Identifying Skill Gaps

Analyze Claude Code conversation logs to identify areas where the user repeatedly gives similar instructions that could be turned into skills.

Step 1: Ask for Date Range

FIRST: Ask the user what date range they want to analyze.

Example: "What date range would you like me to analyze? (e.g., December 1-15, 2024)"

Step 2: Extract User Messages

Claude Code stores conversation logs in

~/.claude/projects/

as JSONL files.

NEVER assume logs aren't accessible. They ARE stored locally.

Run the extraction script with the date range:

scripts/extract-user-messages.ts --after YYYY-MM-DD

This filters out tool calls, assistant responses, and metadata—keeping only what the user said.

Step 3: Analyze for Patterns

Analyze the output and apply the waste analysis framework from references/wastes.md.

1. Apply each lens to identify waste patterns
2. Look for repetition across conversations - the same waste appearing multiple times signals high-value skill opportunities
3. Quantify the waste - count how many messages/characters users spend on each pattern
4. Prioritize by frequency and cost - repeated, lengthy wastes are the best skill candidates

What counts as a pattern: The user giving similar instructions in 3+ separate conversations.

Focus on identifying waste where users repeatedly spend conversation time on things that could be eliminated by a skill.

Step 4: Output Prioritized List

Create a markdown list with:

## Potential Skills

### 1. [Skill Name] - HIGH PRIORITY

**Frequency**: Found in [X] conversations
**Rationale**: [Why this would be useful]
**Example instructions**:

- "[Quote from conversation]"
- "[Another quote]"

### 2. [Skill Name] - MEDIUM PRIORITY

...

Priority levels:

• HIGH: 5+ occurrences, affects workflow significantly
• MEDIUM: 3-4 occurrences, clear pattern
• LOW: 2 occurrences, worth noting