conversation-to-skill-miner

name	conversation-to-skill-miner
description	Mine conversation archives, topic memory, idea inboxes, and project notes for reusable agent-skill candidates, then classify which should be packaged, reviewed, or kept private. Use when Codex is asked to search chats/conversations for possible skills, turn repeated workflows into skills, run a weekly skill-mining review, or prepare a safe public skill backlog from private conversation history.

Conversation To Skill Miner

Overview

Convert messy conversation history into a safe skill backlog. The goal is not to publish every idea; it is to identify repeatable workflows, remove private or high-risk material, and package only the candidates that can be useful without leaking personal context.

Read references/publishability-rubric.md when deciding whether a candidate can be published.

Workflow

1. Define the scan boundary.

   • Prefer durable archives: conversation-memory/, conversation-archive/, daily-ideas/, project READMEs, and existing local skill folders.
   • Do not scan private messaging exports, browser profiles, secrets, or raw logs unless the user explicitly asks and the output will remain private.

2. Find repeated workflows.

   • Look for phrases such as skill, workflow, pipeline, SOP, agent, 继续, 整理, 归档, 自动化, weekly, GitHub, PPT, paper, Simulink, and screen.
   • Prefer workflows that have been requested more than once or already have artifacts, scripts, reports, or topic-memory entries.

3. Classify each candidate.

   • publish_now: generic, safe, repeatable, and already proven by at least one real task.
   • review_first: promising but may contain personal data, domain risk, weak examples, missing validation, or unclear audience.
   • keep_private: depends on private contacts, credentials, sensitive profiling, personal health/finance decisions, or private chat content.

4. Package only safe candidates.

   • Strip raw conversation text and personal examples.
   • Keep general workflows, safety boundaries, trigger phrases, and reusable scripts.
   • Add references only when they are public, lawful, and one level deep from SKILL.md.

5. Validate and report.

   • Run quick_validate.py for each skill.
   • Produce a concise report with candidate name, source pointer, decision, risk, next packaging action, and recommended repository.
   • Keep generated reports local unless they are manually sanitized.

Script

Use the bundled scanner for a first pass:

python3 scripts/scan_conversations_for_skills.py \
  --workspace /path/to/Codex \
  --output /path/to/weekly-skill-candidates.md

The script outputs a markdown report and a sibling JSON file. Treat its result as a triage aid; the agent still makes final publishability decisions.

Weekly Review Rule

For weekly operation, schedule only the scan/report step automatically. Do not auto-publish directly from private conversations. Public upload should happen after an explicit review pass that confirms no secrets, raw chats, private profiles, or copyrighted material are included.