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-lineupgit 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-lineup)<a href="https://agentmods.dev/skills/kdr/overcast/overcast-lineup"><img src="https://agentmods.dev/badge/skills/kdr/overcast/overcast-lineup.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00044 | $0.01029 |
| Opus 5 | $0.00022 | $0.00515 |
| Sonnet 5 | $0.00009 | $0.00206 |
| Haiku 4.5 | $0.00004 | $0.00103 |
Grade A, and why
overcast-lineup 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 7d 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 — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.
overcast-lineup
Use this skill when the task is "run this person through the database": accumulate
every face across the case's clips and images into a local, browsable lineup, then
identify a probe photo against it. Use the broad overcast skill and
overcast/reference/verbs.md for exact flags. The whole DB is local — no media
leaves the case.
Prerequisites
The lineup is deepface-only (clustering needs face embeddings the tinycloud face
path doesn't expose). cluster runs the uv-managed visual-DB Python directly
(via OC_VISUAL_DB_PY), so you do NOT need to bind the face provider — leave
your profile's face binding untouched. Just prepare the Python once and stand up
a face-cluster index:
overcast doctor --json # confirm uv + visual-db are ready
scripts/visual-db-uv.sh --face # install OpenCV/DeepFace (once per machine)
overcast case init --json
overcast index create people --type face-cluster --local --json
Workflow
- Book every case video/image into the lineup —
cluster adddetects, embeds, and assign-or-creates each face into a person (nearest existing person above--min-similarity, else a new one):
overcast cluster add ./interview.mp4 --index <index-id> --json
overcast cluster add ./cctv-lobby.mp4 --index <index-id> --json
overcast cluster add ./mugshot.jpg --index <index-id> --json
- Open the lineup — a self-contained HTML contact sheet, one row per person:
overcast cluster view --index <index-id> --json # add --no-open to only write the gallery
overcast cluster list --index <index-id> --json # people + member counts
- Run a suspect photo through the database.
cluster identifyreports the most similar person (similarity 0–100) or flags the probe as a likely NEW person, and never writes to the DB:
overcast cluster identify ./suspect.jpg --index <index-id> --json
overcast cluster show <person-id> --index <index-id> --json # inspect that person's member faces
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.
- 7d ago First seen · 93 lines · 44 tokens per session scan A b186a356231c
overcast-lineup is a skill published in the GitHub repository kdr/overcast (16 stars, last pushed 4d ago), licensed Apache-2.0. It adds 44 tokens to every session and 1,029 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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