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 agentmods add skills/putervision/webcrypt/video-ingestnpx skills add putervision/WebCrypt --skill video-ingestgit clone --depth 1 https://github.com/putervision/WebCryptWhat 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 | $0.00038 | $0.00893 |
| Opus 5 | $0.00019 | $0.00447 |
| Sonnet 5 | $0.00008 | $0.00179 |
| Haiku 4.5 | $0.00004 | $0.00089 |
Grade A, and why
video-ingest 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 2d 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.
This is a copy
100% identical to video-ingest — 13 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 70 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Video Frame Digesting & Temporal Memory Skill (video-ingest)
This skill provides step-by-step guidance, best practices, and operational patterns for digesting WebM, MP4, and GIF video recordings using @putervision/vision-memory-mcp.
1. When to Use Video Ingestion
Use video ingestion whenever you encounter:
- E2E Playwright / Cypress / Selenium Test Artifacts: Recorded
.webmscreenchunks or.mp4test run videos. - Bug Reproduction Videos: User-uploaded screen recordings demonstrating UI glitches or crashes.
- UI Walkthrough Recordings: Demonstrations of complex multi-step user workflows.
- Visual Regression Diagnostics: Comparing a passing baseline video run against a failing test run.
2. Ingestion Strategies & Parameter Tuning
| Scenario | Recommended Parameters | Why |
|---|---|---|
| Action Event Timestamps (Highest Precision) | action_timestamps: [1.2, 3.5, 7.0] |
Samples keyframes at exact interaction timestamps (clicks, types, navigation events) from test runners or state-memory logs. |
| Dynamic UI / Animations | scene_threshold: 0.3, fps: 1 |
Combines scene-change detection (gt(scene,0.3)) with 1 fps background sampling to capture major screen transitions without frame bloat. |
| High-Speed Test Runs | fps: 2 or fps: 5 |
Increases frame rate sampling for rapidly switching UI test steps. |
| Long Screen Recordings | fps: 0.5, scene_threshold: 0.4 |
Lowers sampling rate to conserve storage while extracting unique keyframe states. |
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.
- 2d ago First seen · 70 lines · 38 tokens per session scan A f5979480493f
video-ingest is a skill published in the GitHub repository putervision/WebCrypt (24 stars, last pushed 11d ago), licensed MIT. It adds 38 tokens to every session and 893 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to video-ingest, differing in 13 lines, and is treated as a copy.
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