Hookify Create

A skill for turning unwanted assistant behaviors into Hookify rule files. These files use regular-expression patterns, which are text-matching rules, to detect commands or tool-use patterns.

In plain words
What is it for?
It analyzes the conversation or a stated concern, identifies behavior to block, and creates a local rule file in the required format.
Why use it?
It helps prevent recurring problematic behavior by recording rules instead of relying on reminders in each conversation.

Skill for Claude CodeCodex

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/poorgramer-zack/copilot-cli-things/hookify-create
Any agent
npx skills add Poorgramer-Zack/copilot-cli-things --skill hookify-create
Clone the repo
git clone --depth 1 https://github.com/Poorgramer-Zack/copilot-cli-things

Made for: Claude Code, Codex.

Per session 58 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,907 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 $0.00058 $0.01907
Opus 5 $0.00029 $0.00954
Sonnet 5 $0.00012 $0.00381
Haiku 4.5 $0.00006 $0.00191

Measured 2d ago against content hash 35c13cf9b7aa, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade C, and why

Hookify Create 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 2d 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")
plugins/hookify/skills/hookify-create/SKILL.md · 232 lines

How it starts

The opening of the file, as written. The whole thing — 232 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 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 from explicit user instructions.

Your Task

You will help the user create hookify rules to prevent unwanted behaviors.

Step 1: Gather Behavior Information

If $ARGUMENTS is provided:

  • User has given specific instructions: $ARGUMENTS
  • Still analyze recent conversation (last 10-15 user messages) for additional context
  • Look for examples of the behavior happening

If $ARGUMENTS is empty:

  • Launch the conversation-analyzer agent to find problematic behaviors
  • Agent will scan user prompts for frustration signals
  • Agent will return structured findings

To analyze conversation: Use the task/agent tool to launch conversation-analyzer agent:

{
  "subagent_type": "general-purpose",
  "description": "Analyze conversation for unwanted behaviors",
  "prompt": "You are analyzing a Copilot CLI 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 Copilot'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 (powershell, edit, create, 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 User

Read the full file on GitHub · 232 lines

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. 2d ago First seen · 232 lines · 58 tokens per session scan C 35c13cf9b7aa

Subscribe to this mod's changes

Hookify Create is a skill published in the GitHub repository Poorgramer-Zack/copilot-cli-things (2 stars, last pushed 5mo ago), licensed MIT. It adds 58 tokens to every session and 1,907 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.

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