cog-weekly-reflection
Cross-domain pattern analysis with personal, professional, and project domain synthesis
npx skills add a5c-ai/babysitter --skill weekly-reflection --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
- Identify patterns in personal domain (energy, mood, productivity) - Identify patterns in professional domain (skills, career, industry) - Identify patterns in project domain (velocity, blockers, progress) - Synthesize cross-domain connections - Generate actionable insights with confidence levels - Quality-gated reflection with iterative refinement ## Tool Use Instructions 1. Use `file-read` to load entries from 01-daily, 02-personal, 03-professional, 04-projects 2. Use `file-search` to find related entries across sections 3. Analyze patterns within each domain independently 4. Synthesize cross-domain connections 5. Use `file-write` to create weekly check-in in 01-daily 6. Add cross-references to identified patterns 7. Use `git-commit` to commit reflection ## Examples ```json { "vaultPath": "./cog-vault", "mode": "weekly-checkin", "userName": "Alex", "rolePack": "engineer", "targetQuality": 80 } ```
- Tool Use Instructions
- Examples
What does the cog-weekly-reflection skill do?
Cross-domain pattern analysis with personal, professional, and project domain synthesis
How do I install it?
Run `npx skills add a5c-ai/babysitter --skill weekly-reflection --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From a5c-ai/babysitter, a repository with 1,642 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.