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.
git clone --depth 1 https://github.com/punt-labs/punt-kitWrote 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/punt-labs/punt-kit/init)<a href="https://agentmods.dev/commands/punt-labs/punt-kit/init"><img src="https://agentmods.dev/badge/commands/punt-labs/punt-kit/init/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/commands/punt-labs/punt-kit/init"><img src="https://agentmods.dev/badge/commands/punt-labs/punt-kit/init.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00009 | $0.00227 |
| Opus 5.5 | $0.00004 | $0.00091 |
| Sonnet 5.5 | $0.00002 | $0.00045 |
| Haiku 4.5 | $0.00001 | $0.00023 |
Grade A, and why
init 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 1mo 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.
What it actually says
Punt Init
Run the deterministic scaffolding tool for a Punt Labs project.
Input
Project path: $ARGUMENTS (defaults to . if empty)
Process
First, run detection to see what we're working with:
punt init --language "" $ARGUMENTS 2>&1 || true
If the output shows Language: none, ask the user which language the project
uses (python, node, swift) via AskUserQuestion, then re-run with the flag:
punt init --language <chosen-language> $ARGUMENTS
If a language was detected, just run:
punt init $ARGUMENTS
Report the output to the user. Explain what files were generated and what manual steps remain.
If the user wants contextual reconciliation (workflow diffing, CLAUDE.md quality review, permission cleanup), suggest /punt reconcile as the next step.
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.
- 1mo ago First seen · 39 lines · 9 tokens per session scan A af7a07bc3a5c
init is a command published in the GitHub repository punt-labs/punt-kit (1 stars, last pushed yesterday), licensed MIT. It adds 9 tokens to every session and 227 once invoked, about $0.0000 per session on Opus 5.5. 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 2026-08-31.
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