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Log work to daily notes with timestamps. Use proactively after completing tasks, reaching milestones, or finishing research sessions. High signal, no redundancy.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
Manage a bookmark research pipeline — fetch new bookmarks, triage against research interests, spawn parallel deep-dive agents, and review results. Use when the user says "bookmark sync", "check bookmarks", "review bookmarks", "triage bookmarks", "deep dive bookmarks", "run bookmark pipeline", or asks about setting up the bookmark system.
Update project context files when reality has drifted from docs. Use when a milestone is hit, the plan has changed, CLAUDE.md feels stale, or the user says "update the docs", "sync context", "evolve context". Walks through ledger, plan, CLAUDE.md, README, and architecture docs.
Create a new project with consistent structure and documentation. Use when the user says "new project" or "start a project" or when building something new. Sets up for agent-assisted development from day one.
Turn any question into an automated feedback loop. The pattern — design a sensor (eval), an actuator (code the agent modifies), and launch an evolutionary optimization loop. Works on any (code → run → score) problem — model training, software optimization, prompt tuning, eval design, data pipelines, agent harnesses. The eval function IS the research.
Mine session logs for skill usage patterns, corrections, and failures to propose improvements. Use when the user says "improve skills", "review skill usage", "what have we learned about our skills", or periodically to evolve skills based on real usage data.
Design and improve harnesses — the environments, constraints, feedback loops, and control systems that make AI agents do reliable work. Use when setting up a new project for agent-assisted development, diagnosing why agents are producing bad output, reviewing architectural constraints, or thinking about how to scale human oversight of agent workflows. Synthesizes OpenAI's harness engineering principles with cybernetic control theory.
| name | log-work |
| description | Log work to daily notes with timestamps. Use proactively after completing tasks, reaching milestones, or finishing research sessions. High signal, no redundancy. |
Log work to daily notes with timestamps. High signal, no redundancy.
Trigger this skill when:
Use judgment - not every tiny action, but meaningful work.
Log entries in daily note (YYYY-MM-DD.md):
[HH:MM] Description of work #tags
- Detail or sub-item
- Another detail
Use #tags for categorization (e.g., #project-setup, #research, #engineering).
Use indented bullets for details when helpful.
Examples:
[15:55] Created new simulations project #project-setup
- Set up project structure in `projects/simulations/`
- Created README.md with overview and goals
[16:12] Simplified to trace-based submission system #data-structure
- Core insight: It's just a form submission with proof of execution
- Standard event schema defined
[12:16] Finished vault reorganization #organization
- New entities/ structure with agents/, humans/, orgs/
- Created 3 new skills
- 267 files moved
date "+%H:%M"
Never guess the time.
Check for YYYY-MM-DD.md in your notes directory. Create if missing.
Add the log entry with timestamp, description, tags, and details.
Empty — add failure modes here as they're discovered in real use.
date command, never assumeBrief confirmation: "Logged: [timestamp] [description]"