camsnap

camsnap is a skill for Claude Code, Codex from CodeAndCanvasLabs/Daemora. It costs 16 tokens per session (288 once invoked), scanned A, original, AGPL-3.0.

A camera tool for capturing individual frames or video clips from RTSP or ONVIF cameras.

In plain words
What is it for?
Use it to take snapshots or record clips from RTSP/ONVIF camera streams.
Why use it?
It provides a direct way to save visual footage from compatible network cameras.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/codeandcanvaslabs/daemora/camsnap
Any agent
npx skills add CodeAndCanvasLabs/Daemora --skill camsnap
Clone the repo
git clone --depth 1 https://github.com/CodeAndCanvasLabs/Daemora

Made for: Claude Code, Codex.

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 camsnap

README.md
[![agentmods](https://agentmods.dev/badge/skills/codeandcanvaslabs/daemora/camsnap.svg)](https://agentmods.dev/skills/codeandcanvaslabs/daemora/camsnap)
Your own site
<a href="https://agentmods.dev/skills/codeandcanvaslabs/daemora/camsnap"><img src="https://agentmods.dev/badge/skills/codeandcanvaslabs/daemora/camsnap.svg" alt="Measured on agentmods" height="20"></a>
Per session 16 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 288 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin unknown 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 $0.00016 $0.00288
Opus 5 $0.00008 $0.00144
Sonnet 5 $0.00003 $0.00058
Haiku 4.5 $0.00002 $0.00029

Measured 4d ago against content hash 7b5f900f7f1d, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

camsnap 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 4d 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/camsnap/SKILL.md · 46 lines

The source is not reproduced here

Licensed AGPL-3.0

The repository is licensed AGPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.

Read it on GitHub

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. 4d ago First seen · 46 lines · 16 tokens per session scan A 7b5f900f7f1d

Subscribe to this mod's changes

camsnap is a skill published in the GitHub repository CodeAndCanvasLabs/Daemora (14 stars, last pushed 2mo ago), licensed AGPL-3.0. It adds 16 tokens to every session and 288 once invoked, about $0.0001 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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