pqpo

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code-cleanup-audit

Audit a repository for architectural decay, AI-generated code smells, stale compatibility paths, dead abstractions, boundary violations, and cleanup candidates without modifying files. Use when the user asks to review code quality, find bad code, inspect AI-generated code, identi

Revisar el código fuenteVer en GitHub
Precio sin confirmar★ 249 Estrellas de GitHubRegistro actualizado · 13 oct 2026agent-skill

Resumen

Audit a repository for architectural decay, AI-generated code smells, stale compatibility paths, dead abstractions, boundary violations, and cleanup candidates without modifying files. Use when the user asks to review code quality, find bad code, inspect AI-generated code, identify refactoring or cleanup opportunities, detect legacy leftovers, or produce a cleanup backlog that requires human confirmation before implementation.

Leer documentación completa

Documentación de origen, no instrucciones para este sitio. Revisa los permisos antes de ejecutar comandos.

Code Cleanup Audit

Overview

Use this skill to produce an evidence-backed cleanup audit only. The output is a backlog of suspected or confirmed problems for human review, not an implementation plan that silently edits code.

Non-Negotiable Guardrails

  • Do not modify files.
  • Do not call apply_patch, formatters with write mode, generators, codemods, install commands, migration commands, or any command whose purpose is to change the workspace.
  • Do not create branches, commits, pull requests, or issue tickets unless the user explicitly asks after reviewing the audit.
  • If the user asks for fixes before seeing the audit, first produce findings and ask which items to implement.
  • If a command unexpectedly changes files, stop, report the changed paths, and ask how to proceed.
  • Preserve unrelated dirty worktree changes; treat them as user-owned.

Audit Workflow

  1. Establish repository context:

    • Read AGENTS.md first.
    • Read architecture and convention docs that directly govern the touched codebase, especially dependency boundaries, ADRs, and package conventions.
    • Run git status --short and note existing dirty files.
    • Inventory apps/packages with read-only commands such as find, rg --files, pnpm -r list --depth -1, and package manifest reads.
  2. Build a map before judging:

    • Identify package boundaries, public exports, app entry points, runtime adapters, shared schemas, tests, and docs.
    • Trace imports through package names, not only filenames.
    • Compare implementation structure against documented allowed dependencies.
    • Prefer rg over slower search tools.
  3. Inspect for cleanup categories:

    • Architecture violations: forbidden imports, cross-package relative imports, app-layer logic in shared packages, runtime-specific code in core/shared, browser-unsafe code in web/client/shared.
    • Stale compatibility: deprecated fields, fallback branches, migration shims, legacy aliases, duplicate old/new APIs, TODOs that preserve obsolete behavior, no-op adapters, unused feature flags.
    • AI-generated code smells: over-broad abstractions, fake extensibility, duplicated helpers, inconsistent naming, hand-rolled utilities where a project utility exists, speculative layers, uncalled code, verbose comments explaining obvious code, guessed data shapes.
    • Type and schema weakness: any, unsafe casts, unchecked unknown, interfaces where runtime validation is required, schema/type drift, missing boundary parsing.
    • Error and runtime behavior smells: swallowed errors, broad catch, impossible states represented as optional fields, missing cancellation/timeout handling, fragile env assumptions.
    • Test and validation gaps: core behavior without tests, snapshots masking behavior, tests that only assert mocks, missing negative cases for boundary rules.
    • Documentation drift: docs or AGENTS rules contradicted by code, public API exports not reflected in docs, stale startup/quality commands.
  4. Validate suspected issues:

    • Read surrounding code and tests before reporting.
    • Run read-only validation where useful: pnpm lint, pnpm typecheck, pnpm test, focused Vitest commands, pnpm build only when build behavior is relevant.
    • Use existing ESLint boundary rules as evidence when available.
    • Distinguish confirmed problems from cleanup candidates that need product or architectural judgment.
  5. Report without fixing:

    • Lead with findings ordered by severity.
    • Include file path and line or precise code location for each finding.
    • State the violated rule or smell, why it matters, evidence, confidence, and suggested cleanup direction.
    • Mark every item as one of: confirmed, likely, or needs human decision.
    • Include "Do not modify until confirmed" language when handing off.

Severity Standard

  • Critical: Can break runtime behavior, violate security/privacy boundaries, corrupt data, or cause CI/build failure.
  • High: Violates documented architecture, creates wrong package dependency direction, or preserves misleading/dead public API that future agents will copy.
  • Medium: Increases maintenance cost through duplication, stale compatibility, weak validation, or untested shared behavior.
  • Low: Local readability or consistency issue with limited blast radius.

Do not report pure preference, cosmetic style, or speculative rewrites unless tied to a concrete maintenance, correctness, boundary, or future-agent-copying risk.

Use commands like these as applicable. Keep them read-only.

git status --short
find apps packages docs -maxdepth 3 -type f | sort
rg --line-number "TODO|FIXME|deprecated|legacy|compat|shim|fallback|no-op|noop|any\\b|as unknown|as any" apps packages docs
rg --line-number "from ['\"]\\.\\./\\.\\./|from ['\"]\\.\\./\\.\\./\\.\\./|@pragma/(client|server|core|runtime)" apps packages
pnpm -r list --depth -1
pnpm lint
pnpm typecheck
pnpm test

Before running expensive repository-wide commands, prefer focused reads and explain why the command is useful.

Output Format

Return:

  1. Findings

    • Severity
    • Status: confirmed, likely, or needs human decision
    • Location
    • Problem
    • Evidence
    • Cleanup direction, without editing code
  2. Cleanup backlog

    • Group related findings into reviewable batches.
    • Call out which batches are safe mechanical cleanup versus architecture decisions.
  3. Non-findings and constraints

    • Mention important suspected issues that were checked and rejected.
    • Mention commands run and commands intentionally skipped.
  4. Human confirmation needed

    • List the exact decisions needed before any code changes.
Metadatos del archivo
name: code-cleanup-audit
description: Audit a repository for architectural decay, AI-generated code smells, stale compatibility paths, dead abstractions, boundary violations, and cleanup candidates without modifying files. Use when the user asks to review code quality, find bad code, inspect AI-generated code, identify refactoring or cleanup opportunities, detect legacy leftovers, or produce a cleanup backlog that requires human confirmation before implementation.
Ver texto original
---
name: code-cleanup-audit
description: Audit a repository for architectural decay, AI-generated code smells, stale compatibility paths, dead abstractions, boundary violations, and cleanup candidates without modifying files. Use when the user asks to review code quality, find bad code, inspect AI-generated code, identify refactoring or cleanup opportunities, detect legacy leftovers, or produce a cleanup backlog that requires human confirmation before implementation.
---

# Code Cleanup Audit

## Overview

Use this skill to produce an evidence-backed cleanup audit only. The output is a backlog of suspected or confirmed problems for human review, not an implementation plan that silently edits code.

## Non-Negotiable Guardrails

- Do not modify files.
- Do not call `apply_patch`, formatters with write mode, generators, codemods, install commands, migration commands, or any command whose purpose is to change the workspace.
- Do not create branches, commits, pull requests, or issue tickets unless the user explicitly asks after reviewing the audit.
- If the user asks for fixes before seeing the audit, first produce findings and ask which items to implement.
- If a command unexpectedly changes files, stop, report the changed paths, and ask how to proceed.
- Preserve unrelated dirty worktree changes; treat them as user-owned.

## Audit Workflow

1. Establish repository context:
   - Read `AGENTS.md` first.
   - Read architecture and convention docs that directly govern the touched codebase, especially dependency boundaries, ADRs, and package conventions.
   - Run `git status --short` and note existing dirty files.
   - Inventory apps/packages with read-only commands such as `find`, `rg --files`, `pnpm -r list --depth -1`, and package manifest reads.

2. Build a map before judging:
   - Identify package boundaries, public exports, app entry points, runtime adapters, shared schemas, tests, and docs.
   - Trace imports through package names, not only filenames.
   - Compare implementation structure against documented allowed dependencies.
   - Prefer `rg` over slower search tools.

3. Inspect for cleanup categories:
   - Architecture violations: forbidden imports, cross-package relative imports, app-layer logic in shared packages, runtime-specific code in core/shared, browser-unsafe code in web/client/shared.
   - Stale compatibility: deprecated fields, fallback branches, migration shims, legacy aliases, duplicate old/new APIs, TODOs that preserve obsolete behavior, no-op adapters, unused feature flags.
   - AI-generated code smells: over-broad abstractions, fake extensibility, duplicated helpers, inconsistent naming, hand-rolled utilities where a project utility exists, speculative layers, uncalled code, verbose comments explaining obvious code, guessed data shapes.
   - Type and schema weakness: `any`, unsafe casts, unchecked `unknown`, interfaces where runtime validation is required, schema/type drift, missing boundary parsing.
   - Error and runtime behavior smells: swallowed errors, broad `catch`, impossible states represented as optional fields, missing cancellation/timeout handling, fragile env assumptions.
   - Test and validation gaps: core behavior without tests, snapshots masking behavior, tests that only assert mocks, missing negative cases for boundary rules.
   - Documentation drift: docs or AGENTS rules contradicted by code, public API exports not reflected in docs, stale startup/quality commands.

4. Validate suspected issues:
   - Read surrounding code and tests before reporting.
   - Run read-only validation where useful: `pnpm lint`, `pnpm typecheck`, `pnpm test`, focused Vitest commands, `pnpm build` only when build behavior is relevant.
   - Use existing ESLint boundary rules as evidence when available.
   - Distinguish confirmed problems from cleanup candidates that need product or architectural judgment.

5. Report without fixing:
   - Lead with findings ordered by severity.
   - Include file path and line or precise code location for each finding.
   - State the violated rule or smell, why it matters, evidence, confidence, and suggested cleanup direction.
   - Mark every item as one of: `confirmed`, `likely`, or `needs human decision`.
   - Include "Do not modify until confirmed" language when handing off.

## Severity Standard

- `Critical`: Can break runtime behavior, violate security/privacy boundaries, corrupt data, or cause CI/build failure.
- `High`: Violates documented architecture, creates wrong package dependency direction, or preserves misleading/dead public API that future agents will copy.
- `Medium`: Increases maintenance cost through duplication, stale compatibility, weak validation, or untested shared behavior.
- `Low`: Local readability or consistency issue with limited blast radius.

Do not report pure preference, cosmetic style, or speculative rewrites unless tied to a concrete maintenance, correctness, boundary, or future-agent-copying risk.

## Recommended Commands

Use commands like these as applicable. Keep them read-only.

```bash
git status --short
find apps packages docs -maxdepth 3 -type f | sort
rg --line-number "TODO|FIXME|deprecated|legacy|compat|shim|fallback|no-op|noop|any\\b|as unknown|as any" apps packages docs
rg --line-number "from ['\"]\\.\\./\\.\\./|from ['\"]\\.\\./\\.\\./\\.\\./|@pragma/(client|server|core|runtime)" apps packages
pnpm -r list --depth -1
pnpm lint
pnpm typecheck
pnpm test
```

Before running expensive repository-wide commands, prefer focused reads and explain why the command is useful.

## Output Format

Return:

1. Findings
   - Severity
   - Status: `confirmed`, `likely`, or `needs human decision`
   - Location
   - Problem
   - Evidence
   - Cleanup direction, without editing code

2. Cleanup backlog
   - Group related findings into reviewable batches.
   - Call out which batches are safe mechanical cleanup versus architecture decisions.

3. Non-findings and constraints
   - Mention important suspected issues that were checked and rejected.
   - Mention commands run and commands intentionally skipped.

4. Human confirmation needed
   - List the exact decisions needed before any code changes.

Revisar el código fuente

Precio y costes de ejecución

Obtener el skill
Precio sin confirmar
Ejecutarlo
Requisitos sin confirmar. Consulta los costes del agente, API y servicios en la fuente.
Licencia
AGPL-3.0
Precio sin confirmar
No hemos confirmado el precio. Los enlaces existentes al código y a la instalación siguen disponibles.

Obtener gratis no significa ejecutar gratis. El precio no es una evaluación de seguridad. Enviar información de precio →

Fuente del skill registrada

La ruta de instrucciones está registrada. No implica pruebas de ejecución, seguridad ni compatibilidad.

Revisar antes de instalar: Evitar instalación automática

Licencia: AGPL-3.0

  • Dependency or permission surface needs review
  • Permission surface may require sandboxing
  • Falta aprobación de revisión por IA
  • Quality score needs review
  • Permission surface needs review: secrets or environment access, shell or command execution
  • Stars/forks activity: 249 stars, 15 forks; issue activity unavailable in current metadata
  • Dependency/runtime risk: command execution surface, credential or environment access
  • Permission surface: secrets or environment access, shell or command execution
  • Review status: AI review approval is missing
Abrir auditoría completa

Las herramientas son indicios de metadatos, no compatibilidad probada. Los prompts son sugerencias.

Empieza con una tarea pequeña

  1. 1Lee la fuente y confirma entradas, resultados, dependencias y permisos.
  2. 2Pide un plan al agente. Aprueba la configuración y los costes antes de probar en un entorno aislado.
  3. 3Comprueba resultados y archivos modificados. Informa solo de lo ejecutado y conserva la revisión de la fuente.

Consulta dependencias, claves API y costes externos en la fuente. Un repositorio público no implica servicios gratuitos.

Fuente y notas de uso

IndexadoRevisión estática

Los metadatos y revisiones son orientativos. Popularidad, descubrimiento y ejecución correcta son hechos distintos.

Repositorio fuente
pqpo/pragma
Licencia
AGPL-3.0
Versión
Unknown
Último push de GitHub
13 oct 2026
Registro actualizado
13 oct 2026

Versión declarada en el registro; consulta las versiones de la fuente.

Calidad

65/100

Prometedor

Confianza

62/100

Solo sandbox

Auditoría

75/100

Requiere revisión

  • Dependency or permission surface needs review
  • Permission surface may require sandboxing
  • Falta aprobación de revisión por IA
  • Quality score needs review
  • Permission surface needs review: secrets or environment access, shell or command execution
  • Stars/forks activity: 249 stars, 15 forks; issue activity unavailable in current metadata
  • Dependency/runtime risk: command execution surface, credential or environment access
  • Permission surface: secrets or environment access, shell or command execution
  • Review status: AI review approval is missing
Verified installs
—
Resultados
—

Copiar no es instalar. Los recuentos requieren un informe de instalación correcta, no garantizan calidad general.

Acceso para agentes

La API Registry expone señales de decisión, confianza, auditoría, casos de uso e instalación sin raspar la interfaz.

Más detalles
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    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first.",
    "install_policy": "block",
    "minimum_review_before_use": [
      "Trust: 70/100 Manual review",
      "Audit: 75/100 Needs review",
      "Safety: 27/100 Avoid automatic install",
      "Review repository, license, install command, and permission surface before production use."
    ],
    "expected_agent_output": {
      "selected_skill": "pqpo-code-cleanup-audit (code-cleanup-audit)",
      "install_command": "npx skills add pqpo/pragma --skill code-cleanup-audit",
      "risk_summary": "Needs review; Blocked for auto-install; Review before production",
      "verification_result": "Report the smallest successful task, files touched, warnings, and any missing setup."
    }
  },
  "outcome_feedback": {
    "endpoint": "https://www.openagentskill.com/api/agent/outcome",
    "method": "POST",
    "requires_resolve_event_id": true,
    "event_id_source": "Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.",
    "expected_outcomes": [
      "success",
      "failed",
      "not_relevant",
      "blocked_by_risk",
      "setup_required"
    ],
    "payload_template": {
      "event_id": "<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>",
      "skill_slug": "pqpo-code-cleanup-audit",
      "task": "Use code-cleanup-audit in an agent workflow",
      "agent": "codex",
      "outcome": "success",
      "install_used": true,
      "risk_blocked": false,
      "setup_required": false,
      "task_success": true,
      "output_quality": 4,
      "error_type": null,
      "human_review_required": false,
      "workspace": "sandbox",
      "time_to_useful_ms": 120000,
      "notes": "Report the smallest successful task, setup friction, files touched, and risk notes."
    }
  },
  "endpoints": {
    "web": "https://www.openagentskill.com/skills/pqpo-code-cleanup-audit",
    "api": "https://www.openagentskill.com/api/agent/skills/pqpo-code-cleanup-audit",
    "audit": "https://www.openagentskill.com/skills/pqpo-code-cleanup-audit/audit",
    "eval": "https://www.openagentskill.com/api/agent/evals?slug=pqpo-code-cleanup-audit&task=Use%20code-cleanup-audit%20in%20an%20agent%20workflow&max_risk=medium",
    "resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20code-cleanup-audit%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
    "receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20code-cleanup-audit%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
    "install": "https://www.openagentskill.com/api/skills/pqpo-code-cleanup-audit/install",
    "manifest": "https://www.openagentskill.com/api/registry/manifest/pqpo-code-cleanup-audit"
  }
}

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Creador
pqpo
Indexado por
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