verification
Use when checking whether agent edits are reflected in the OpenChatCut project and editor.
Profile →npx skills add 0xsline/OpenChatCut --skill verification --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Verification Use the lowest verification level that proves the requested result: | Level | Required evidence | |---|---| | L0 | Static checks such as the focused verification script, `npx tsc --noEmit`, tests, and build. | | L1 | A real Agent run against the editor at `localhost:5199`, followed by structural and rendered evidence. | | L2 | The packaged desktop app completing the user scenario, including human visual review where automation is insufficient. | Runtime behavior changes require L0 + L1. Release and desktop-only changes also require L2 when the packaged app is the behavior under test. Prefer two signals: 1. `read_project` for structure: assets, tracks, items, frame placement, timeline duration. 2. A visual capture path for rendered evidence at exact frames. Use `view_timeline_frames` for composed timeline proof. This verifies the edited OpenChatCut timeline: trims, layers, captions, effects, markers, placeholders, crops, transitions, and layout. For raw source-asset frame inspection, choose the cheapest path based on where the bytes live: - The agent in this build has no local filesystem access; all source bytes live in the project media store (`/media/uploads/`). Use
- Real Agent transcript check
What does the verification skill do?
Use when checking whether agent edits are reflected in the OpenChatCut project and editor.
How do I install it?
Run `npx skills add 0xsline/OpenChatCut --skill verification --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From 0xsline/OpenChatCut, a repository with 805 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.