dry_run:
print(f" WOULD {label} → [{etype}] {ename!r} ({nrel} rels)")
graduated += 1
else:
entity_id = create_entity_candidate(args.base_url, decision, mem)
if entity_id:
print(f" CREATE {label} → [{etype}] {ename!r} ({nrel} rels) entity={entity_id[:8]}")
graduated += 1
entities_created.append(entity_id)
else:
errors += 1
print(f"\ntotal: graduated={graduated} skipped={skipped} errors={errors}")
if entities_created:
print(f"Review at /admin/triage ({len(entities_created)} entity candidates created)")
if __name__ == "__main__":
main()