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 transilienceai/communitytools --skill pentest-engagementgit clone --depth 1 https://github.com/transilienceai/communitytoolsWrote 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/transilienceai/communitytools/pentest-engagement)<a href="https://agentmods.dev/skills/transilienceai/communitytools/pentest-engagement"><img src="https://agentmods.dev/badge/skills/transilienceai/communitytools/pentest-engagement/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/transilienceai/communitytools/pentest-engagement"><img src="https://agentmods.dev/badge/skills/transilienceai/communitytools/pentest-engagement.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00140 | $0.02479 |
| Opus 5.5 | $0.00056 | $0.00992 |
| Sonnet 5.5 | $0.00028 | $0.00496 |
| Haiku 4.5 | $0.00014 | $0.00248 |
Grade A, and why
pentest-engagement 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.
How it starts
The opening of the file, as written. The whole thing — 61 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pentest Engagement
Orchestrates a scoped pentest end-to-end via the pentest-engagement workflow. It is the breadth-complete, coverage-gated counterpart to the flag-shaped htb-solve — same engine (coordinator-loop, now with interleaved per-finding validation built into the loop), but driven by an attack-class coverage matrix instead of a flag, with surface expansion and root-cause severity baked in.
When to use
A real (non-CTF) engagement defined by a scope — either:
- WEB — web / API / cloud apps defined by apex domains / asset URLs, or
- NETWORK — a list of IPs / CIDRs / ranges (e.g. 1500 hosts) to scan for live services and vulnerabilities.
The workflow auto-detects the mode in Setup (engagement_kind): predominantly IPs/CIDRs → network; apex domains / app URLs → web. For HackTheBox/CTF use hackthebox (htb-solve) instead.
Run it
WEB — from a scope file or inline:
Workflow('pentest-engagement', { scope_file: 'projects/pentest/<engagement>-scope.md' })
Workflow('pentest-engagement', { scope: { engagement_name, apex_domains:[], assets:[...], creds_env:[...], roe, business_tier } })
NETWORK — inline IP/CIDR list or a scope file containing one (a plain newline list of IPs/CIDRs is accepted):
Workflow('pentest-engagement', { targets: ['10.0.0.0/24', '192.0.2.0/24', '198.51.100.7'] })
Workflow('pentest-engagement', { scope_file: 'projects/pentest/<engagement>-ips.txt', scan_profile: 'standard' })
Options (shared): maxConcurrent (default = prudent, derived from CPU cores — ~half the cores, capped 2–8; never hundreds/thousands of parallel tasks), dryRun, max_experiments, business_tier, report (default true).
Options (network): scan_profile light (bounded 1-1024 + curated less-common, for large/fast sweeps) / standard (full-range -p- on every reachable host, DEFAULT; two-stage SYN→-sV on found-open ports, host-count-guarded, message-bus + non-443-TLS aware) / full (-p- + bounded UDP); udp (top-50 UDP; off for light/standard, auto-on for full); slice_size (hosts per scan worker, auto ≈64 IP-list / 2 CIDR-heavy); deepen_top (deep-dive the N highest-value hosts, default 10, 0 to skip); geo_vantages (≤2 gcp zones for the 2nd-vantage allowlist re-probe; overrides the US+EU default), auto_provision (default true; false = detect+flag only, no cloud spend). On a source-IP/geo-allowlist signature the workflow auto-provisions a 2nd-geography vantage and re-probes the filtered hosts before concluding "no surface."
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.
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 · 61 lines · 140 tokens per session scan A fe0ef46edd8f
pentest-engagement is a skill published in the GitHub repository transilienceai/communitytools (596 stars, last pushed 3mo ago), licensed MIT. It adds 140 tokens to every session and 2,479 once invoked, about $0.0006 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 2026-08-30.
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