context-audit

📁 hjewkes/agent-skills 📅 11 days ago
10
总安装量
10
周安装量
#29463
全站排名
安装命令
npx skills add https://github.com/hjewkes/agent-skills --skill context-audit

Agent 安装分布

opencode 10
claude-code 10
cursor 10
gemini-cli 9
github-copilot 9
codex 9

Skill 文档

Context Audit

Analyzes what’s consuming your context window and recommends optimizations. Three audit modes can run independently or together.

Quick Start

  • /context-audit or “audit my context” — runs all three audits
  • “static audit” or “context inventory” — file inventory only
  • “session analysis” — JSONL token parsing only
  • “context score” — scoring and recommendations only

Audit Modes

1. Static Inventory

Run scripts/audit-context to automate the static inventory. Supports --json for structured output, --flagged for problems only, --top N for largest items.

The script scans all context-contributing sources:

  • Skills (SKILL.md, rules/, references/)
  • CLAUDE.md files (global + project + subdirectories)
  • Auto-memory files (~/.claude/projects/*/memory/*.md)
  • Plugins with per-plugin tool count estimates
  • MCP servers

Thresholds: Flag SKILL.md > 500 words, any rules/ directory, CLAUDE.md > 2KB, 5+ MCP servers, plugins with 10+ tools.

2. Live Context Window (/context)

After running the static inventory, tell the user about the built-in /context command:

  • It shows real-time token usage: current tokens, max capacity, and percentage used
  • It breaks down what’s in the context window right now (system prompt, conversation, tool results)
  • Recommend the user run /context themselves for live token data — it complements the static inventory
  • If the user shares /context output, incorporate it into the scoring (Session Efficiency component)

3. Session Token Analysis

Parse the current session’s JSONL to track context growth:

  1. Find the active session JSONL in ~/.claude/projects/
  2. Extract usage.input_tokens and usage.cache_read_input_tokens per turn
  3. Identify the 5 largest token jumps between consecutive turns
  4. Correlate jumps with tool calls from preceding turns
  5. Report what triggered each spike

Read references/audit-procedures.md for the full JSONL parsing procedure.

4. Recommendations & Scoring

Generate actionable recommendations and a letter grade (A-F, 0-100).

Scoring weights:

Component Weight
Skills health 30%
CLAUDE.md health 25%
Plugin/MCP health 25%
Session efficiency 20%

Output Format

Produce a single report with sections:

  1. Static Inventory table (from audit-context script output)
  2. /context note — remind the user to run /context for live token breakdown
  3. Session Analysis (if JSONL available)
  4. Top Recommendations
  5. Score

Read references/audit-procedures.md for detailed procedures, scoring rubric, and recommendation rules.