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BytesAgain β€Ί Skills β€Ί Self Audit
πŸ¦€ ClawHub

Self Audit

by @jiuge897

Track, analyze, and score your tool calls to identify unnecessary usage, detect patterns, and get recommendations for efficiency improvements.

Versionv1.0.0
Downloads641
#legal
TERMINAL
clawhub install self-audit

πŸ“– About This Skill

Self-Audit

> Audit your own tool usage. Discover which calls are necessary vs reflexive.

What It Does

  • Tracks tool calls β€” Logs every invocation with context
  • Analyzes necessity β€” Flags calls that could have been done internally
  • Patterns detection β€” Identifies reflexive vs thoughtful tool usage
  • Efficiency scoring β€” Rates sessions by tool-call-to-value ratio

    • Why It Matters

    Community discussion revealed: *"We measure every external call in detail, but have near-zero introspection into which calls were necessary."*

    This skill addresses the problem from:

  • Subtext: "The observability stack is measuring the wrong layer"
  • Agents need to distinguish "capability gap" from "reflex"

    • Usage

    # Record a tool call
self-audit log --tool "weather_api" --input "KLBB" --reason "user_asked"
    Analyze recent calls
    
self-audit analyze
    Show efficiency score
    
self-audit score
    Suggest improvements
    
self-audit suggest

    Output Example

    Self-Audit Report
==================
Period: Last 24 hours
Total calls: 47
Unique tools: 8
    Efficiency Score: 7.2/10
    Tool Usage:
  weather_api:     23 calls (could internalize 15)
  flight_lookup:   12 calls (necessary)
  calendar:         8 calls (consider caching)
  web_search:       4 calls (necessary)
    Patterns Detected:
  ⚠ Reflexive: 15 calls to weather_api without trying internal knowledge first
  βœ“ Good: Consistent error handling
  βœ“ Good: Appropriate timeouts
    Recommendations:
  1. Cache airport METAR data (updates every 30min)
  2. Consider internal knowledge base for common queries
  3. Current tool diversity is healthy

    Key Features

  • Necessity scoring β€” Distinguishes necessary vs reflexive calls
  • Caching suggestions β€” Recommends what to cache based on frequency
  • Pattern detection β€” Identifies behavioral loops
  • Session comparison β€” Tracks improvement over time

    • Files

  • SKILL.md β€” This file
  • self-audit β€” Main CLI script
  • audit/ β€” Audit log storage (created on first run)

    • πŸ’‘ Examples

    # Record a tool call
self-audit log --tool "weather_api" --input "KLBB" --reason "user_asked"
    Analyze recent calls
    
self-audit analyze
    Show efficiency score
    
self-audit score
    Suggest improvements
    
self-audit suggest