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 skills add HezaoHezao/poirot --skill plangit clone --depth 1 https://github.com/HezaoHezao/poirotWrote 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/hezaohezao/poirot/plan)<a href="https://agentmods.dev/skills/hezaohezao/poirot/plan"><img src="https://agentmods.dev/badge/skills/hezaohezao/poirot/plan/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/hezaohezao/poirot/plan"><img src="https://agentmods.dev/badge/skills/hezaohezao/poirot/plan.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00012 | $0.02009 |
| Opus 5 | $0.00006 | $0.01005 |
| Sonnet 5 | $0.00002 | $0.00402 |
| Haiku 4.5 | $0.00001 | $0.00201 |
Grade A, and why
plan 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 10d 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.
This is a copy
75% identical to writing-plans — 109 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 339 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Plan Mode
Use this skill when the user wants a plan instead of execution.
Core behavior
For this turn, you are planning only.
- Do not implement code.
- Do not edit project files except the plan markdown file.
- Do not run mutating terminal commands, commit, push, or perform external actions.
- You may inspect the repo or other context with read-only commands/tools when needed.
- Your deliverable is a markdown plan saved under
.poirot/plans/.
Output requirements
Write a markdown plan that is concrete and actionable.
Include, when relevant:
- Goal
- Current context / assumptions
- Proposed approach
- Step-by-step plan
- Files likely to change
- Tests / validation
- Risks, tradeoffs, and open questions
If the task is code-related, include exact file paths, likely test targets, and verification steps.
Save location
Save the plan with write_file under:
.poirot/plans/YYYY-MM-DD_HHMMSS-<slug>.md
Treat that as relative to the active working directory / sandbox workspace. Poirot sandbox file tools are path-aware, so using this relative path keeps the plan with the workspace.
If no specific target path is provided by the runtime, create a sensible
timestamped filename yourself under .poirot/plans/.
Interaction style
- If the request is clear enough, write the plan directly.
- If no explicit instruction accompanies the plan request, infer the task from the current conversation context.
- If it is genuinely underspecified, ask a brief clarifying question instead of guessing.
- After saving the plan, reply briefly with what you planned and the saved path.
Writing the Plan Well
The rest of this skill is the craft of authoring a good implementation plan — the content that goes inside the markdown file above.
Overview
Write comprehensive implementation plans assuming the implementer has zero context for the codebase and questionable taste. Document everything they need: which files to touch, complete code, testing commands, docs to check, how to verify. Give them bite-sized tasks. DRY. YAGNI. TDD. Frequent commits.
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.
- 10d ago First seen · 339 lines · 12 tokens per session scan A 3201b9cc7968
plan is a skill published in the GitHub repository HezaoHezao/poirot (217 stars, last pushed 1mo ago), licensed MIT. It adds 12 tokens to every session and 2,009 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 75% identical to writing-plans, differing in 109 lines, and is treated as a copy.
Other skills, from other repositories
commit
Atomic git commit with conventional message. Use when the user says "commit", "save my changes", "commit this", or wants to create a git commit. Stages specific files, writes a conventional commit message with body explaining non-obvious decisions. Never uses git add -A.
python-run
Run and debug Python scripts in the project. Use when the user says "run python", "execute this script", "debug this py file", or wants to run/modify a .py file. Handles dependency checks, linting, execution, and error analysis.
hqe
Comprehensive codebase health auditing, remediation, and verification skill based on the canonical HQE Protocol v5.0.0.
cost-efficiency-analyzer
Analyzes cost structure, cost efficiency, and expense management from P&L data. Use when the user asks about costs, expenses, COGS, operating expenses, cost ratios, cost control, spending efficiency, margin compression from cost side, or wants to understand where money is going. Also use for "are we spending too…
computer-use
Read and drive native desktop applications through the accessibility layer — list on-screen apps, snapshot one window as a numbered element tree, then click / type / set a value / scroll / drag / run a named action, by element index or by screen coordinates. Use for work in a desktop app rather than a web page. Full…
feature-demo-recording
Record a demo video of a web feature from a real browser. Two modes -- a NARRATED film where measured voiceover drives the timeline (designed slides, subtitles, punch-in camera, rendered from an HTML timeline), and a SILENT evidence clip for a PR or a QA pass. Use when the user asks to record a video, demo, or screen…