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-avaliar-softwaregit 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-avaliar-software)<a href="https://agentmods.dev/skills/andregusman-raiz/a-gusman-claude/ag-avaliar-software"><img src="https://agentmods.dev/badge/skills/andregusman-raiz/a-gusman-claude/ag-avaliar-software/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-avaliar-software"><img src="https://agentmods.dev/badge/skills/andregusman-raiz/a-gusman-claude/ag-avaliar-software.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 | $0.00378 |
| Opus 5.5 | $0.00016 | $0.00151 |
| Sonnet 5.5 | $0.00008 | $0.00076 |
| Haiku 4.5 | $0.00004 | $0.00038 |
Grade A, and why
ag-avaliar-software 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 2mo 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
ag-avaliar-software — Due Diligence Tecnica
Spawn the ag-avaliar-software agent to evaluate external software for incorporation. Analyzes stack, quality, security, data, and compatibility. Produces Go/No-Go score.
Invocation
Use the Agent tool with:
subagent_type:ag-avaliar-softwaremode:autorun_in_background:trueprompt: Compose from template below + $ARGUMENTS
Prompt Template
Projeto: [CWD or user-provided path]
Software: [nome do software externo]
URL/Path: [URL do repo ou path local]
## Output
- Due diligence report com Go/No-Go score
- Analise de: stack, qualidade de codigo, seguranca, dados, compatibilidade com rAIz Platform
- Riscos identificados com mitigacao sugerida
Realize due diligence tecnica completa: identificacao, stack analysis, qualidade de codigo,
seguranca, dados/schema, compatibilidade com rAIz Platform (Next.js 14, TS, Supabase, Vercel).
Produza relatorio com score Go/No-Go fundamentado.
Referencia: Playbook 11 (Incorporacao de Software).
Important
- ALWAYS spawn as Agent subagent — do NOT execute inline
- Runs in background — produces detailed evaluation report
- After spawning, confirm to the user
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.
- 2mo ago First seen · 44 lines · 41 tokens per session scan A 38a838f2015c
ag-avaliar-software 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 378 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 2026-08-30.
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