review-claudemd

Review CLAUDE.md from conversation history

Analyze recent conversations to improve both global (~/.claude/CLAUDE.md) and local (project) CLAUDE.md files.

Step 1: Find conversation history

The project's conversation history is in ~/.claude/projects/. The folder name is the project path with slashes replaced by dashes.

# Find the project folder (replace / with -)
PROJECT_PATH=$(pwd | sed 's|/|-|g' | sed 's|^-||')
CONVO_DIR=~/.claude/projects/-${PROJECT_PATH}
ls -lt "$CONVO_DIR"/*.jsonl | head -20

Step 2: Extract recent conversations

Extract the 15-20 most recent conversations (excluding the current one) to a temp directory:

SCRATCH=/tmp/claudemd-review-$(date +%s)
mkdir -p "$SCRATCH"

for f in $(ls -t "$CONVO_DIR"/*.jsonl | head -20); do
  basename=$(basename "$f" .jsonl)
  # Skip current conversation if known
  cat "$f" | jq -r '
    if .type == "user" then
      "USER: " + (.message.content // "")
    elif .type == "assistant" then
      "ASSISTANT: " + ((.message.content // []) | map(select(.type == "text") | .text) | join("\n"))
    else
      empty
    end
  ' 2>/dev/null | grep -v "^ASSISTANT: $" > "$SCRATCH/${basename}.txt"
done

ls -lhS "$SCRATCH"

Step 3: Spin up subagents

Launch parallel subagents to analyze conversations. Each agent should read:

• Global CLAUDE.md: ~/.claude/CLAUDE.md
• Local CLAUDE.md: ./CLAUDE.md (if exists)
• Batch of conversation files

Give each agent this prompt template:

Read:
1. Global CLAUDE.md: ~/.claude/CLAUDE.md
2. Local CLAUDE.md: [project]/CLAUDE.md
3. Conversations: [list of files]

Analyze the conversations against BOTH CLAUDE.md files. Find:
1. Instructions that exist but were violated (need reinforcement or rewording)
2. Patterns that should be added to LOCAL CLAUDE.md (project-specific)
3. Patterns that should be added to GLOBAL CLAUDE.md (applies everywhere)
4. Anything in either file that seems outdated or unnecessary

Be specific. Output bullet points only.

Batch conversations by size:

• Large (>100KB): 1-2 per agent
• Medium (10-100KB): 3-5 per agent
• Small (<10KB): 5-10 per agent

Step 4: Aggregate findings

Combine results from all agents into a summary with these sections: