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 angad-kandhari/deliberate --skill pentestgit clone --depth 1 https://github.com/angad-kandhari/deliberateWrote 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/angad-kandhari/deliberate/pentest)<a href="https://agentmods.dev/skills/angad-kandhari/deliberate/pentest"><img src="https://agentmods.dev/badge/skills/angad-kandhari/deliberate/pentest/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/angad-kandhari/deliberate/pentest"><img src="https://agentmods.dev/badge/skills/angad-kandhari/deliberate/pentest.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 | $0.00126 | $0.02450 |
| Opus 5 | $0.00063 | $0.01225 |
| Sonnet 5 | $0.00025 | $0.00490 |
| Haiku 4.5 | $0.00013 | $0.00245 |
Grade A, and why
pentest 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 9d 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 — 157 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pentest
Penetration-testing skill for LLM coding agents doing authorized security assessment.
The common case: point it at your own project's codebase to find vulnerabilities, then fix each one with secure and confirm the hole is closed with verify. The same discipline scales to scoped engagements — red-team exercises, CTFs, bug-bounty targets, or a running system you have written permission to test.
Where secure keeps the code you write safe, this skill hunts for the holes that got in anyway — proves they're real, and hands each one to secure to fix. Think of them as a loop: pentest finds, secure fixes, verify confirms. Counters the failure modes of undisciplined testing — probing without authorization, thrashing without a model, "findings" that don't reproduce, and testing that damages the system it was meant to protect.
0. Authorization Is the Precondition, Not a Formality
Authorized targets only. The gate scales with the target — but it's always a gate.
- Your own code or system: authorization is satisfied by ownership. Audit freely — this is the everyday case, and the rest of this skill is written for it.
- Anything you don't own — a third-party service, a shared or production environment with real users' data, a client's system, a bug-bounty target: you need explicit, current, written authorization that names this target, plus the rules of engagement (in-scope hosts/accounts, allowed techniques, testing window, contact). Get it before the first probe. "Probably fine" is not authorization.
- When in doubt about whether a target is yours to test, treat it as out of scope until you've confirmed otherwise.
Test: Do I own this target, or can I point to the authorization that covers it?
1. Map the Surface Before You Probe It
Understand the terrain first — whether that terrain is a codebase or a live host.
When auditing your own code (the common case), the source is the recon:
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.
- 9d ago First seen · 157 lines · 126 tokens per session scan A 78d47eae8435
pentest is a skill published in the GitHub repository angad-kandhari/deliberate (2 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 126 tokens to every session and 2,450 once invoked, about $0.0006 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 2026-08-31.
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explain
Guided code tour of a file or subsystem this session touched — entry point, the load-bearing pieces, the edges, and what connects to it.
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A system-planning guide that turns a vague idea into a set of linked design documents. It defines goals, modules, interfaces, data, workflows, and ways to check the result.
digest
Generate a structured vibe-learn learning digest of the current coding session from .vibe-learn/session-log.jsonl.
quiz
Check your understanding of the vibe-learn session — recall questions grounded in the session log, with results tracked across sessions in the knowledge ledger.
learn
Explain recent vibe-learn session activity or answer a question about what was built, grounded in .vibe-learn/session-log.jsonl.