Overcast presence window
Find the interval a person or object is present — anchor one appearance, then sweep outward with face-match / detect until it drops off both sides.From its SKILL.md
npx -y skills add kdr/overcast --skill overcast-presence-windowAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
2 things to look at
- 12 stars12 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
- runs commandsInstructs the agent to run 8 commands, including `overcast doctor --json` and 7 more.
SKILL.md
2.2 KB, 503 tokens by cl100k_base, as published. Nobody here has run it
overcast-presence-window
Use this skill to answer "from when to when is <target> on screen?" — a first/last
appearance interval, not a single instant. It anchors one confirmed appearance and
expands until the target stops appearing, the presence-tracking analog of a
temporal search. Use the broad overcast skill and
overcast/reference/verbs.md for exact flags.
Workflow
- Local clip + record id:
overcast doctor --json
overcast case init --json
overcast watch ./clip.mp4 --json # -> record id REC
- Anchor one appearance (whichever fits the target):
overcast face ./clip.mp4 --match ./person.jpg --json # a specific person (similarity 0-100)
overcast grid ./clip.mp4 --count 16 --json # then see the montage for an object
- Sweep outward from the anchor until K consecutive misses on each side:
# person: widen the window; --fps controls sample density (precision vs cost)
overcast face ./clip.mp4 --match ./person.jpg --start <a> --end <b> --fps 1 --min-similarity 55 --json
# object: step frames outward and check presence
overcast see frame://REC@<t> --prompt "Is <target> present? answer only yes or no" --json
- Emit the presence interval(s) and show them:
overcast note "<target> present" --ref REC --at <first-last> --confidence medium --json
overcast view REC --at <first-last> --json
overcast brief --export ./presence.md --json
Output
One or more [first-last] intervals with the per-hit citations (record.id +
media.at) that bound them, and the sample density used. If the target leaves
and returns, report each interval separately rather than one span covering the
gap.
Caveats
Sampled detections are per-frame, not continuous — presence between samples is
inferred; raise --fps to tighten boundaries at higher cost. Occlusion or an
off-camera moment splits one presence into several intervals — that's a real
result, not noise. Face similarity is 0-100. Needs the video local.
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.