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Create and manage structured documentation — experiments, plans, findings, checkpoints, research, learnings. Config-driven, parallel-safe.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
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Create and manage structured documentation — experiments, plans, findings, checkpoints, research, learnings. Config-driven, parallel-safe.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Karpathy-inspired autonomous research loop. Agent edits one file, evals, keeps or discards, repeats. Plateau-triggered web search breaks through ceilings. Git as state machine. Runs until stopped or budget exhausted. Supports claude, codex, and pi providers.
Persistent, budgeted, DAG-ordered runner for parallel `claude -p`, `codex exec`, or `pi -p` workers in tmux. Use ONLY when you need persistence across sessions, per-worker budget caps, dependency ordering, or mixed models/providers per worker. For ad-hoc parallel sub-agents inside a live conversation, use Claude Code's built-in Agent tool instead.
Analyze a task, pick the right fleet type, and generate a ready-to-launch fleet (fleet.json + prompt.md files). Discovers available fleet skills dynamically. Use when the user wants to run work in parallel, asks to "plan a fleet", or says "fleet-plan".
Reviewer-gated iterative fleet for headless `claude -p`, `codex exec`, or `pi -p` workers that run in cycles until a designated reviewer approves the output. Use when the work needs multiple rounds of iteration with a quality gate — a reviewer worker reads all worker logs, writes a verdict (lgtm | iterate | escalate), and the orchestrator decides whether to continue, pause, or stop. NEVER kills or restarts workers automatically; the operator owns all kill/pause decisions.
Use when exporting Markdown reports to PDF, especially when Mermaid diagrams render blank, oversized, lose color, tables overflow, a TOC or PDF outline is needed, or Chrome/Puppeteer adds unwanted page headers and footers.
Independence-validated parallel fleet that runs each worker (claude -p, codex exec, or pi -p) in its own git worktree. Use when tasks touch non-overlapping files and you need merge-safe isolation (each worker on its own branch). For DAG-ordered one-shot workers with budgets, use dag-fleet. For headless iteration with a reviewer loop, use iterative-fleet.
| name | doc |
| description | Create and manage structured documentation — experiments, plans, findings, checkpoints, research, learnings. Config-driven, parallel-safe. |
| argument-hint | [start|expt|plan|finding|ckpt|research|review|learn|list|status|resume] [args] |
| allowed-tools | Bash(bash ${AGENTS_SKILLS_DIR}/scripts/*), Read, Write, Glob, Grep |
| license | Apache-2.0 |
| metadata | {"author":"Sagar Sarkale","version":"1.0"} |
Config-driven documentation scaffolding. Config lives inside the skill at config/defaults.yaml — no repo-root files needed.
| Command | What to run |
|---|---|
| start <name> | bash ${AGENTS_SKILLS_DIR}/scripts/start.sh "<name>" |
| expt <name> | bash ${AGENTS_SKILLS_DIR}/scripts/expt.sh "<name>" |
| plan <index> <title> | bash ${AGENTS_SKILLS_DIR}/scripts/plan.sh <index> "<title>" |
| finding <index> <title> | bash ${AGENTS_SKILLS_DIR}/scripts/finding.sh <index> "<title>" |
| ckpt <index> <description> | bash ${AGENTS_SKILLS_DIR}/scripts/ckpt.sh <index> "<description>" |
| research <index> <topic> | bash ${AGENTS_SKILLS_DIR}/scripts/research.sh <index> "<topic>" |
| review <index> <title> | bash ${AGENTS_SKILLS_DIR}/scripts/review.sh <index> "<title>" |
| learn <index> <domain> <title> | bash ${AGENTS_SKILLS_DIR}/scripts/learn.sh <index> "<domain>" "<title>" |
| list | bash ${AGENTS_SKILLS_DIR}/scripts/list.sh |
| status <index> | bash ${AGENTS_SKILLS_DIR}/scripts/status.sh <index> |
| resume <index> | bash ${AGENTS_SKILLS_DIR}/scripts/resume.sh <index> |
start = scaffold docs/ + create experiment. Use this when beginning new work.
expt = create experiment only. Use when docs/ already exists.
You are responsible for tracking the active experiment per conversation. When the user creates an experiment or references one, remember its index. Pass it to every script call — scripts are stateless and parallel-safe.
| User says... | You do... |
|---|---|
| "Let's investigate X" / starts new work | /doc start "<name>" — remember the returned index |
| "Plan this" / "How should we approach" | /doc plan <idx> "<title>" then write plan content into the created file |
| User enters plan mode | STOP. Do NOT use .claude/plan.md. Instead run /doc plan <idx> "<title>" and write directly there. Plans live in experiment folders, never in ephemeral storage. |
| You discover something significant | /doc finding <idx> "<title>" then write finding content |
| Conversation wrapping up / context switch | /doc ckpt <idx> "<short-label>" — short label only (2-5 words), then write body content into the file with What/Why/How + mermaid diagram. Do this automatically without being asked. |
| "Research X" / "Look into Y" | /doc research <idx> "<topic>" — write prompt, do research, write results |
| "Review X" / "Check this output" | /doc review <idx> "<title>" then write review content with verdict |
| "Remember this" / "Key learning" | /doc learn <idx> <domain> "<title>" — write distilled insight |
| "Continue experiment 19" / "Pick up" | /doc resume <idx> — reads meta + latest plan + latest checkpoint. Set as active for this conversation. |
| "What experiments exist?" | /doc list |
| "What's the state of experiment 19?" | /doc status <idx> |
/doc list to show optionsYou resolve context. Scripts just take a number.
.claude/plan.md or any ephemeral storage. ALWAYS use /doc plan./doc resume first to load context.The ckpt command arg is a short label (2-5 words), NOT the checkpoint content. After the script creates the file, you MUST write the body into it using this structure:
```mermaid
graph TD
A[Starting state] --> B[What was done]
B --> C[Current state]
C --> D[Next steps]
```
## What
What was accomplished. Bullet points, brief.
## Key Takeaways
Surprising findings, confirmed/rejected hypotheses, numbers that matter.
## Issues
Blockers hit, workarounds used, unresolved problems. Include error messages if relevant.
## Decisions
Key choices made and why. What was considered and rejected.
## Next
Concrete next steps with enough detail that a new agent can pick up cold.
Include file paths, command examples, and what to watch out for.
The checkpoint must contain everything a fresh agent needs to continue the work without asking questions. Be brief but complete — file paths, key numbers, what worked, what didn't.
DO NOT cram content into the description argument. Keep the arg short: /doc ckpt 7 "v1 analysis complete" then edit the file.
experiments/NNN-{name}/
├── .meta.json auto-updated by scripts
├── plans/ multiple plans, numbered
├── findings/ multiple findings, numbered
├── checkpoints/ progress snapshots, numbered
├── review/ structured reviews, numbered
└── research/ prompt + response pairs, numbered
/doc start my-investigation — that's it. Scaffolds docs/ and creates the first experiment.
To customize folder structure or naming: edit config/defaults.yaml inside the skill.
.meta.json.23 not 023 not 023-docs-and-structs..claude/plan.md. This is non-negotiable.config/defaults.yaml. learn will error on invalid domains."auth-flow" not "investigation-into-authentication-flow-reliability-issues". The numbering prefix handles ordering; the title just needs to identify the topic at a glance.$ARGUMENTS