Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add kdr/overcast --skill overcast-presence-windowgit clone --depth 1 https://github.com/kdr/overcastWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/kdr/overcast/overcast-presence-window)<a href="https://agentmods.dev/skills/kdr/overcast/overcast-presence-window"><img src="https://agentmods.dev/badge/skills/kdr/overcast/overcast-presence-window/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/kdr/overcast/overcast-presence-window"><img src="https://agentmods.dev/badge/skills/kdr/overcast/overcast-presence-window.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00035 | $0.00549 |
| Opus 5 | $0.00017 | $0.00275 |
| Sonnet 5 | $0.00007 | $0.00110 |
| Haiku 4.5 | $0.00003 | $0.00055 |
Grade A, and why
overcast-presence-window scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 63 lines — stays where its author put it; the contents beside it link to each section on GitHub.
overcast-presence-window
Use this skill to answer "from when to when is 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 this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 63 lines · 35 tokens per session scan A 9a2c494a870a
overcast-presence-window is a skill published in the GitHub repository kdr/overcast (16 stars, last pushed 5d ago), licensed Apache-2.0. It adds 35 tokens to every session and 549 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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