# Evidence Driven Testing

Records visual proof while testing UI behavior, the agent tests the app hands-on via...

- Repository: https://github.com/michaelshimeles/rstack (1423 stars)
- Category: Design
- License: see repository
- Last updated: 2026-10-26
- Runs scripts: yes, review before use

## Install

Claude Code: `npx skills add michaelshimeles/rstack --skill evidence-driven-testing -g -a claude-code -y`
Codex: `npx skills add michaelshimeles/rstack --skill evidence-driven-testing -g -a codex -y`
Cursor: `npx skills add michaelshimeles/rstack --skill evidence-driven-testing -g -a cursor -y`
Gemini CLI: `npx skills add michaelshimeles/rstack --skill evidence-driven-testing -g -a gemini-cli -y`

## Description

Records visual proof while testing UI behavior, the agent tests the app hands-on via computer use while a screen recording with structured test/assertion annotations captures the session, then posts the video and a results summary to the requested destination. Use when changed runtime behavior needs observable verification, including headless environments (scripted screenshots and probes) and non-UI changes (measured numbers, output pairs).

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# Evidence-Driven Testing

Record proof of behavior and deliver it to the requested destination.

Choose evidence proportional to the change. Use the recorder for interactive
flows, scripted captures for headless UI checks, and output pairs for CLI or
API changes. Documentation-only edits need content checks and verification of
runnable examples, not a recording. Reuse suitable evidence already captured
in the task. Publish only to destinations included in the requested work.

The recording is the capture of you testing the app via computer use: start the
recorder, then drive the app yourself, click, type, navigate, through each
test target. Every action in the video is the test being performed live; the
recording has no value as evidence unless it shows that interactive session.
If the harness has no computer-use tools but a GUI exists, drive the app with
`cua-driver` instead (see below), it is still your live session.

The bundled recorder, `scripts/evidence.py`, captures the display with FFmpeg
on Linux, macOS, and Windows, timestamps each annotation you add while
testing, burns them into the video on stop, and verifies the result with
ffprobe. It writes `evidence.mp4`, `report.md`, and `manifest.json` into the
session folder.

## Inputs

- **Test targets** (required): The behaviors/flows to verify, phrased as testable statements.
- **PR / issue** (optional): Where to post the evidence. If omitted, deliver to the requester only.

## The recorder

`EVIDENCE` below means the path to `scripts/evidence.py` inside this skill's
folder (wherever the skill is installed, e.g.
`~/.claude/skills/evidence-driven-testing/scripts/evidence.py`). It needs only
Python 3 and FFmpeg.

The rest: https://github.com/michaelshimeles/rstack/blob/HEAD/evidence-driven-testing/SKILL.md