segment-evidence
Skill2 starsChanged 7 months agoMITView on GitHub
Fuse video shot segments with storyboard frames, OCR, transitions, and timeline artifacts into one per-segment evidence map for grounded video review.
In this repository17 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- compare-video-runsSkill
- install-skill-packSkill
- layout-safety-reviewSkill
- package-review-promptSkill
- review-bundleSkill
- segment-storyboardSkill
- skill-catalogSkill
- source-media-signalsSkill
- storyboard-extractSkill
- storyboard-ocrSkill
- storyboard-transitionsSkill
- storyboard-understandSkill
- video-artifact-intakeSkill
- video-shotsSkill
- video-technical-reviewSkill
The file
We split this skill into the rules it gives an agent
4 rules. About 0 are common, 0 are distinctive, and 4 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈0
Distinctive · estimate
This author's own choices. Worth a look.
4
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 8
Use this after video-shots when a reviewer needs one ordered map of what evidence exists for each video part.
- Very specific: line 21
Use the same bundle locators as video-artifact-intake:
- Very specific: line 48
Run video-shots first. Run segment-storyboard plus storyboard-ocr when global storyboard sampling leaves too many empty segments.
- Very specific: line 59
Treat empty as an abstention signal.
≈ “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.
Files
Segment Evidence
Use this after video-shots when a reviewer needs one ordered map of what
evidence exists for each video part.
This skill owns:
- reading
video.shots.json - attaching overlapping storyboard frames
- attaching OCR text evidence and OCR quality counts
- attaching overlapping transition and timeline evidence
- writing
segment.evidence.json
Inputs
Use the same bundle locators as video-artifact-intake:
{
"outputDir": "./output/example-run",
"maxTextItemsPerSegment": 8
}maxTextItemsPerSegment defaults to 8. outputPath is optional if the
artifact should be written somewhere other than segment.evidence.json.
Outputs
The result contains manifestPath and manifest. The manifest has one segment
per shot, with:
- segment start/end times
- representative shot frame path when available
- overlapping storyboard frames
- overlapping timeline items
- overlapping transitions
- text evidence from OCR and timeline artifacts
evidenceStatus:usable,weak, orempty
Sequencing Guidance
Run video-shots first. Run segment-storyboard plus storyboard-ocr when
global storyboard sampling leaves too many empty segments. Run
storyboard-transitions and timeline-producing tools first if you want richer
segment evidence. The tool can still run with only video.shots.json, but most
segments will be weak or empty.
Interpretation Notes
segment.evidence.json is an evidence router. It says which artifacts support
each segment. It does not prove full semantic understanding by itself.
Treat empty as an abstention signal. Treat weak as a request to inspect the
representative frame or source video before making claims.
Repo-side runner:
node --import tsx scripts/harness/segment-evidence.ts
Installed-pack runner:
node ./.video-evaluator/agent/run-tool.mjs segment-evidence
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
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.

