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 commands/hmaurus/masterclaude/linkedin-postgit clone --depth 1 https://github.com/hmaurus/masterclaudeWhat 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 | $0.00018 | $0.00445 |
| Opus 5 | $0.00009 | $0.00222 |
| Sonnet 5 | $0.00004 | $0.00089 |
| Haiku 4.5 | $0.00002 | $0.00044 |
Grade A, and why
linkedin-post 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.
What it actually says
LinkedIn Post
Crie e publique um post no LinkedIn seguindo estas etapas:
Contexto obrigatório
Antes de criar qualquer conteúdo, consulte estes documentos de referência (se disponíveis no projeto atual):
docs/referencias/perfil-de-maurus.md— tom pessoal, valores, estilo de comunicação.agents/product-marketing-context.md— posicionamento, brand voice, keywordsdocs/referencias/social-content.md— preferências de postagem LinkedIn
Regras
- Tom: pessoal, opinativo, autêntico — nunca corporativo ou genérico
- Links: NÃO colocar links no corpo do post (LinkedIn reduz alcance). Mencionar que o link vai no primeiro comentário se necessário
- Formato: LinkedIn usa formato "little" — o MCP server escapa caracteres automaticamente
- Imagens: Se o usuário mencionar imagem, usar
linkedin_create_post_with_imagecom o caminho absoluto do arquivo - Workflow: SEMPRE exibir o rascunho completo para aprovação antes de postar
Fluxo
- Verificar status do token com
linkedin_check_status - Se o usuário forneceu tema/conteúdo, redigir o post seguindo o tom e regras acima
- Exibir rascunho para aprovação
- Após aprovação, publicar usando o tool adequado:
- Texto:
linkedin_create_post - Com imagem:
linkedin_create_post_with_image - Com link:
linkedin_create_post_with_link
- Texto:
- Retornar URL do post publicado
Argumento
$ARGUMENTS
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 First seen · 45 lines · 18 tokens per session scan A 80b4eb9407c1
linkedin-post is a command published in the GitHub repository hmaurus/masterclaude (2 stars, last pushed 1mo ago), licensed MIT. It adds 18 tokens to every session and 445 once invoked, about $0.0001 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 2026-08-31.
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.
constitution
Create or update the project constitution from interactive or provided principle inputs.
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.