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documentation-audit

This skill should be used when verifying documentation claims against codebase reality. Triggers on "audit docs", "verify documentation", "check docs", "docs accurate", "documentation drift", "before release", "after refactor", "docs don't match". Uses two-pass extraction with pattern expansion for comprehensive detection.

aiskillstore/marketplace

インストール方法を見る

含まれるファイル（4）

SKILL.md3.5 KB
checklist.md3.2 KB
extraction-patterns.md3.8 KB
skill-report.json31.1 KB

SKILL.md（原文）

インストールする前に、エージェントに与えられる指示の中身を確認できます。

Documentation Audit

Systematically verify claims in documentation against the actual codebase using a two-pass approach.

Overview

Core principle: Low recall is worse than false positives—missed claims stay invisible.

Two-pass process:

Pass 1: Extract and verify claims directly from docs
Pass 2A: Expand patterns from false claims to find similar issues
Pass 2B: Compare codebase inventory vs documented items (gap detection)

Quick Start

Identify target docs (user-facing only, skip plans/, audits/)
Note current git commit for report header
Run Pass 1 extraction using parallel agents (one per doc)
Analyze false claims for patterns
Run Pass 2 expansion searches
Generate docs/audits/AUDIT_REPORT_YYYY-MM-DD.md

Claim Types

Type	Example	Verification
`file_ref`	`scripts/foo.py`	File exists?
`config_default`	"defaults to 'AI Radio'"	Check schema/code
`env_var`	`STATION_NAME`	In .env.example + code?
`cli_command`	`--normalize` flag	Script supports it?
`behavior`	"runs every 2 minutes"	Check timers/code

Verification confidence:

Tier 1 (auto): file_ref, config_default, env_var, cli_command
Tier 2 (semi-auto): symbol_ref, version_req
Tier 3 (human review): behavior, constraint

Pass 2 Pattern Expansion

After Pass 1, analyze false claims and search for similar patterns:

Dead script found: diagnose_track_selection.py
  → Search: all script references → Found 8 more dead scripts

Wrong interval: "every 10 seconds"
  → Search: "every \d+ (seconds?|minutes?)" → Found 3 more

Wrong service name: ai-radio-break-gen.service
  → Search: service/timer names → Found naming inconsistencies

Common patterns to always check:

Dead scripts: scripts/*.py references
Timer intervals: every \d+ (seconds?|minutes?)
Service names: ai-radio-*.service, *.timer
Config vars: RADIO_* environment variables
CLI flags: --flag patterns in bash blocks

Output Format

Generate docs/audits/AUDIT_REPORT_YYYY-MM-DD.md:

# Documentation Audit Report
Generated: YYYY-MM-DD | Commit: abc123

## Executive Summary
| Metric | Count |
|--------|-------|
| Documents scanned | 12 |
| Claims verified | ~180 |
| Verified TRUE | ~145 (81%) |
| **Verified FALSE** | **31 (17%)** |

## False Claims Requiring Fixes
### CONFIGURATION.md
| Line | Claim | Reality | Fix |
|------|-------|---------|-----|
| 135 | `claude-sonnet-4-5` | Actual: `claude-3-5-sonnet-latest` | Update |

## Pattern Summary
| Pattern | Count | Root Cause |
|---------|-------|------------|
| Dead scripts | 9 | Scripts deleted, docs not updated |

## Human Review Queue
- [ ] Line 436: behavior claim needs verification

Detailed References

For execution checklist and anti-patterns: checklist.md For claim extraction patterns: extraction-patterns.md

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同じリポジトリのスキル

概要と使いどころ

acquisition-policy-workflow

無料

Trigger for: explaining current FAR, DFARS, or agency-supplement text; determining documented acquisition-policy status for an agency and FAR part; comparing codified text, RFO model text, and agency deviations; tracing acquisition rulemaking; finding procurement comment periods; analyzing public comments; refreshing prior policy analysis; or producing an Acquisition Policy Impact Brief. Use published federal sources and supplied policy documents without making legal or procurement-specific applicability determinations. Do not use for clause selection, market research execution, opportunities, pricing, grants, or cooperative agreements.

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