Babysitter is a workflow engine for AI coding agents that enforces predefined steps, quality checks, human approvals, and decision records. It is used to coordinate complex, repeatable agent workflows across supported coding tools. The catalogue contains skills, agents, instructions, settings, a plugin, and an MCP integration for its workflow.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/a5c-ai/babysitter/planning-patternsnpx skills add a5c-ai/babysitter --skill planning-patternsgit clone --depth 1 https://github.com/a5c-ai/babysitterWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/a5c-ai/babysitter/planning-patterns)<a href="https://agentmods.dev/skills/a5c-ai/babysitter/planning-patterns"><img src="https://agentmods.dev/badge/skills/a5c-ai/babysitter/planning-patterns.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00025 | $0.00375 |
| Opus 5 | $0.00013 | $0.00187 |
| Sonnet 5 | $0.00005 | $0.00075 |
| Haiku 4.5 | $0.00003 | $0.00038 |
Grade A, and why
planning-patterns scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
- Search for existing solutions and patterns
- Identify relevant libraries and tools
- Find best practices in the domain
- Check for known pitfalls
2. Brainstorming Phase
- Generate at least 3 alternative approaches
- Evaluate trade-offs: complexity, time, risk, scalability
- Consider build-vs-buy decisions
- Rank by feasibility and alignment
3. Plan Creation
- Structure with phases, tasks, and milestones
- Define acceptance criteria per phase
- Map dependencies between tasks
- Include risk assessment with mitigations
- Define TDD strategy per coding phase
- Estimate effort and timeline
4. Review Gate
- Verify completeness against original request
- Validate logical phase ordering
- Check actionability of risk mitigations
- Score plan completeness (>=80 to pass)
Plan-to-Build Continuity
- Save plans to
docs/plans/directory - Reference plan file in session memory
- BUILD workflow reads plan during requirements clarification
- Component-builder follows documented phases
When to Use
- PLAN workflow (primary)
- Any task requiring strategic thinking before execution
Agents Used
planner(primary consumer)github-researcher(research phase)
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 6d ago First seen · 54 lines · 25 tokens per session scan A 1d4d0943fc25
planning-patterns is a skill published in the GitHub repository a5c-ai/babysitter (1,769 stars, last pushed yesterday), licensed MIT. It adds 25 tokens to every session and 375 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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