Getting it into your agent
There is no command for this one: it runs only inside a plugin, and the catalogue could not identify which plugin ships it. The source is linked below.
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.
[](https://agentmods.dev/skills/encod3d-sec/torch/screenshot)<a href="https://agentmods.dev/skills/encod3d-sec/torch/screenshot"><img src="https://agentmods.dev/badge/skills/encod3d-sec/torch/screenshot.svg" alt="Measured on agentmods" 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 | $0.00099 | $0.03875 |
| Opus 5 | $0.00049 | $0.01937 |
| Sonnet 5 | $0.00020 | $0.00775 |
| Haiku 4.5 | $0.00010 | $0.00387 |
Grade A, and why
screenshot scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
is fine (it's a GET you already make). Never screenshot a host you would not curl. How it starts
The opening of the file, as written. The whole thing — 208 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Screenshot: visual PoC capture
Turn the text walkthrough into evidence. Capture runs on the Kali tooling host (it has the VPN
route to in-scope targets); the PNG is then pulled into the vault under targets/<eng>/poc/. Driver:
scripts/shot.py (chromium headless). For redaction-before-report use Skill(evidence).
One evidence dir, captured by hand. poc/ = the curated story you choose to show (login, the
exploited state, the flag). ALL PoC evidence is now captured MANUALLY and LIVE via capture.sh straight
into poc/ the moment a step lands - there is no auto-capture net.
Scope check
Only screenshot in-scope hosts (read targets/<eng>/scope.md). On passive_only RoE a screenshot
is fine (it's a GET you already make). Never screenshot a host you would not curl.
What to capture: EVERY breakthrough, as it happens (with retries)
Screenshot the moment each step LANDS, not at the end - the box may expire. A breakthrough = anything
you'd put in the report: the entry page, a leaked secret / useful source (deobfuscated JS, a
config, an app.log), the cipher / decrypt response, the vuln firing, the authed/exploited
state, the flag. Tell the arc (Entry -> Trigger -> Impact) AND capture the intermediate proofs
(the leak, the crypto response) - those are exactly what a reviewer disbelieves without a picture.
- Always show the URL. Every web/source capture must carry its address bar so the image is
self-identifying - which page/path it is (
https://T/folder/folder/log.md), not an anonymous blob. Live<url>mode adds it automatically; for--html/--termof a fetched resource pass--url-bar "<full URL>". - Retry (box is up). Renders fail transiently (nav timeout, cold chromium). Retry 2-3x and confirm
the PNG is non-empty (
[ -s out.png ]) before moving on; while the box is up, go back and re-capture anything you missed rather than shipping evidence with gaps. NameNN-slug.png(NN = step order) so the evidence reads top-to-bottom.
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.
- 6d ago First seen · 208 lines · 99 tokens per session scan A 2d3c87c61457
screenshot is a skill published in the GitHub repository Encod3d-Sec/TORCH (286 stars, last pushed 4d ago), licensed MIT. It adds 99 tokens to every session and 3,875 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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