Borrowing it
Nothing to install: this file belongs to brovar/10x-pentest. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/brovar/10x-pentest/main/.github/skills/pt-scope-review/SKILL.mdgit clone --depth 1 https://github.com/brovar/10x-pentestWrote 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/brovar/10x-pentest/pt-scope-review)<a href="https://agentmods.dev/skills/brovar/10x-pentest/pt-scope-review"><img src="https://agentmods.dev/badge/skills/brovar/10x-pentest/pt-scope-review/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/brovar/10x-pentest/pt-scope-review"><img src="https://agentmods.dev/badge/skills/brovar/10x-pentest/pt-scope-review.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 | $0.00113 | $0.01883 |
| Opus 5 | $0.00056 | $0.00941 |
| Sonnet 5 | $0.00023 | $0.00377 |
| Haiku 4.5 | $0.00011 | $0.00188 |
Grade A, and why
pt-scope-review 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 10d 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 — 129 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/pt-scope-review — Scope Quality Review
An independent critic for the scope. Where /pt-scope asks "are the required fields present?"
(its mechanical readiness gate), this asks "is this scope actually sound, coherent, and sufficient
to run a safe, useful test?" — with fresh eyes, so the producer isn't grading its own work.
Advisory, with triage. It does not hard-block /pt-recon; the producer's readiness gate is the
hard floor. But errors here poison every downstream stage, so it's strongly recommended.
When to use, when to skip
- Use right after
/pt-scope, before recon — a flawed scope costs the whole engagement. - Skip only for a trivial re-scope you already trust. Advisory: you can proceed without it.
Initial Response
<engagement-id>→ review that engagement's scope (Step 0).- A saved report path (contains
<!-- PT-SCOPE-REVIEW -->) → resume triage (jump to Step 7). - Without → print
Usage: /pt-scope-review <engagement-id>.and STOP.
Inputs
scope.md— [blocking] (the subject of review).engagement.md— [blocking] (retest lineage; authorization must be fresh on a retest).- Source / environment — [optional] — to cross-check that stated assets/accounts are real.
Process
Step 1: Internal-consistency scan
Read scope.md fully against itself and scope-schema. Highest-value findings are contradictions the
author half-noticed: e.g. environment: production + destructive_policy: full-exploit with no
confirmation; dos_policy: forbidden but objectives imply stress; a validity window that ends before
the stated testing window; box_type: white + repo_access: false.
Step 2: Grounding spot-checks
Verify a few claims are real, not asserted: in-scope assets resolve to actual targets; the provided
U-NNN accounts exist / are obtainable; the authorization reference points to something.
Step 3: Deep independent verification
Re-derive rather than trust. Where the host supports parallel sub-agents, delegate; else inline: independently check the scope against a completeness rubric (are there in-scope-implied assets or account roles the operator forgot?) and, from code + already-gathered passive sources (never target-touching traffic), sample whether the stated scope matches the real system boundary (e.g. an in-code admin surface or subdomain the RoE should mention).
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.
- 10d ago First seen · 129 lines · 0 tokens per session scan A 8cd8a8c3866f
pt-scope-review is a skill published in the GitHub repository brovar/10x-pentest (3 stars, last pushed 28d ago), licensed Apache-2.0. It adds 113 tokens to every session and 1,883 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…