Agent skill

analyze-tools

Analyze which tools Claude uses most frequently. Use when user says "what tools do I use most", "tool usage stats", "analyze my claude tools", or "which tools does claude use".

View SKILL.md on GitHub Repository
Stars 163
Forks 31

Install this agent skill to your Project

npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/data/vibe-check-analyze-tools

SKILL.md

Analyze Claude Tool Usage

Purpose: Analyze which tools Claude uses most frequently in conversations

Database Location

To find the database location, run:

bash
vibe-check status

The default location is: ~/.vibe-check/vibe_check.db

Note: If the status shows no PID, vibe-check is not running and the database may be stale. Start it with vibe-check start.

Important: Use Read-Only Mode

To avoid database locks when the monitor is running, always use read-only mode:

bash
sqlite3 "file:/path/to/vibe_check.db?mode=ro" "SELECT ..."

Understanding Tool Data

Tool usage is stored in the JSON event_data field. Assistant messages contain tool_use content blocks.

The structure is:

json
{
  "type": "assistant",
  "message": {
    "content": [
      {
        "type": "tool_use",
        "name": "Read",
        "input": {...}
      }
    ]
  }
}

Tool Analysis Queries

Extract All Tool Uses

sql
SELECT
    json_extract(value, '$.name') as tool_name,
    COUNT(*) as usage_count
FROM conversation_events,
     json_each(json_extract(event_data, '$.message.content'))
WHERE event_type = 'assistant'
    AND json_extract(value, '$.type') = 'tool_use'
    AND json_extract(value, '$.name') IS NOT NULL
GROUP BY tool_name
ORDER BY usage_count DESC;

Tool Usage Over Time

sql
SELECT
    DATE(inserted_at) as date,
    json_extract(value, '$.name') as tool_name,
    COUNT(*) as usage_count
FROM conversation_events,
     json_each(json_extract(event_data, '$.message.content'))
WHERE event_type = 'assistant'
    AND json_extract(value, '$.type') = 'tool_use'
    AND json_extract(value, '$.name') IS NOT NULL
    AND DATE(inserted_at) >= DATE('now', '-30 days')
GROUP BY date, tool_name
ORDER BY date DESC, usage_count DESC;

Tool Usage by Repository

sql
SELECT
    CASE
        WHEN git_remote_url IS NULL THEN '(no repo)'
        ELSE SUBSTR(git_remote_url, INSTR(git_remote_url, '/') + 1)
    END as repository,
    json_extract(value, '$.name') as tool_name,
    COUNT(*) as usage_count
FROM conversation_events,
     json_each(json_extract(event_data, '$.message.content'))
WHERE event_type = 'assistant'
    AND json_extract(value, '$.type') = 'tool_use'
    AND json_extract(value, '$.name') IS NOT NULL
GROUP BY git_remote_url, tool_name
ORDER BY usage_count DESC
LIMIT 30;

Tool Combinations (Most Common Pairs)

sql
WITH tool_sessions AS (
    SELECT
        event_session_id,
        json_extract(value, '$.name') as tool_name
    FROM conversation_events,
         json_each(json_extract(event_data, '$.message.content'))
    WHERE event_type = 'assistant'
        AND json_extract(value, '$.type') = 'tool_use'
        AND json_extract(value, '$.name') IS NOT NULL
)
SELECT
    a.tool_name as tool_1,
    b.tool_name as tool_2,
    COUNT(DISTINCT a.event_session_id) as sessions_together
FROM tool_sessions a
JOIN tool_sessions b ON a.event_session_id = b.event_session_id
WHERE a.tool_name < b.tool_name
GROUP BY a.tool_name, b.tool_name
ORDER BY sessions_together DESC
LIMIT 15;

Sessions by Tool Intensity

sql
SELECT
    event_session_id,
    COUNT(*) as total_tool_uses,
    COUNT(DISTINCT json_extract(value, '$.name')) as unique_tools,
    MIN(inserted_at) as session_start,
    git_remote_url
FROM conversation_events,
     json_each(json_extract(event_data, '$.message.content'))
WHERE event_type = 'assistant'
    AND json_extract(value, '$.type') = 'tool_use'
GROUP BY event_session_id
ORDER BY total_tool_uses DESC
LIMIT 20;

Response Format

When triggered, provide:

  1. Overview - Most used tools overall
  2. Trends - Tool usage patterns over time
  3. Context - Which repos use which tools
  4. Insights - Interesting patterns

Example Output

🔧 Claude Tool Usage Analysis

Top Tools (All Time):
1. Read: 487 uses (32.4%)
2. Bash: 312 uses (20.8%)
3. Edit: 289 uses (19.2%)
4. Grep: 178 uses (11.8%)
5. Glob: 156 uses (10.4%)
6. Write: 82 uses (5.5%)

Recent Trends (Last 7 days):
- Read usage increased 23%
- Task tool emerging (+45 uses)
- Bash usage stable

By Repository:
- vibe-check: Heavy Read + Bash (database work)
- my-app: Heavy Edit + Write (active development)
- docs: Heavy Write (documentation)

Common Tool Combinations:
- Grep → Read (78 sessions)
- Glob → Read (65 sessions)
- Read → Edit (52 sessions)

Most Tool-Intensive Session:
- Session abc123 (vibe-check, 2026-01-10)
  42 tool uses, 8 unique tools

Advanced Analysis (if requested)

File Operation Patterns

Analyze Read/Write/Edit patterns to show which files Claude works with most.

Error Analysis

Search for tool errors in responses to identify common issues.

Efficiency Metrics

Calculate avg tools per session, tools per message, etc.

Visualization Suggestions

If user wants visual analysis, suggest:

  • Export to CSV and visualize in spreadsheet
  • Generate simple text-based charts
  • Create timeline of tool adoption

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