Back to list
LandonSchropp

identifying-skill-gaps

by LandonSchropp

My personal toolkit for working with AI agents

0🍴 0📅 Jan 25, 2026

SKILL.md


name: identifying-skill-gaps description: Use when analyzing Claude Code conversation logs to find patterns in repeated user instructions that could become skills. Ask for date range first.

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

Score

Total Score

55/100

Based on repository quality metrics

SKILL.md

SKILL.mdファイルが含まれている

+20
LICENSE

ライセンスが設定されている

0/10
説明文

100文字以上の説明がある

0/10
人気

GitHub Stars 100以上

0/15
最近の活動

1ヶ月以内に更新

+10
フォーク

10回以上フォークされている

0/5
Issue管理

オープンIssueが50未満

+5
言語

プログラミング言語が設定されている

+5
タグ

1つ以上のタグが設定されている

+5

Reviews

💬

Reviews coming soon