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Record a lesson learned after fixing a bug or discovering a pattern. Updates domain memory files and checks for contradictions. Use after resolving non-trivial issues.
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Basado en la clasificación ocupacional SOC
Run OCR and translation quality evaluations across scripts and languages. Produces research-grade reports with MCR, cross-model agreement, embedding-space hallucination detection, and corpus readiness scores.
Run a Glass Bead Game session — a parlor game played against the Source Library corpus. Players connect verified passages from different books, times, and traditions into a growing string of 'beads,' with Claude as librarian, verifier, and scribe. Trigger when the user says 'glass bead game,' 'let's play beads,' or asks to start/resume/publish a game session. Claude runs the search-verify-display loop; humans do the noticing, choosing, and judging.
Stage-2 verification of first-translation flips using INDEPENDENT Claude subagents (subscription, not API key) with full evidence capture. Use to verify proposed badge changes (demotes/promotes) before writing any public claim — the binding step that catches AI-fabricated priors. Each subagent reports its actual search queries + sources, persisted to the first_translation_attempts provenance log.
Triage and respond to the user-feedback queue — pull open feedback, detect items already fixed but never marked, route translation-requests and metadata-corrections, mark items resolved, and (on approval) email submitters. Use when asked to check/triage/answer/clear feedback, "what are people saying?", or "respond to feedback."
Sweep Claude's private per-machine memory for team-relevant operational knowledge and propose moving it into the shared repo (or the private ops repo) as draft PRs. Use to promote lessons that accreted privately, or run on a schedule. Never auto-merges; never leaks.
One-shot audience & usage report — signups, DAU/MAU, time on-site, traffic, top content, search behavior, referrers, countries, and user journeys. Use when asked "what's our usage?", "how many signups?", "time on site?", "traffic?", or any audience/engagement metrics question.
| name | lesson |
| description | Record a lesson learned after fixing a bug or discovering a pattern. Updates domain memory files and checks for contradictions. Use after resolving non-trivial issues. |
After fixing a bug, resolving an incident, or discovering an important pattern, record it for future sessions.
Classify the domain. Determine which memory file this belongs to:
memory/pipeline-ops.mdmemory/data-quality.mdmemory/ui-navigation.mdmemory/mcp-server.mdmemory/lessons-learned.mdMEMORY.md (keep under 200 lines)Check for contradictions. Read the target memory file and check:
Write the entry. Format:
- **Short description (YYYY-MM-DD):** What happened, what the fix was, and the general rule to follow going forward.
Check staleness nearby. While editing, scan neighboring entries:
(verify).(snapshot, may be stale) if not already marked.Report. Tell the user what was added, what was updated, and any stale entries found.
Good entry:
- **Lambda timeout on large books (2026-03-13):** Books with >500 pages can exceed Lambda 15min timeout. Split into chunks of 400 pages max. See `src/lib/lambda-queue.ts:128`.
Bad entry (no date, no rule):
- Fixed the Lambda timeout issue.