Plugin Audit
SkillCloud & infraLets your agent audit how well the vercel-plugin injects skills by analyzing real Claude Code session logs.
Then ask your AI: use the Plugin Audit skill
Details
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
Account requirements not reviewed. Check the skill instructions before use; Ahel provides instructions and does not run this skill.
No other account needed.
Add it as a step in a pipeline you build on Ahel, or connect Ahel to Claude, ChatGPT, Cursor, Claude Code or Codex and ask your AI to use it.
About this skill
Audit vercel-plugin performance on real-world projects. Extracts tool calls from Claude Code conversation logs, tests hook matching against actual inputs, identifies pattern coverage gaps, and checks plugin cache staleness. Use when asked to audit, test, or investigate plugin skill injection on a re
What this skill tells your AI
The instructions your AI receives, as published by vercel/vercel-plugin in .claude/skills/plugin-audit/SKILL.md and read by Ahel’s review.
Audit how well vercel-plugin skill injection performs on real-world Claude Code sessions.
Workflow
1. Locate conversation logs
Find JSONL conversation logs for a target project:
ls -lt ~/.claude/projects/-Users-*-<project-name>/*.jsonl
The path uses the project's absolute path with slashes replaced by hyphens and a leading hyphen.
2. Extract tool calls
Parse the JSONL log to extract all tool_use entries. Each line is a JSON object with message.content[] containing type: "tool_use" blocks. Extract name and input fields. Group by tool type (Bash, Read, Write, Edit).
3. Test hook matching
Use the exported pipeline functions directly — do NOT shell out to the hook script for each test. Import from the hooks directory:
import { loadSkills, matchSkills } from "./hooks/pretooluse-skill-inject.mjs";
import { createLogger } from "./hooks/logger.mjs";
Call loadSkills() once, then matchSkills(toolName, toolInput, compiledSkills) for each tool call. This is fast and gives exact match results.
4. Identify gaps
Compare matched skills against what SHOULD have matched based on the project's technology stack. Common gap categories:
- Path pattern gaps: Files that should trigger a skill but don't (e.g.,
src/db/schema.tsnot matchingvercel-storage) - Bash pattern gaps: Commands that should trigger but don't (e.g., missing package manager variants)
- Dedup masking: Skills that matched but were deduped before injection
- Budget/cap drops: Skills matched but dropped by the 12KB budget or 3-skill ceiling
5. Check plugin cache staleness
Compare the installed plugin cache against the dev version:
# Cache location
~/.claude/plugins/cache/vercel-labs-vercel-plugin/vercel-plugin/<version>/
# Compare skill content
diff <(grep 'pattern' skills/<skill>/SKILL.md) <(grep 'pattern' ~/.claude/plugins/cache/.../skills/<skill>/SKILL.md)
Check ~/.claude/plugins/installed_plugins.json for version and git SHA.
Report Format
Produce a structured report with:
- Session summary: Project, date, tool call count, model
- Match matrix: Table of tool calls × matched skills (with match type)
- Coverage gaps: Unmatched tool calls that should have matched, with suggested pattern additions
- Dedup timeline: Order of skill injections and what got deduped
- Cache status: Whether installed version matches dev, with specific diffs
References
Signals
- GitHub stars
- 301
- Forks
- 64
- Last commit
- Oct 2026
Advanced
- Item type
- skill
- Key
plugin-audit-vercel- Source
- github.com/vercel/vercel-plugin
github.com/vercel/vercel-plugin
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