Anticorrelator Lore Memory

/memory Skill

Manages the per-project knowledge store. Most subcommands are script calls — run and show the output.

Route $ARGUMENTS

Match the first word of $ARGUMENTS to a command below. If empty, show the index.

Resolve knowledge path first:

KDIR=$(lore resolve)

add <category> <title>

Quick-add directly to a category directory (bypasses inbox):

1. Write entry as $KDIR/<category>/<slug>.md with # Title, body, and <!-- learned: ... | confidence: high | source: manual --> metadata
2. If category directory doesn't exist, create it
3. Run lore heal

search <query>

lore search "<query>" --type knowledge

Show the script output. For top matches, briefly summarize relevant context.

view [category] [query]

• No argument: run lore index and display the dynamic category/entry listing
• With category: lore read <category> (resolves knowledge, domains/, and _threads/ files)
• With category + query: lore read <category> --query "<query>" (matching sections full, non-matching as heading-only)
• view inbox: read .md files from $KDIR/_inbox/
• For threads: lore read <slug> --type thread or lore read <slug> --type thread --query "<query>"

curate

Periodic refinement of the knowledge store (optional, not required).

Start with the mechanical pre-scan:

lore curate

This lists inbox remnants, medium-confidence entries, and entries missing backlinks. Then apply judgment:

1. Refile inbox remnants: If $KDIR/_inbox/ has .md files (from interrupted captures), review each and either file to the correct category or drop.
2. Quality gate for medium-confidence entries: Scan entry files for confidence: medium in their HTML comment metadata (typically from agent captures). Re-evaluate each against the 4-condition gate:
   • Reusable beyond the original task?
   • Non-obvious — not already covered by another entry or docs?
   • Stable — still accurate?
   • High confidence — can you verify it now? Drop entries that fail the gate. Upgrade passing entries to confidence: high.
3. Deduplicate: Merge entries that describe the same insight from different contexts.
4. Backlinks: Add missing [[backlinks]] cross-references between related entries.
5. Title quality: Improve vague or generic titles to be specific and scannable.
6. Stale entries: Flag or remove entries that contradict current code.
7. Confidence calibration: If $KDIR/_capture_log.csv exists, count entries with source=stop-hook. Compare against the number of stop-hook medium-confidence entries that passed the quality gate (upgraded) vs failed (dropped). Report the pass rate:
   • >70% pass rate: "Stop hook evaluator is well-calibrated"
   • 40-70% pass rate: "Stop hook evaluator calibration is acceptable"
   • <40% pass rate: "Stop hook evaluator needs tightening — consider refining triggers in scripts/stop-capture-prompt.txt"
8. Report what was found and fixed:

   [curate] Done.
     Dropped: N entries (reasons)
     Merged: N duplicates
     Upgraded: N to high confidence
     Backlinks added: N
     Stop hook calibration: X/Y passed (Z%) — <assessment>
   

9. Run lore heal

Drop authority: Curate has explicit authority to remove entries without user confirmation when they fail the 4-condition gate. Report what was dropped in the summary so the user can object.

renormalize

Redirect to /renormalize skill. Invoke /renormalize instead.

heal

lore heal

Show the script output. To apply fixes: lore heal --fix

init [--force]

1. Check if inside a git repo: git rev-parse --is-inside-work-tree
2. If yes: lore init
3. If no: inform user, ask for confirmation, then lore init --force
4. Report the created path

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