pentest-report

pentest-report is a skill for Claude Code, Codex from tahirraufkeeyu/software-development-agent-stack--sdas. It costs 73 tokens per session (1,555 once invoked), scanned A, original, MIT.

A report-writing tool that turns completed penetration-test findings into a client-ready security assessment document. It includes explanations of risk, suggested fixes, and the evidence behind each finding.

In plain words
What is it for?
Use it to prepare customer deliverables after a penetration test or security review, including an executive summary, risk ratings, methodology, findings, and evidence appendix.
Why use it?
It removes the manual work of organising scanner results and tester notes into a consistent report. It does not perform the security test itself.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to prepare customer deliverables after a penetration test or security review, including an executive summary, risk ratings, methodology, findings, and evidence appendix.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/tahirraufkeeyu/software-development-agent-stack--sdas/pentest-report
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.

Any agent
npx skills add tahirraufkeeyu/software-development-agent-stack--sdas --skill pentest-report
Clone the repo
git clone --depth 1 https://github.com/tahirraufkeeyu/software-development-agent-stack--sdas

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for pentest-report

README.md
[![agentmods](https://agentmods.dev/badge/skills/tahirraufkeeyu/software-development-agent-stack--sdas/pentest-report/github.svg)](https://agentmods.dev/skills/tahirraufkeeyu/software-development-agent-stack--sdas/pentest-report)
Your own site
<a href="https://agentmods.dev/skills/tahirraufkeeyu/software-development-agent-stack--sdas/pentest-report"><img src="https://agentmods.dev/badge/skills/tahirraufkeeyu/software-development-agent-stack--sdas/pentest-report/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.

agentmods 80×15 button for pentest-report

Your own site · 80×15
<a href="https://agentmods.dev/skills/tahirraufkeeyu/software-development-agent-stack--sdas/pentest-report"><img src="https://agentmods.dev/badge/skills/tahirraufkeeyu/software-development-agent-stack--sdas/pentest-report.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 73 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,555 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00073 $0.01555
Opus 5 $0.00036 $0.00777
Sonnet 5 $0.00015 $0.00311
Haiku 4.5 $0.00007 $0.00155

Measured 6d ago against content hash 590af11d1f2a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

pentest-report 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 6d 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.

departments/security/skills/pentest-report/SKILL.md · 168 lines

How it starts

The opening of the file, as written. The whole thing — 168 lines — stays where its author put it; the contents beside it link to each section on GitHub.

When to use

Trigger on any of:

  • "Write the pentest report from these findings."
  • "Turn security-audit's output into a deliverable for the customer."
  • "Prepare the Q3 security assessment document."
  • End of an internal red-team engagement that already has a findings list.

Do not use to perform the assessment. This skill only assembles the report from evidence already collected.

Inputs

  • AUDIT_DIR — directory containing scanner outputs (the OUT_DIR from security-audit typically). Required.
  • MANUAL_NOTES — optional path to a markdown file with findings the tester documented by hand.
  • ENGAGEMENT_META — YAML with engagement name, client, tester(s), dates, scope list, methodology notes.
  • OUT_FILE (default: ./pentest-report.md).

Example ENGAGEMENT_META:

engagement: "Q3 2026 External Web App Assessment"
client: "Acme Corp"
testers:
  - "Taylor Reyes <[email protected]>"
window:
  start: "2026-04-05"
  end:   "2026-04-12"
scope:
  in:
    - https://app.acme.example
    - https://api.acme.example
  out:
    - https://blog.acme.example
methodology:
  - "OWASP WSTG v4.2"
  - "PTES Technical Guidelines"

Outputs

  • $OUT_FILE — markdown report matching references/report-template.md.
  • pentest-report.findings.json — machine-readable finding list used during assembly (kept for regeneration / re-export to DOCX/PDF).
  • pentest-report.risk-matrix.csv — risk matrix data.

Tool dependencies

  • jq to read scanner outputs.
  • pandoc (optional) to convert $OUT_FILE to DOCX/PDF for client delivery.
  • cvss-cli (optional) to recompute vectors when raw vectors are present.

Procedure

  1. Load ENGAGEMENT_META and validate required fields (client, window, scope, testers).
  2. Collect findings:
    • From $AUDIT_DIR/findings.normalized.json (security-audit output).
    • From $AUDIT_DIR/secrets.deduped.json (secret-scanner output).
    • From $AUDIT_DIR/dep-audit.normalized.json (dependency-audit output).
    • From $MANUAL_NOTES (parsed: each H3 becomes a finding).
  3. Normalize each finding into the report schema:
    { title, severity, cvss_score, cvss_vector, cwe, description,
      evidence (markdown block with code fences + image refs),
      impact, remediation, references[], status }
    
  4. Deduplicate across sources by (cwe, affected_asset) — if two scanners found the same issue, merge evidence blocks and keep the higher CVSS.
  5. Assign each finding a stable ID: FIND-<YEAR>-<0-padded-index>.
  6. Assemble the document per references/report-template.md:
    • Title page + engagement metadata.
    • Executive Summary (non-technical; counts per severity; business impact paragraph; 3 headline recommendations).
    • Scope (in/out, test windows, test accounts used).
    • Methodology (tools, frameworks cited from meta).
    • Findings (ordered by severity desc, then CVSS desc).
    • Risk Matrix (Impact x Likelihood 5x5, each cell lists finding IDs).
    • Recommendations (strategic, beyond per-finding fixes).
    • Appendix A: Raw evidence pointers (relative paths into $AUDIT_DIR).
    • Appendix B: Tool versions.
  7. Emit pentest-report.risk-matrix.csv: finding_id,likelihood(1-5),impact(1-5),risk(likelihood*impact).
  8. Optionally convert: pandoc $OUT_FILE -o pentest-report.docx --reference-doc=corp-template.docx.

Read the full file on GitHub · 168 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 6d ago First seen · 168 lines · 73 tokens per session scan A 590af11d1f2a

Subscribe to this mod's changes

pentest-report is a skill published in the GitHub repository tahirraufkeeyu/software-development-agent-stack--sdas (18 stars, last pushed 4mo ago), licensed MIT. It adds 73 tokens to every session and 1,555 once invoked, about $0.0004 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 2026-09-03.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

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…

microsoft/ai-agents-for-beginners · 200 tokens

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…

vercel/next.js · 95 tokens

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…

vercel/next.js · 83 tokens

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…

vercel/next.js · 170 tokens

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…

vercel/next.js · 103 tokens