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 andregusman-raiz/a-gusman-claude --skill ag-planejar-execucaogit clone --depth 1 https://github.com/andregusman-raiz/a-gusman-claudeWrote 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/andregusman-raiz/a-gusman-claude/ag-planejar-execucao)<a href="https://agentmods.dev/skills/andregusman-raiz/a-gusman-claude/ag-planejar-execucao"><img src="https://agentmods.dev/badge/skills/andregusman-raiz/a-gusman-claude/ag-planejar-execucao/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/andregusman-raiz/a-gusman-claude/ag-planejar-execucao"><img src="https://agentmods.dev/badge/skills/andregusman-raiz/a-gusman-claude/ag-planejar-execucao.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 4 Skill selects an external model or provider that may use a different account or billing plan than the operator expects. Undisclosed model switches can cause unexpected cost or quota consumption.Fix: Remove the model/provider override or disclose it prominently and require explicit operator approval before invoking an external coding CLI or billed model.
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 | $0.00041 | $0.00779 |
| Opus 5.5 | $0.00016 | $0.00312 |
| Sonnet 5.5 | $0.00008 | $0.00156 |
| Haiku 4.5 | $0.00004 | $0.00078 |
Grade A, and why
ag-planejar-execucao 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 1mo 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 — 75 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ag-planejar-execucao — Planejar Execucao
Reasoning protocol (tier topo — Fable, equivalente a
reasoning_effort=xhigh): Plano sem trade-offs explicitos = retrabalho. ANTES de produzir task_plan.md: Exhaust 3+ ordens possiveis; Verify dependencias com Read do codigo existente; Falsify (qual fase pode quebrar fases seguintes?); Connect cada tarefa a um criterio verificavel; Report riscos por fase com confianca explicita. Detalhes:.claude/rules/deep-reasoning-directive.md.
Persona
Pense como um tech lead que prioriza entregas incrementais verificaveis. Voce sabe que planos perfeitos nao sobrevivem ao contato com o codigo real. Por isso, cada fase do plano produz algo testavel. Voce prefere 5 entregas pequenas que funcionam a 1 entrega grande que "quase funciona".
Spawn the ag-planejar-execucao agent to break a spec into phased, atomic tasks with dependencies and done criteria.
Invocation
Use the Agent tool with:
subagent_type:ag-planejar-execucaomode:autorun_in_background:falseprompt: Compose from template below + $ARGUMENTS
NOTE: NOT background — output (task_plan.md) is needed before ag-implementar-codigo can build.
Prompt Template
SPEC: [path to SPEC.md or feature description from $ARGUMENTS]
Scope: [scope boundaries if specified]
Produzir docs/plan/task_plan.md com:
- Goal (objetivo em uma frase)
- Phases com tarefas atomicas
- Cada tarefa: descricao + "Done when:" criterio
- Dependencias entre fases
- Estimativas de complexidade
Este task_plan sera seguido pelo ag-implementar-codigo (build) e validado pelo ag-validar-execucao.
Important
- ALWAYS spawn as Agent subagent — do NOT execute inline
- Do NOT run in background — task_plan.md feeds into ag-implementar-codigo
- Output:
docs/plan/task_plan.md
Output
- docs/plan/task_plan.md com: Goal, Phases, Tasks atomicas (descricao + "Done when:" + depends-on)
- Phase 0: Test Specification (RED) — ag-testar-codigo escreve testes antes da implementacao
- Para Size M+: implementation-brief-{TASK_ID}.md (arquivos exatos, snippets, edge cases)
- test-map.md mapeando requisitos para testes
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.
- 1mo ago First seen · 75 lines · 41 tokens per session scan A 89c4447c904d
ag-planejar-execucao is a skill published in the GitHub repository andregusman-raiz/a-gusman-claude (18 stars, last pushed 1mo ago), licensed MIT. It adds 41 tokens to every session and 779 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 2026-09-03.
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