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 agentmods add commands/kumaran-is/claude-code-onboarding/hookify-listgit clone --depth 1 https://github.com/kumaran-is/claude-code-onboardingWrote 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/commands/kumaran-is/claude-code-onboarding/hookify-list)<a href="https://agentmods.dev/commands/kumaran-is/claude-code-onboarding/hookify-list"><img src="https://agentmods.dev/badge/commands/kumaran-is/claude-code-onboarding/hookify-list.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00024 | $0.00366 |
| Opus 5 | $0.00012 | $0.00183 |
| Sonnet 5 | $0.00005 | $0.00073 |
| Haiku 4.5 | $0.00002 | $0.00037 |
Grade B, and why
hookify-list scanned grade B 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 today.
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.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
1. Use Glob to find all rule files: `.claude/hookify.*.local.md` What it actually says
Hookify List — Show All Rules
List every .claude/hookify.*.local.md file and its current status.
Steps
-
Use Glob to find all rule files:
.claude/hookify.*.local.md -
For each file, read it and extract:
name,enabled,event,action,pattern(orconditions)- First line of message body (for preview)
-
Print a summary table:
## Hookify Rules
| Name | Status | Event | Action | Pattern |
|------|--------|-------|--------|---------|
| warn-console-log | ✅ enabled | file | warn | console\.log\( |
| require-tests | ❌ disabled | stop | block | (conditions) |
Total: N rules (X enabled, Y disabled)
-
For each rule, add a one-line preview of its message body.
-
Footer:
To toggle rules: /hookify-configure
To create a rule: /hookify [describe behavior]
To edit manually: Edit .claude/hookify.{name}.local.md (changes apply immediately)
To disable: Set enabled: false | To delete: remove the file
If No Rules Found
No Hookify rules configured yet.
To create one:
/hookify Warn me when I use console.log
/hookify Block force-push to main
/hookify # scan conversation for behaviors to prevent
$ARGUMENTS
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.
- today First seen · 53 lines · 0 tokens per session scan B dc330adacfe0
hookify-list is a command published in the GitHub repository kumaran-is/claude-code-onboarding (35 stars, last pushed 2mo ago), licensed MIT. It adds 24 tokens to every session and 366 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other commands, from other repositories
git
Git operations with intelligent commit messages and workflow optimization.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.