Hooks eval

When NOT To Use

• Writing a new hook (use abstract:hook-authoring)
• Evaluating skills (use abstract:skills-eval)
• Evaluating rules in .claude/rules/ (use abstract:rules-eval)

Table of Contents

• Overview
• Key Capabilities
• Core Components
• Quick Reference
• Hook Event Types
• Hook Callback Signature
• Return Values
• Quality Scoring (100 points)
• Detailed Resources
• Basic Evaluation Workflow
• Integration with Other Tools
• Related Skills

Hooks Evaluation Framework

Overview

This skill provides a detailed framework for evaluating, auditing, and implementing Claude Code hooks across all scopes (plugin, project, global) and both JSON-based and programmatic (Python SDK) hooks.

Key Capabilities

• Security Analysis: Vulnerability scanning, dangerous pattern detection, injection prevention
• Performance Analysis: Execution time benchmarking, resource usage, optimization
• Compliance Checking: Structure validation, documentation requirements, best practices
• SDK Integration: Python SDK hook types, callbacks, matchers, and patterns

Core Components

Component	Purpose
Hook Types Reference	Complete SDK hook event types and signatures
Evaluation Criteria	Scoring system and quality gates
Security Patterns	Common vulnerabilities and mitigations
Performance Benchmarks	Thresholds and optimization guidance

Quick Reference

Hook Event Types

HookEvent = Literal[
    "PreToolUse",       # Before tool execution
    "PostToolUse",      # After tool execution
    "UserPromptSubmit", # When user submits prompt
    "Stop",             # When stopping execution
    "SubagentStop",     # When a subagent stops
    "TeammateIdle",     # When teammate agent becomes idle (2.1.33+)
    "TaskCompleted",    # When a task finishes execution (2.1.33+)
    "PreCompact"        # Before message compaction
]

Verification: Run the command with --help flag to verify availability.

Note: Python SDK does not support SessionStart, SessionEnd, or Notification hooks due to setup limitations. However, plugins can define SessionStart hooks via hooks.json using shell commands (e.g., leyline's detect-git-platform.sh).

Plugin-Level hooks.json

Plugins can declare hooks via "hooks": "./hooks/hooks.json" in plugin.json. The evaluator validates:

• Referenced hooks.json exists and is valid JSON
• Shell commands referenced in hooks exist and are executable
• Hook matchers use valid event types

Hook Callback Signature

async def my_hook(
    input_data: dict[str, Any],    # Hook-specific input
    tool_use_id: str | None,       # Tool ID (for tool hooks)
    context: HookContext           # Additional context
) -> dict[str, Any]:               # Return decision/messages
    ...

Verification: Run the command with --help flag to verify availability.

Return Values

return {
    "hookSpecificOutput": {
        "hookEventName": "PreToolUse",       # Match hook type
        "permissionDecision": "deny",        # Optional: block action
        "permissionDecisionReason": "...",   # Reason for denial
        "additionalContext": "...",          # Optional: context added
    }
}

Verification: Run the command with --help flag to verify availability.

Quality Scoring (100 points)

Category	Points	Focus
Security	30	Vulnerabilities, injection, validation
Performance	25	Execution time, memory, I/O
Compliance	20	Structure, documentation, error handling
Reliability	15	Timeouts, idempotency, degradation
Maintainability	10	Code structure, modularity

Detailed Resources

• SDK Hook Types: See modules/sdk-hook-types.md for complete Python SDK type definitions, patterns, and examples
• Evaluation Criteria: See modules/evaluation-criteria.md for detailed scoring rubric and quality gates
• Security Patterns: See modules/sdk-hook-types.md for vulnerability detection and mitigation
• Performance Guide: See modules/evaluation-criteria.md for benchmarking and optimization

Basic Evaluation Workflow

# 1. Run detailed evaluation
/hooks-eval --detailed

# 2. Focus on security issues
/hooks-eval --security-only --format sarif

# 3. Benchmark performance
/hooks-eval --performance-baseline

# 4. Check compliance
/hooks-eval --compliance-report

Verification: Run the command with --help flag to verify availability.

Integration with Other Tools

# Complete plugin evaluation pipeline
/hooks-eval --detailed          # Evaluate all hooks
/analyze-hook hooks/specific.py      # Deep-dive on one hook
/validate-plugin .                   # Validate overall structure

Verification: Run the command with --help flag to verify availability.

Related Skills

• abstract:hook-scope-guide - Decide where to place hooks (plugin/project/global)
• abstract:hook-authoring - Write hook rules and patterns
• abstract:validate-plugin - Validate complete plugin structure

Troubleshooting

Common Issues

Hook not firing Verify hook pattern matches the event. Check hook logs for errors

Syntax errors Validate JSON/Python syntax before deployment

Permission denied Check hook file permissions and ownership

Exit Criteria

• Every hook in scope receives a composite quality score (0-100) across the five weighted categories: Security (30), Performance (25), Compliance (20), Reliability (15), Maintainability (10).
• Any hook scoring below 60 on the Security category is flagged as a blocking issue before the evaluation report is returned.
• Shell commands referenced in hooks.json are verified to exist and be executable; missing scripts are listed as FAIL findings.
• The evaluation report distinguishes between JSON hooks (Claude Code) and Python SDK hooks and applies the correct signature expectations for each type.