feat: Karpathy-inspired upgrades — contradiction, lint, synthesis
Three additive upgrades borrowed from Karpathy's LLM Wiki pattern: 1. CONTRADICTION DETECTION: auto-triage now has a fourth verdict — "contradicts". When a candidate conflicts with an existing memory (not duplicates, genuine disagreement like "Option A selected" vs "Option B selected"), the triage model flags it and leaves it in the queue for human review instead of silently rejecting or double-storing. Preserves source tension rather than suppressing it. 2. WEEKLY LINT PASS: scripts/lint_knowledge_base.py checks for: - Orphan memories (active but zero references after 14 days) - Stale candidates (>7 days unreviewed) - Unused entities (no relationships) - Empty-state projects - Unregistered projects auto-detected in memories Runs Sundays via the cron. Outputs a report. 3. WEEKLY SYNTHESIS: scripts/synthesize_projects.py uses sonnet to generate a 3-5 sentence "current state" paragraph per project from state + memories + entities. Cached in project_state under status/synthesis_cache. Wiki project pages now show this at the top under "Current State (auto-synthesis)". Falls back to a deterministic summary if no cache exists. deploy/dalidou/batch-extract.sh: added Step C (synthesis) and Step D (lint) gated to Sundays via date check. All additive — nothing existing changes behavior. The database remains the source of truth; these operations just produce better synthesized views and catch rot. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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scripts/lint_knowledge_base.py
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170
scripts/lint_knowledge_base.py
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"""Weekly lint pass — health check for the AtoCore knowledge base.
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Inspired by Karpathy's LLM Wiki pattern (the 'lint' operation).
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Checks for orphans, stale claims, contradictions, and gaps.
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Outputs a report that can be posted to the wiki as needs_review.
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Usage:
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python3 scripts/lint_knowledge_base.py --base-url http://dalidou:8100
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Run weekly via cron, or on-demand when the knowledge base feels stale.
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"""
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from __future__ import annotations
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import argparse
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import json
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import os
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import urllib.request
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from datetime import datetime, timezone, timedelta
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DEFAULT_BASE_URL = os.environ.get("ATOCORE_BASE_URL", "http://localhost:8100")
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ORPHAN_AGE_DAYS = 14
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def api_get(base_url: str, path: str):
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with urllib.request.urlopen(f"{base_url}{path}", timeout=15) as r:
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return json.loads(r.read())
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def parse_ts(ts: str) -> datetime | None:
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if not ts:
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return None
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try:
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return datetime.strptime(ts[:19], "%Y-%m-%d %H:%M:%S").replace(tzinfo=timezone.utc)
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except Exception:
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return None
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def main():
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parser = argparse.ArgumentParser()
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parser.add_argument("--base-url", default=DEFAULT_BASE_URL)
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args = parser.parse_args()
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b = args.base_url
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now = datetime.now(timezone.utc)
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orphan_threshold = now - timedelta(days=ORPHAN_AGE_DAYS)
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print(f"=== AtoCore Lint — {now.strftime('%Y-%m-%d %H:%M UTC')} ===\n")
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findings = {
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"orphan_memories": [],
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"stale_candidates": [],
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"unused_entities": [],
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"empty_state_projects": [],
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"unregistered_projects": [],
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}
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# 1. Orphan memories: active but never reinforced after N days
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memories = api_get(b, "/memory?active_only=true&limit=500").get("memories", [])
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for m in memories:
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updated = parse_ts(m.get("updated_at", ""))
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if m.get("reference_count", 0) == 0 and updated and updated < orphan_threshold:
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findings["orphan_memories"].append({
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"id": m["id"],
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"type": m["memory_type"],
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"project": m.get("project") or "(none)",
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"age_days": (now - updated).days,
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"content": m["content"][:120],
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})
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# 2. Stale candidates: been in queue > 7 days without triage
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candidates = api_get(b, "/memory?status=candidate&limit=500").get("memories", [])
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stale_threshold = now - timedelta(days=7)
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for c in candidates:
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updated = parse_ts(c.get("updated_at", ""))
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if updated and updated < stale_threshold:
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findings["stale_candidates"].append({
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"id": c["id"],
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"age_days": (now - updated).days,
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"content": c["content"][:120],
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})
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# 3. Unused entities: no relationships in either direction
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entities = api_get(b, "/entities?limit=500").get("entities", [])
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for e in entities:
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try:
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detail = api_get(b, f"/entities/{e['id']}")
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if not detail.get("relationships"):
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findings["unused_entities"].append({
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"id": e["id"],
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"type": e["entity_type"],
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"name": e["name"],
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"project": e.get("project") or "(none)",
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})
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except Exception:
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pass
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# 4. Registered projects with no state entries
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try:
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projects = api_get(b, "/projects").get("projects", [])
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for p in projects:
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state = api_get(b, f"/project/state/{p['id']}").get("entries", [])
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if not state:
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findings["empty_state_projects"].append(p["id"])
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except Exception:
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pass
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# 5. Memories tagged to unregistered projects (auto-detection candidates)
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registered_ids = {p["id"] for p in projects} | {
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a for p in projects for a in p.get("aliases", [])
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}
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all_mems = api_get(b, "/memory?limit=500").get("memories", [])
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for m in all_mems:
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proj = m.get("project", "")
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if proj and proj not in registered_ids and proj != "(none)":
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if proj not in findings["unregistered_projects"]:
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findings["unregistered_projects"].append(proj)
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# Print report
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print(f"## Orphan memories (active, no reinforcement, >{ORPHAN_AGE_DAYS} days old)")
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if findings["orphan_memories"]:
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print(f" Found: {len(findings['orphan_memories'])}")
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for o in findings["orphan_memories"][:10]:
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print(f" - [{o['type']}] {o['project']} ({o['age_days']}d): {o['content']}")
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else:
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print(" (none)")
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print(f"\n## Stale candidates (>7 days in queue)")
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if findings["stale_candidates"]:
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print(f" Found: {len(findings['stale_candidates'])}")
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for s in findings["stale_candidates"][:10]:
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print(f" - ({s['age_days']}d): {s['content']}")
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else:
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print(" (none)")
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print(f"\n## Unused entities (no relationships)")
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if findings["unused_entities"]:
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print(f" Found: {len(findings['unused_entities'])}")
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for u in findings["unused_entities"][:10]:
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print(f" - [{u['type']}] {u['project']}: {u['name']}")
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else:
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print(" (none)")
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print(f"\n## Empty-state projects")
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if findings["empty_state_projects"]:
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print(f" Found: {len(findings['empty_state_projects'])}")
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for p in findings["empty_state_projects"]:
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print(f" - {p}")
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else:
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print(" (none)")
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print(f"\n## Unregistered projects detected in memories")
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if findings["unregistered_projects"]:
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print(f" Found: {len(findings['unregistered_projects'])}")
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print(" These were auto-detected by extraction — consider registering them:")
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for p in findings["unregistered_projects"]:
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print(f" - {p}")
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else:
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print(" (none)")
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total_findings = sum(
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len(v) if isinstance(v, list) else 0 for v in findings.values()
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)
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print(f"\n=== Total findings: {total_findings} ===")
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# Return exit code based on findings count (for CI)
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return 0 if total_findings == 0 else 1
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if __name__ == "__main__":
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raise SystemExit(main())
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