hookify

hookify is a skill for Claude Code, Codex from anthony-spruyt/claude-plugins. It costs 51 tokens per session (1,213 once invoked), scanned C, original, MIT.

A Hookify skill for turning unwanted agent behaviors into hook rules. It can use explicit instructions or analyze recent conversation messages, then create rules using Hookify's file format.

In plain words
What is it for?
Use it when you want to prevent a named behavior, analyze a conversation for problems, or invoke the /hookify command.
Why use it?
It reduces the manual work of translating a complaint or repeated mistake into an automatic warning or prevention rule.

Skill for Claude CodeCodex

Part of the hookify-plus plugin — 5 skills, 1 agent, 3 hooks shipped together

Install

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.

agentmods
npx agentmods add skills/anthony-spruyt/claude-plugins/hookify
Any agent
npx skills add anthony-spruyt/claude-plugins --skill hookify
Clone the repo
git clone --depth 1 https://github.com/anthony-spruyt/claude-plugins

Made for: Claude Code, Codex.

Or install hookify-plus, the plugin that ships this one along with the rest of its 5 skills, 1 agent, 3 hooks.

Wrote 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.

agentmods badge for hookify

README.md
[![agentmods](https://agentmods.dev/badge/skills/anthony-spruyt/claude-plugins/hookify.svg)](https://agentmods.dev/skills/anthony-spruyt/claude-plugins/hookify)
Your own site
<a href="https://agentmods.dev/skills/anthony-spruyt/claude-plugins/hookify"><img src="https://agentmods.dev/badge/skills/anthony-spruyt/claude-plugins/hookify.svg" alt="Measured on agentmods" height="20"></a>
Per session 51 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,213 The whole file, excluding the scripts and references it only reads on demand.
Security scan C 1 finding. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00051 $0.01213
Opus 5 $0.00026 $0.00607
Sonnet 5 $0.00010 $0.00243
Haiku 4.5 $0.00005 $0.00121

Measured 3d ago against content hash 580bc6b4a9aa, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade C, and why

hookify scanned grade C with 1 finding 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 3d 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.

Recursive force deletehighDestructive command

rm -rf with a variable or a broad path is one typo away from removing the wrong tree.

- Label: Short description (e.g., "Block rm -rf")
hookify-plus/skills/hookify/SKILL.md · 159 lines

How it starts

The opening of the file, as written. The whole thing — 159 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Hookify — Create Hooks from Unwanted Behaviors

FIRST: Load the hookify-plus:writing-rules skill using the Skill tool to understand rule file format and syntax.

Create hook rules to prevent problematic behaviors by analyzing the conversation or acting on explicit user instructions.

Step 1: Gather Behavior Information

If $ARGUMENTS is provided:

  • Parse the user's specific instructions from $ARGUMENTS.
  • Also scan recent conversation (last 10-15 user messages) for additional context and examples of the behavior occurring.

If $ARGUMENTS is empty:

  • Launch the conversation-analyzer agent via the Task tool to find problematic behaviors.
  • The agent scans user messages for frustration signals, corrections, repeated issues, and explicit avoidance requests.

Conversation-analyzer agent prompt:

{
  "subagent_type": "general-purpose",
  "description": "Analyze conversation for unwanted behaviors",
  "prompt": "You are analyzing a Claude Code conversation to find behaviors the user wants to prevent.

Read user messages in the current conversation and identify:
1. Explicit requests to avoid something (\"don't do X\", \"stop doing Y\")
2. Corrections or reversions (user fixing Claude's actions)
3. Frustrated reactions (\"why did you do X?\", \"I didn't ask for that\")
4. Repeated issues (same problem multiple times)

For each issue found, extract:
- What tool was used (Bash, Edit, Write, etc.)
- Specific pattern or command
- Why it was problematic
- User's stated reason

Return findings as a structured list with:
- category: Type of issue
- tool: Which tool was involved
- pattern: Regex or literal pattern to match
- context: What happened
- severity: high/medium/low

Focus on the most recent issues (last 20-30 messages). Don't go back further unless explicitly asked."
}

Step 2: Present Findings to the User

After gathering behaviors (from arguments or the agent), present findings using AskUserQuestion.

Question 1 — Which behaviors to hookify:

Read the full file on GitHub · 159 lines

Files

What ships with it

3 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.

Changes

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.

  1. 3d ago First seen · 159 lines · 51 tokens per session scan C 580bc6b4a9aa

Subscribe to this mod's changes

hookify is a skill published in the GitHub repository anthony-spruyt/claude-plugins (2 stars, last pushed 5d ago), licensed MIT. It adds 51 tokens to every session and 1,213 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it C with 1 finding (recursive force delete). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

brainstorming

You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.

obra/superpowers · 37 tokens

auto-perf-optimize

Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.

microsoft/vscode · 62 tokens

chat-perf

Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.

microsoft/vscode · 51 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens