Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add athola/claude-night-market --skill hooks-evalgit clone --depth 1 https://github.com/athola/claude-night-marketWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/athola/claude-night-market/hooks-eval)<a href="https://agentmods.dev/skills/athola/claude-night-market/hooks-eval"><img src="https://agentmods.dev/badge/skills/athola/claude-night-market/hooks-eval/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/athola/claude-night-market/hooks-eval"><img src="https://agentmods.dev/badge/skills/athola/claude-night-market/hooks-eval.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00018 | $0.01588 |
| Opus 5 | $0.00009 | $0.00794 |
| Sonnet 5 | $0.00004 | $0.00318 |
| Haiku 4.5 | $0.00002 | $0.00159 |
Grade A, and why
hooks-eval scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 206 lines — stays where its author put it; the contents beside it link to each section on GitHub.
When NOT To Use
- Writing a new hook (use
abstract:hook-authoring) - Evaluating skills (use
abstract:skills-eval) - Evaluating rules in
.claude/rules/(useabstract: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.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 206 lines · 18 tokens per session scan A 67afa3869c9f
hooks-eval is a skill published in the GitHub repository athola/claude-night-market (337 stars, last pushed yesterday), licensed MIT. It adds 18 tokens to every session and 1,588 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
evalscope
LLM evaluation & inference performance testing via the evalscope CLI. Translates natural language requests into evalscope commands for: (1) Model accuracy evaluation — runs registered benchmarks against local checkpoints or API endpoints (OpenAI-compatible, Anthropic, LiteLLM); (2) Performance stress testing — TTFT…
agent-harness-optimizer
Use when agent harness optimization patterns for token efficiency, memory persistence, session management, and cross-harness parity. Use when optimizing agent performance, reducing token costs,.
react-hooks-composition
Advanced React hooks composition patterns - SWR integration, debounced search, memoized contexts, state machines, and performance optimization.
React Component Patterns
Use this skill when you’re building or refactoring React components in a production app and want consistent patterns for typing, composition, state, and performance without introducing premature abstraction.
react-patterns
React production patterns — hooks, state management, performance optimization, and component design. Use when building React components, reviewing React code, or fixing React performance issues.
algorithmic-art
Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright…