Registry indexed

code-cleanup-audit

Price unconfirmed★ 245 GitHub starsRegistry updated · Oct 5, 2026agent-skill

Overview

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.

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Source documentation, not instructions for this website. Review permissions before running any commands.

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

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.
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.
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.
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.
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.

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:

Findings
- Severity
- Status: confirmed, likely, or needs human decision
- Location
- Problem
- Evidence
- Cleanup direction, without editing code
Cleanup backlog
- Group related findings into reviewable batches.
- Call out which batches are safe mechanical cleanup versus architecture decisions.
Non-findings and constraints
- Mention important suspected issues that were checked and rejected.
- Mention commands run and commands intentionally skipped.
Human confirmation needed
- List the exact decisions needed before any code changes.

View source ↗

File metadata

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.

View original text

---
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.

Review the source

Price & running costs

Get the skill: Price unconfirmed
Run it: Requirements have not been confirmed. Check the source for agent, API and service charges.
License: AGPL-3.0
Price unconfirmed: We have not confirmed a price for this skill. Existing source and install links remain available.

Free to get does not mean free to run. Price labels are not safety ratings. Submit pricing information →

Skill source recorded

Skill instructions are recorded. This is not a runtime test, safety guarantee or compatibility certification.

Review before install: Avoid automatic install

License: AGPL-3.0

Dependency or permission surface needs review
Permission surface may require sandboxing
AI review approval is missing
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
Stars/forks activity: 245 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

Open full audit

Listed tools are metadata hints, not tested compatibility. Agent prompts are suggested handoffs.

Start with one small task

1Read the source. Confirm the input, expected output, dependencies and permissions.
2Ask your agent for a plan. Approve setup and any costs before running a small isolated test.
3Check the output and changed files. Report only what actually ran; keep the source revision for reproduction.

Check the source for dependencies, API keys and third-party costs. A public repository does not mean every service is free.

Source & usage notes

IndexedStatic Checked

Repository metadata and review signals are advisory. Popularity, source discovery and successful execution are different facts.

Source repository: pqpo/pragma
License: AGPL-3.0
Version: Unknown
Last GitHub push: Oct 5, 2026
Registry updated: Oct 5, 2026
Instruction path: .codex/skills/code-cleanup-audit/SKILL.md @ 1d55c32faa06

Version reported in registry metadata; check source releases before relying on it.

Quality

65/100

Promising

Trust

62/100

Sandbox only

Audit

75/100

Needs review

Open full audit View eval report

Dependency or permission surface needs review
Permission surface may require sandboxing
AI review approval is missing
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
Stars/forks activity: 245 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: —
Outcomes: —

Copies are not installs. Installation counts require a reported successful installation; they are not a blanket quality guarantee.

Agent access

This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.

Open install API LLM text format Open manifest Auto-resolve Plan

More details

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Creator: pqpo
Source: pqpo/pragma
Indexed by: OpenAgentSkill community index

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pqpo

Registry indexed

code-cleanup-audit

Review the source View on GitHub

Price unconfirmed★ 245 GitHub starsRegistry updated · Oct 5, 2026agent-skill

Overview

Read full documentation

Source documentation, not instructions for this website. Review permissions before running any commands.

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

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.
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.
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.
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.
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.

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:

Findings
- Severity
- Status: confirmed, likely, or needs human decision
- Location
- Problem
- Evidence
- Cleanup direction, without editing code
Cleanup backlog
- Group related findings into reviewable batches.
- Call out which batches are safe mechanical cleanup versus architecture decisions.
Non-findings and constraints
- Mention important suspected issues that were checked and rejected.
- Mention commands run and commands intentionally skipped.
Human confirmation needed
- List the exact decisions needed before any code changes.

View source ↗

File metadata

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.

View original text

---
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.

Review the source

Price & running costs

Get the skill: Price unconfirmed
Run it: Requirements have not been confirmed. Check the source for agent, API and service charges.
License: AGPL-3.0
Price unconfirmed: We have not confirmed a price for this skill. Existing source and install links remain available.

Free to get does not mean free to run. Price labels are not safety ratings. Submit pricing information →

Skill source recorded

Skill instructions are recorded. This is not a runtime test, safety guarantee or compatibility certification.

Review before install: Avoid automatic install

License: AGPL-3.0

Dependency or permission surface needs review
Permission surface may require sandboxing
AI review approval is missing
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
Stars/forks activity: 245 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

Open full audit

Listed tools are metadata hints, not tested compatibility. Agent prompts are suggested handoffs.

Start with one small task

1Read the source. Confirm the input, expected output, dependencies and permissions.
2Ask your agent for a plan. Approve setup and any costs before running a small isolated test.
3Check the output and changed files. Report only what actually ran; keep the source revision for reproduction.

Check the source for dependencies, API keys and third-party costs. A public repository does not mean every service is free.

Source & usage notes

IndexedStatic Checked

Repository metadata and review signals are advisory. Popularity, source discovery and successful execution are different facts.

Source repository: pqpo/pragma
License: AGPL-3.0
Version: Unknown
Last GitHub push: Oct 5, 2026
Registry updated: Oct 5, 2026
Instruction path: .codex/skills/code-cleanup-audit/SKILL.md @ 1d55c32faa06

Version reported in registry metadata; check source releases before relying on it.

Quality

65/100

Promising

Trust

62/100

Sandbox only

Audit

75/100

Needs review

Open full audit View eval report

Dependency or permission surface needs review
Permission surface may require sandboxing
AI review approval is missing
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
Stars/forks activity: 245 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: —
Outcomes: —

Copies are not installs. Installation counts require a reported successful installation; they are not a blanket quality guarantee.

Agent access

This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.

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More details

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      "successRate": null,
      "recentSuccessRate": null,
      "recentFailureRate": null,
      "riskBlocked": 0,
      "setupRequired": 0,
      "notRelevant": 0,
      "avgOutputQuality": null,
      "avgTimeToUsefulMs": null,
      "productionOutcomes": 0,
      "humanReviewRequired": 0,
      "uniqueAgents": 0,
      "lastOutcomeAt": null
    },
    "signals": [],
    "penalties": [
      "No real agent outcome evidence yet"
    ]
  },
  "audit": {
    "score": 75,
    "risk_level": "needs_review",
    "risk_label": "Needs review",
    "warnings": [
      "Dependency or permission surface needs review",
      "Permission surface may require sandboxing",
      "AI review approval is missing",
      "Quality score needs review",
      "Permission surface needs review: secrets or environment access, shell or command execution",
      "Stars/forks activity: 245 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"
    ]
  },
  "safety_gate": {
    "tier": "blocked",
    "label": "Blocked for auto-install",
    "auto_install_policy": "block",
    "auto_install_allowed": false,
    "human_review_required": true,
    "blocked": true,
    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first."
  },
  "quality": {
    "score": 65,
    "label": "Promising"
  },
  "supply": {
    "track": "Coding and developer agents",
    "scenario": "Coding agents",
    "maintenance": "1d since push",
    "risk": "Needs review"
  },
  "alternative_skills": [],
  "do_not_use_when": [
    "teams that need a vendor-supported SLA",
    "high-compliance environments without internal security review",
    "No major risk signals from current metadata",
    "High-risk permission hints: Shell or command execution, Secrets or environment access",
    "Dependency or permission surface needs review",
    "Permission surface may require sandboxing",
    "AI review approval is missing",
    "Quality score needs review"
  ],
  "agent_contract": {
    "task_input": "Use code-cleanup-audit in an agent workflow",
    "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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Creator: pqpo
Source: pqpo/pragma
Indexed by: OpenAgentSkill community index

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Overview

Code Cleanup Audit

Overview

Non-Negotiable Guardrails

Audit Workflow

Severity Standard

Recommended Commands

Output Format

Review the source

Price & running costs

Start with one small task

Source & usage notes

Agent access

Related skills

For the creator

Registry indexed

Claim this skill listing

Add the evidence badges to your README

Community signal

Overview

Code Cleanup Audit

Overview

Non-Negotiable Guardrails

Audit Workflow

Severity Standard

Recommended Commands

Output Format

Review the source

Price & running costs

Start with one small task

Source & usage notes

Agent access

Related skills

For the creator

Registry indexed

Claim this skill listing

Add the evidence badges to your README

Community signal