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.
git clone --depth 1 https://github.com/felvieira/claude-skills-fvWrote 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/commands/felvieira/claude-skills-fv/humanize)<a href="https://agentmods.dev/commands/felvieira/claude-skills-fv/humanize"><img src="https://agentmods.dev/badge/commands/felvieira/claude-skills-fv/humanize/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/commands/felvieira/claude-skills-fv/humanize"><img src="https://agentmods.dev/badge/commands/felvieira/claude-skills-fv/humanize.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 | $0.00052 | $0.01898 |
| Opus 5 | $0.00026 | $0.00949 |
| Sonnet 5 | $0.00010 | $0.00380 |
| Haiku 4.5 | $0.00005 | $0.00190 |
Grade A, and why
humanize 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 12d 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 — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/humanize — Remove AI Writing Patterns
Objetivo: reescrever texto para soar natural e humano, removendo os 29 padrões catalogados em policies/anti-ai-writing.md. Baseado em blader/humanizer + Wikipedia: Signs of AI writing.
Quando usar:
- antes de publicar PRD no tracker (
/to-prd) - ao finalizar docs de usuário (skill 10)
- ao revisar copy antes de publicar (skill 13)
- ao revisar artigo/blog (skill 14, skill 41)
- ao revisar página de vendas/ads (skill 50)
- em todo texto final que vai pro ar: landing page, app, blog, README público
- ao revisar qualquer prosa que humanos vão ler
Quando NÃO usar:
- código-fonte (não é prosa)
- comentários técnicos curtos (overhead desproporcional)
- conteúdo em idioma diferente do input (skill processa no idioma do texto)
Skill ativada: Documenter (skill 10) em modo "anti-AI editor".
Processo
Passo 1 — Detectar input
# Argumento é path de arquivo?
test -f "$1" && cat "$1" # lê arquivo
# Sem argumento: texto veio inline na conversa
Se nenhum input detectado: pedir ao usuário o texto ou path.
Passo 2 — Voice calibration (opcional)
Se o usuário forneceu amostra de escrita própria (inline ou path):
- Ler a amostra antes de qualquer reescrita
- Notar: comprimento de frases, nível de vocabulário, início de parágrafos, pontuação, vícios de linguagem, como trata transições
- Usar esses padrões na reescrita — não apenas remover AI-isms, mas substituir com os padrões da amostra
Se sem amostra: usar voz padrão (natural, variada, opinativa).
Passo 3 — Draft rewrite
Aplicar todas as 5 categorias de policies/anti-ai-writing.md:
- Conteúdo (padrões 1-6): significado inflado, notabilidade, -ing superficial, linguagem promocional, atribuições vagas, seções formulaicas
- Linguagem (padrões 7-13): vocabulário AI, copula avoidance, paralelismos negativos, regra dos três, synonym cycling, falsos ranges, passiva sem sujeito
- Estilo (padrões 14-19): em dash, negrito, listas com cabeçalho inline, title case, emojis, curly quotes
- Comunicação (padrões 20-22): artefatos de chatbot, disclaimers de cutoff, sycofância
- Enchimento (padrões 23-29): frases de enchimento, hedging, conclusões genéricas, hifenização excessiva, autoridade persuasiva, signposting, headers com aquecimento
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.
- 12d ago First seen · 141 lines · 52 tokens per session scan A d03371e1f1d3
humanize is a command published in the GitHub repository felvieira/claude-skills-fv (23 stars, last pushed 2d ago), licensed Apache-2.0. It adds 52 tokens to every session and 1,898 once invoked, about $0.0003 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.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.