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 joao-aires/agent-skills-public --skill plangit clone --depth 1 https://github.com/joao-aires/agent-skills-publicWrote 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/joao-aires/agent-skills-public/plan)<a href="https://agentmods.dev/skills/joao-aires/agent-skills-public/plan"><img src="https://agentmods.dev/badge/skills/joao-aires/agent-skills-public/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/joao-aires/agent-skills-public/plan"><img src="https://agentmods.dev/badge/skills/joao-aires/agent-skills-public/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 | $0.00039 | $0.00547 |
| Opus 5.5 | $0.00016 | $0.00219 |
| Sonnet 5.5 | $0.00008 | $0.00109 |
| Haiku 4.5 | $0.00004 | $0.00055 |
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 yesterday.
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 — 43 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Plan
Read task guidance. Reuse existing plans and commands; scale the plan to the agreed work.
Establish the planning basis
- Agree on the outcome and completion evidence. Refine material gaps before assuming scope.
- Inspect affected architecture and contracts. Use system-design after product refinement or when the feature changes consequential architecture, before dependent planning or implementation.
- Read project conventions for existing constraints and delivery guidance for acceptance and verification.
- Load optional stack/domain guidance selected by task guidance only when relevant and available. Use service-contract design expertise for changed service behavior.
Order the work by its dependencies
Start from a useful observable result and work backward to its prerequisites. A good increment joins enough of the application to prove something meaningful: a caller can exercise the operation, the necessary data changes occur, and a check can distinguish success from failure. Organizing the plan only by folders or technical layers can postpone discovery that those parts do not work together.
Put uncertain or constraining work early enough that it can change the remaining plan. For each increment, name the behavior it delivers, the important prerequisite and the evidence needed before moving on. Reuse the project's technical conventions to choose implementation detail. Include the consequences that apply:
| Affected concern | Include in the plan |
|---|---|
| UI or interaction behavior | UI/behavior design before dependent implementation |
| Persistence or consumers | Migration and compatibility work |
| Acceptance and regression risk | Focused tests and their evidence |
| Delivery and failure | Release and recovery consequences |
Return an executable plan
Return steps in the order they can actually be carried out. Make it clear which work is ready, which depends on a decision, and which can proceed independently. For changes to persisted data or deployed consumers, explain the order in which old and new versions can coexist and when cleanup becomes safe.
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.
- yesterday Changed · +24 lines 9ea2c690de3e
- 2d ago Changed 22c16231f481
- 5d ago Changed 99a9077fa540
- 7d ago First seen · 19 lines · 39 tokens per session scan A 1fd5f7a29354
plan is a skill published in the GitHub repository joao-aires/agent-skills-public (2 stars, last pushed yesterday), licensed MIT. It adds 39 tokens to every session and 547 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-10-15.
Other skills, from other repositories
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…