Skill Sentinel

Skill Sentinel

Overview

This public intake copy packages plugins/antigravity-awesome-skills-claude/skills/skill-sentinel from https://github.com/sickn33/antigravity-awesome-skills into the native Omni Skills editorial shape without hiding its origin.

Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.

This intake keeps the copied upstream files intact and uses the external_source block in metadata.json plus ORIGIN.md as the provenance anchor for review.

Skill Sentinel

Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: How It Works, Resumo Rapido, Localizacao, Instalacao, Comandos Principais, Auditoria Completa De Todas As Skills.

When to Use This Skill

Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.

• When the user mentions "auditar skills" or related topics
• When the user mentions "qualidade skills" or related topics
• When the user mentions "verificar skills ecossistema" or related topics
• When the user mentions "saude ecossistema skills" or related topics
• When the user mentions "skills duplicadas" or related topics
• When the user mentions "otimizar skills" or related topics

Operating Table

Workflow

This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.

1. python C:\Users\renat\skills\skill-sentinel\scripts\runaudit.py --format json 1.
2. Primeira auditoria do ecossistema: ` python runaudit.py Gera relatorio completo com scores, findings e recomendacoes.
3. Monitorar evolucao ao longo do tempo: python runaudit.py --compare Mostra delta de scores entre auditorias.
4. Validar uma skill antes de deploy: python runaudit.py --skill nome-da-skill Auditoria focada com findings especificos.
5. Identificar proxima skill a criar: python run_audit.py --recommend ` Gap analysis com templates prontos.
6. Confirm the user goal, the scope of the imported workflow, and whether this skill is still the right router for the task.
7. Read the overview and provenance files before loading any copied upstream support files.

Imported Workflow Notes

Imported: Output Em Json (Para Processamento)

python C:\Users\renat\skills\skill-sentinel\scripts\run_audit.py --format json

Imported: Workflows Comuns

1. Primeira auditoria do ecossistema:

python run_audit.py

Gera relatorio completo com scores, findings e recomendacoes.

2. Monitorar evolucao ao longo do tempo:

python run_audit.py --compare

Mostra delta de scores entre auditorias.

3. Validar uma skill antes de deploy:

python run_audit.py --skill nome-da-skill

Auditoria focada com findings especificos.

4. Identificar proxima skill a criar:

python run_audit.py --recommend

Gap analysis com templates prontos.

Imported: Overview

Auditoria e evolucao do ecossistema de skills. Qualidade de codigo, seguranca, custos, gaps, duplicacoes, dependencias e relatorios de saude.

Imported: How It Works

Meta-agente que monitora, audita e evolui o ecossistema de skills. Analisa todas as skills em 7 dimensoes, identifica problemas, sugere melhorias e recomenda novas skills especialistas.

Examples

Example 1: Ask for the upstream workflow directly

Use @skill-sentinel to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.

Explanation: This is the safest starting point when the operator needs the imported workflow, but not the entire repository.

Example 2: Ask for a provenance-grounded review

Review @skill-sentinel against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.

Explanation: Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.

Example 3: Narrow the copied support files before execution

Use @skill-sentinel for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.

Explanation: This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.

Example 4: Build a reviewer packet

Review @skill-sentinel using the copied upstream files plus provenance, then summarize any gaps before merge.

Explanation: This is useful when the PR is waiting for human review and you want a repeatable audit packet.

Best Practices

Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.

• Provide clear, specific context about your project and requirements
• Review all suggestions before applying them to production code
• Combine with other complementary skills for comprehensive analysis
• Keep the imported skill grounded in the upstream repository; do not invent steps that the source material cannot support.
• Prefer the smallest useful set of support files so the workflow stays auditable and fast to review.
• Keep provenance, source commit, and imported file paths visible in notes and PR descriptions.
• Point directly at the copied upstream files that justify the workflow instead of relying on generic review boilerplate.

Imported Operating Notes

Imported: Best Practices

• Provide clear, specific context about your project and requirements
• Review all suggestions before applying them to production code
• Combine with other complementary skills for comprehensive analysis

Troubleshooting

Problem: The operator skipped the imported context and answered too generically

Symptoms: The result ignores the upstream workflow in plugins/antigravity-awesome-skills-claude/skills/skill-sentinel, fails to mention provenance, or does not use any copied source files at all. Solution: Re-open metadata.json, ORIGIN.md, and the most relevant copied upstream files. Check the external_source block first, then restate the provenance before continuing.

Problem: The imported workflow feels incomplete during review

Symptoms: Reviewers can see the generated SKILL.md, but they cannot quickly tell which references, examples, or scripts matter for the current task. Solution: Point at the exact copied references, examples, scripts, or assets that justify the path you took. If the gap is still real, record it in the PR instead of hiding it.

Problem: The task drifted into a different specialization

Symptoms: The imported skill starts in the right place, but the work turns into debugging, architecture, design, security, or release orchestration that a native skill handles better. Solution: Use the related skills section to hand off deliberately. Keep the imported provenance visible so the next skill inherits the right context instead of starting blind.

Related Skills

• @00-andruia-consultant - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @00-andruia-consultant-v2 - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @10-andruia-skill-smith - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @10-andruia-skill-smith-v2 - Use when the work is better handled by that native specialization after this imported skill establishes context.

Additional Resources

Use this support matrix and the linked files below as the operator packet for this imported skill. They should reflect real copied source material, not generic scaffolding.

• analysis_criteria.md
• schema.md
• security_patterns.md
• skill_template.md
• analyzers/init.py
• analyzers/code_quality.py
• analyzers/cross_skill.py
• analyzers/dependencies.py

Imported Reference Notes

Imported: Resumo Rapido

Imported: Localizacao

C:\Users\renat\skills\skill-sentinel\
├── SKILL.md
├── scripts/
│   ├── requirements.txt
│   ├── config.py
│   ├── db.py
│   ├── governance.py
│   ├── scanner.py
│   ├── analyzers/
│   │   ├── code_quality.py
│   │   ├── security.py
│   │   ├── performance.py
│   │   ├── governance_audit.py
│   │   ├── documentation.py
│   │   ├── dependencies.py
│   │   └── cross_skill.py
│   ├── recommender.py
│   ├── cost_optimizer.py
│   ├── report_generator.py
│   └── run_audit.py
├── references/
│   ├── analysis_criteria.md
│   ├── security_patterns.md
│   ├── skill_template.md
│   └── schema.md
└── data/
    ├── sentinel.db
    └── reports/

Imported: Instalacao

pip install -r C:\Users\renat\skills\skill-sentinel\scripts\requirements.txt

Imported: Comandos Principais

#### Imported: Auditoria Completa De Todas As Skills

python C:\Users\renat\skills\skill-sentinel\scripts\run_audit.py

#### Imported: Auditar Apenas Uma Skill

python C:\Users\renat\skills\skill-sentinel\scripts\run_audit.py --skill instagram

#### Imported: Apenas Recomendacoes De Novas Skills

python C:\Users\renat\skills\skill-sentinel\scripts\run_audit.py --recommend

#### Imported: Comparar Com Auditoria Anterior (Tendencias)

python C:\Users\renat\skills\skill-sentinel\scripts\run_audit.py --compare

#### Imported: Ver Historico De Auditorias

python C:\Users\renat\skills\skill-sentinel\scripts\run_audit.py --history

#### Imported: Descobrir Skills Disponiveis

python C:\Users\renat\skills\skill-sentinel\scripts\scanner.py

#### Imported: Ver Audit Log Do Sentinel

python C:\Users\renat\skills\skill-sentinel\scripts\governance.py

#### Imported: Verificar Banco De Dados

python C:\Users\renat\skills\skill-sentinel\scripts\db.py

Imported: 1. Qualidade De Codigo (Peso: 20%)

• Complexidade ciclomatica por funcao (limiar: 10)
• Tamanho de funcoes (limiar: 50 linhas)
• Tamanho de arquivos (limiar: 500 linhas)
• Cobertura de docstrings
• Padroes de error handling (bare except, broad except)

Imported: 2. Seguranca (Peso: 20%)

• Secrets hardcoded (tokens, passwords, API keys)
• SQL injection (f-strings em queries)
• URLs HTTP inseguras
• Tokens em logs
• Validacao de input

Imported: 3. Performance (Peso: 15%)

• Retry com backoff para APIs
• Timeouts configurados
• Reuso de conexoes HTTP
• N+1 queries
• Async/concorrencia

Imported: 4. Governanca (Peso: 15%)

• Nivel 0: Nenhuma
• Nivel 1: Action logging
• Nivel 2: Logging + rate limiting
• Nivel 3: Completa (+ confirmacoes 2-step)
• Nivel 4: Avancada (+ alertas e trends)

Imported: 5. Documentacao (Peso: 15%)

• SKILL.md com frontmatter (name, description, version)
• Trigger keywords (PT-BR e EN)
• Secoes obrigatorias e recomendadas
• Reference files

Imported: 6. Dependencias (Peso: 15%)

• requirements.txt presente
• Versoes pinadas
• Deps importadas vs listadas
• Deps listadas vs importadas

Imported: 7. Cross-Skill (Analise Global)

• Modulos duplicados entre skills
• Padroes de Database compartilhados
• Governanca inconsistente
• Oportunidades de extracao

Imported: Otimizacao De Custos

Alem das 7 dimensoes, o sentinel analisa impacto de custo:

• Tamanho do SKILL.md (tokens consumidos por ativacao)
• References grandes sem indice
• Output verboso dos scripts
• Ausencia de output JSON estruturado

Imported: Gap Analysis E Recomendacoes

O recommender identifica capacidades ausentes no ecossistema comparando com uma taxonomia de 20 categorias e gera templates de SKILL.md prontos para novas skills sugeridas.

Imported: Governanca Do Sentinel

O proprio sentinel pratica o que prega:

• Todas as auditorias sao registradas em action_log
• Historico de scores em score_history para tendencias
• Relatorios salvos em data/reports/

Imported: Formato Do Relatorio

O relatorio gerado em data/reports/ contem:

1. Resumo executivo (tabela de scores)
2. Tendencias (se houver auditoria anterior)
3. Findings por severidade (critico/alto/medio/baixo/info)
4. Analise por skill (detalhada)
5. Recomendacoes de novas skills
6. Plano de acao priorizado

Imported: Referencias

Para detalhes tecnicos, consultar:

• references/analysis_criteria.md - Rubricas de scoring
• references/security_patterns.md - Padroes de seguranca
• references/skill_template.md - Template para novas skills
• references/schema.md - Schema do banco de dados

Imported: Common Pitfalls

• Using this skill for tasks outside its domain expertise
• Applying recommendations without understanding your specific context
• Not providing enough project context for accurate analysis

Imported: Limitations

• Use this skill only when the task clearly matches the scope described above.
• Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
• Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.