agentleFS
forefyforefy/.context/skills/hunter-utils/evidence-capture/SKILL.md

evidence-capture

Skill153 starsChanged 45 days agoMITView on GitHub

Enforce reproduction bug evidence in either image or video formats to be ready to submit

2 other projects use a version of this.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

2 rules. About 0 are common, 2 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈2

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Don't fabricate data only use real data and real captures no workarounds find the best way to get proper evidence

    line 17
  2. Distinctive:

    No scene without a real capture: Every step is a screenshot the tool took, hashed into a manifest.

    line 21

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Evidence capture skills assists in the image and/or video evidence that go to prove reproducible bugs.

Must-have rules

  • Reproductions usually are made of steps. each step needs to be thought of what we want to present it could be insight or outcome that is tailored to the sentence in the reproduction example
  • Captures are only visuals, added text must be minimal if even at all
  • OCR-adding markings of the exact point-in-image that the evidence speaks to, for example, if we are showing BurpSuite raw Request/Response pair - a marker signaling the lines exactly on where to look is crucial (other than staring at a wall of info) - the marking should fit the evidence
  • Image type captures must go with a 1 line title describing the step (e.g. Attached image demonstrates browser view of when the user interacts with x)
  • Capture each thing from the tool that owns it - HTTP from Burp (Repeater or Proxy), never a raw request or response pasted into a browser tab; app behaviour from the browser; code from the editor or a rendered snippet, not a photo of a terminal; a command from the terminal; on-chain state from the explorer or a Foundry trace. The owning tool carries the detail a makeshift capture loses (headers, timing, a diff), and showing it the wrong way reads as amateur. If the right tool is open, use it.
  • Correlate surfaces across scenes - To show Burp, the browser, and a code snippet together, chain one capture per scene in order (wire scene, then the browser step, then the code). Each stays a real, hashable capture.
  • link to the live source whether its proof in code, in burp, in browser in a specific moment from the user story etc
  • Don't fabricate data only use real data and real captures no workarounds find the best way to get proper evidence
  • When done, critique the result with actual OCR or visual analysis and wonder if you missed any guidelines in this skill checklist or you did something off (e.g. if you marked a part in the image too much to the right of where the text actually is)

Extended rules

  • No scene without a real capture. Every step is a screenshot the tool took, hashed into a manifest. Never hand-draw a UI, never fabricate a frame, never claim a step you did not capture.
  • Always end with insight, impact and risk. It is the point of the video: who is affected, what is at stake, what to verify, and the blast radius. A video that stops at the walkthrough is unfinished.
  • Let the subject pick the form. A race condition wants a timeline; a privilege jump wants two lanes that cross; a data leak wants the record pulled into view; an auth flow wants the wire step foregrounded. Reach for the shape that explains this mechanism, not the shape you used last time.
  • Make it beautiful and legible. One accent, deliberate pacing, a designed open and close, captions only where the image needs them. The craft is what makes a reviewer watch to the end.
  • Redact before you capture HTTP. When a step's payload carries a credential, cookie, token or PII, redact it before it enters any file. Record the original request's hash, not its secrets. The build shows [redacted] and the hash, which is what a reader checks.

Dependencies

  • For videos Explicitly use HyperFrames and their studio app locally.
  • A capture source. Any one of:
    • Burp proxy history over the reburp REST API (http://127.0.0.1:9090) for the real HTTP request and response behind a step. See the burp-interaction usage if present.
    • A browser you can drive and screenshot (Claude in Chrome, or the built-in browser pane) for the UI frames and live network list.
    • Terminal screenshots for a CLI or a Foundry or forge test reproduction, where each step is a command and its real output.
    • Github code paths

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.