القائمة
The single owner of the hypothesis lifecycle — creates, tests, promotes, and kills hypotheses. Uses extensions as programmatic data collectors and reviews their output.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Tags transcript message threads with semantic concepts (roast, game-recommendation, etc.) so past conversations can be searched by idea, not just keywords.
Captures notable interactions missed during live conversation — new person info, game preferences, boundaries, jokes that landed/flopped, relationship insights.
Consolidates impression files by applying weight decay, removing redundant entries, and enforcing per-user limits. Maintains relationship file summaries.
Consolidates old memories by removing duplicates, promoting recurring patterns to learned-patterns.md or relationship files, and archiving outdated entries.
Identifies behavioral patterns from recent conversations and reaction feedback, updates learned-patterns.md when 3+ observations confirm a pattern.
Evaluates overall effectiveness — are idle behaviors producing value, are extensions working, what's blocking improvement. Higher-level thinking about approach, not individual conversations.
| name | hypothesis-review |
| description | The single owner of the hypothesis lifecycle — creates, tests, promotes, and kills hypotheses. Uses extensions as programmatic data collectors and reviews their output. |
| allowed-tools | Read, Write, Edit, Grep, Glob, Bash, mcp__custom-tools__search_transcripts |
You own the entire hypothesis lifecycle. Other skills (self-reflection, pattern-learning) may notice things worth testing — they'll note them in memory files for you to pick up. You're the only skill that reads/writes agent-data/hypotheses.md.
Read agent-data/hypotheses.md. For each in Testing/Untested:
Check extension data first — if an extension is collecting data for this hypothesis, read agent-data/hypothesis-data/ for structured JSONL files. This is cheaper and more reliable than manual transcript searching.
If no extension exists, search transcripts + impressions + reaction-feedback.jsonl manually. Update status based on findings.
For hypotheses with quantifiable predictions (rates, counts, patterns) that have been active 1+ weeks without enough data:
local/extensions/ that uses hooks (onReaction, postResponse, onSkillComplete, etc.) to collect data to agent-data/hypothesis-data/. Read EXTENSIONS.md for the API.local/extensions/.A good hypothesis has: specific prediction + data-grounded reason + concrete verification method. Write to ## Untested in hypotheses.md.
Mine for: cross-user dynamics, temporal patterns, blind spots, relationship evolution, idle skill effectiveness.
learned-patterns.md, move to Resolved. Re-read to verify the write.Delete agent-data/hypothesis-data/*.jsonl files for resolved hypotheses. Remove corresponding extensions from local/extensions/.
Write findings to today's memory file under ## Hypothesis Review.
Cooldown: 720 minutes
agent-data/hypothesis-data/ first (cheap, structured)