overcast-camera-ballistics

overcast-camera-ballistics is a skill for Claude Code from kdr/overcast. It costs 65 tokens per session (985 once invoked), scanned A, original, Apache-2.0.

A forensic workflow for checking whether photos and videos were made with the same camera by reading EXIF metadata, which is technical information stored inside media files. It groups files by camera details and distinguishes a shared body serial number from weaker matching details.

In plain words
What is it for?
Use it to extract make, model, lens, serial number, capture time, location, or editing data from case media, group files into device clusters, and feed suggested links into a graph or map.
Why use it?
It helps assess whether media is linked to the same physical device without treating a shared camera model or lens as conclusive proof.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is for f in ./media/*.jpg ./media/*.mp4; do overcast exif "$f" --json; done # batch the whole case.

Part of the overcast plugin — 35 skills, 1 hook shipped together

Good fit Use it to extract make, model, lens, serial number, capture time, location, or editing data from case media, group files into device clusters, and feed suggested links into a graph or map.

Compare 6 skills from other repositories ↓
Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/kdr/overcast
agentmods
npx agentmods add skills/kdr/overcast/overcast-camera-ballistics

Made for: Claude Code.

Or install overcast, the plugin that ships this one along with the rest of its 35 skills, 1 hook.

Wrote 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.

agentmods badge for overcast-camera-ballistics

README.md
[![agentmods](https://agentmods.dev/badge/skills/kdr/overcast/overcast-camera-ballistics.svg)](https://agentmods.dev/skills/kdr/overcast/overcast-camera-ballistics)
Your own site
<a href="https://agentmods.dev/skills/kdr/overcast/overcast-camera-ballistics"><img src="https://agentmods.dev/badge/skills/kdr/overcast/overcast-camera-ballistics.svg" alt="Measured on agentmods" height="20"></a>
Per session 65 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 985 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00065 $0.00985
Opus 5 $0.00032 $0.00492
Sonnet 5 $0.00013 $0.00197
Haiku 4.5 $0.00006 $0.00098

Measured 7d ago against content hash a66523bdf74d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

overcast-camera-ballistics 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.

skills/overcast-camera-ballistics/SKILL.md · 82 lines

How it starts

The opening of the file, as written. The whole thing — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.

overcast-camera-ballistics

Use this skill to answer "were these shot on the same camera?": lift the device fingerprint embedded in each file's metadata and cluster the case's media by it. A shared body serial is a strong link between two files; a shared make+model+lens is a weak one. Use the broad overcast skill and overcast/reference/verbs.md for exact flags. EXIF is free — read it before anything billed.

Workflow

  1. Lift the fingerprint from every image/video. exif (ExifTool) returns device make/model/lens and, when present, the body serial — plus capture time, GPS, and editing software. Loop it over the case's media so every file has an exif record:
overcast doctor --json
overcast case init --json
overcast exif ./photo1.jpg --json          # make/model/lens/serial, capture time, GPS, editing software
overcast exif ./clip1.mp4 --json
for f in ./media/*.jpg ./media/*.mp4; do overcast exif "$f" --json; done   # batch the whole case
  1. Roll the case up by camera fingerprint. devices groups the exif records into shared-device clusters (one entry per file); --min N sets the smallest cluster to report, --findings emits suggested findings for serial-linked (strong) clusters:
overcast devices --min 2 --json            # every camera shared by >=2 files
overcast devices --min 2 --findings --json # + suggested findings for serial-linked clusters
  1. Read the strength honestly, then promote. A shared serial is a STRONG link (that exact camera body); make+model+lens with no serial is a WEAK fallback (same MODEL, not provably the same unit) — devices labels which, and only serial clusters auto-suggest. Triage and record with the right confidence:
overcast finding list --state triage --json
overcast finding accept <id> --target <target-id> --json         # a serial-linked cluster onto its line
overcast note "clip1.mp4 + photo1.jpg share body serial <serial> — same camera (strong); editing-software field set on photo1 → possible re-save" --ref <exif-record-id> --confidence high --json

Read the full file on GitHub · 82 lines

Changes

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.

  1. 7d ago First seen · 82 lines · 65 tokens per session scan A a66523bdf74d

Subscribe to this mod's changes

overcast-camera-ballistics is a skill published in the GitHub repository kdr/overcast (16 stars, last pushed 4d ago), licensed Apache-2.0. It adds 65 tokens to every session and 985 once invoked, about $0.0003 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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