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/gaoscode/planweave/plan-makernpx skills add GaosCode/PlanWeave --skill plan-makergit clone --depth 1 https://github.com/GaosCode/PlanWeaveWhat 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 | $0.00084 | $0.01760 |
| Opus 5 | $0.00042 | $0.00880 |
| Sonnet 5 | $0.00017 | $0.00352 |
| Haiku 4.5 | $0.00008 | $0.00176 |
Grade A, and why
plan-maker 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 2d 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.
How it starts
The opening of the file, as written. The whole thing — 137 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Plan Maker
Use this skill to design a PlanWeave package-shaped plan draft from incomplete input. Do not execute work, audit an existing package, or write a Plan Package unless the user explicitly asks to materialize the plan.
Quick Start
- Restate the user's goal, non-goals, constraints, and likely success criteria.
- Ask only blocking clarification questions; otherwise state assumptions and continue.
- Gather lightweight context from README, current code, schemas, tests, examples, and nearby docs.
- Identify core objects, lifecycle stages, contracts, risks, and validation paths.
- Draft canvases, tasks, blocks, formal project graph dependencies, prompt placement, review gates, and verification using PlanWeave's existing package concepts.
- End with open assumptions and the recommended next action: refine with the user, audit with
plan-auditor, or materialize the draft when explicitly requested.
Context Discovery
- If strong source docs exist and the main job is converting them into a Plan Package, use
plan-importer. - If no docs exist, inspect the current codebase enough to avoid invented architecture.
- Search producers and consumers for likely core objects before splitting tasks.
- Treat user goals as authority, but mark uncertain scope, missing domain rules, and unknown external dependencies.
- Do not invent large product requirements to make the plan look complete.
Planning Principles
- Design around core object lifecycles: create, validate, transform, state, storage, consumption, side effects, final output, failure, retry, rollback, and manual intervention.
- Keep schema, types, APIs, CLI flags, events, files, and prompt inputs/outputs consistent across producers and consumers.
- Split tasks by data flow, contract boundary, ownership, risk, or independently verifiable acceptance.
- Do not split only to create more nodes; merge tiny tasks that cannot be claimed, tested, or reported independently.
- Model real execution order with explicit dependencies and gates.
- Parallel tasks must be genuinely independent in data and contract timing. Record possible overlap
with
parallel.sharedResourcesso agents and the canvas can surface coordination context. - Express mandatory order with graph dependencies.
- For multi-canvas plans, model orchestration as a formal project graph, not as prose-only canvas order.
- Do not schedule broad UI/package polish before foundation contracts and runtime behavior are stable.
- Do not import other projects' skills, bootstrap rules, or prompt conventions unless this target repository explicitly requires them.
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.
- 2d ago First seen · 137 lines · 84 tokens per session scan A 8d26dda8d1db
plan-maker is a skill published in the GitHub repository GaosCode/PlanWeave (364 stars, last pushed 4d ago), licensed MIT. It adds 84 tokens to every session and 1,760 once invoked, about $0.0004 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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