Skill

optimizing-claude-code

Audits repositories for Claude Code readiness by analyzing CLAUDE.md quality, settings, project organization, MCP configs, and skills; suggests prioritized improvements for agentic work.

Python

Bash

Git

code-quality

developer-tools

npx claudepluginhub codealive-ai/agents-reflection-skills

Tool Access

This skill uses the workspace's default tool permissions.

Preview

**Default**: Audit-only. Present findings and await approval before modifying files.

Supporting Assets

references/best-practices.mdreferences/checklist.mdreferences/rubric.mdscripts/audit_repo.py

SKILL.md

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Stats

Parent Repo Stars31

Parent Repo Forks0

Last CommitFeb 15, 2026

Used By3 plugins

Actions

View Source View Plugin View on GitHub View README

Help us improve

Share bugs, ideas, or general feedback.

Optimizing Claude Code

Default: Audit-only. Present findings and await approval before modifying files.

Workflow

1. Run Audit

Execute from repo root:

python scripts/audit_repo.py --root . --include-user-scope

Analyzes:

Repository scale and directory hotspots
CLAUDE.md files (discovery, quality, @imports)
Settings (user/project/local scopes)
MCP configurations
Skills and subagents

2. Generate Report

Structure output as:

Executive Summary (5 bullets max)

Readiness assessment
Key strengths
Critical gaps
Priority actions

Repository Profile

File count and scale (Small/Medium/Large)
Primary language/framework

Memory Files Assessment

Per-file metrics
@import validation
Content quality
Staleness indicators

Settings & Configuration

Permissions analysis
MCP server inventory
Skills/subagents discovered

Issues by Priority

P0: Blocks agentic work
P1: High impact
P2: Nice-to-have

Recommendations

Specific suggested edits
Reference best practices
Do NOT apply without approval

3. Apply Changes (If Requested)

When asked to implement:

Confirm which changes
Edit incrementally
Show diffs
Re-audit to verify

Large Repository Guidance

When file count exceeds 3000, include scaling recommendations:

Vanilla context becomes unreliable at scale
Consider context engines or retrieval layers
Strategic CLAUDE.md placement becomes critical
Focus on navigation aids over exhaustive documentation

Reference Files

best-practices.md: Environment setup, CLAUDE.md structure, prompting patterns, workflows, safety
rubric.md: CLAUDE.md scoring criteria (0-16 scale), anti-patterns, templates
checklist.md: Step-by-step audit workflow, prioritization guide