video-ingest

A guide for reading, importing, analyzing, and comparing WebM, MP4, and GIF recordings with visual and state memory tools. These recordings can come from browser tests, bug reports, or user walkthroughs.

In plain words
What is it for?
Use it to investigate end-to-end test videos, reproduce interface bugs, document multi-step workflows, and diagnose visual changes using key moments, scene changes, and recorded actions.
Why use it?
It turns long recordings into searchable visual and time-based information, making it easier to find the screen state around an interaction or compare a passing run with a failing one.

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/putervision/webcrypt/video-ingest
Any agent
npx skills add putervision/WebCrypt --skill video-ingest
Clone the repo
git clone --depth 1 https://github.com/putervision/WebCrypt

Made for: Claude Code, Codex.

Per session 38 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 893 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 100% copy Near-identical to another mod 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 $0.00038 $0.00893
Opus 5 $0.00019 $0.00447
Sonnet 5 $0.00008 $0.00179
Haiku 4.5 $0.00004 $0.00089

Measured 2d ago against content hash f5979480493f, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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.

Origin

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.

.agents/skills/video-ingest/SKILL.md · 70 lines

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 .webm screenchunks or .mp4 test 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.

Read the full file on GitHub · 70 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. 2d ago First seen · 70 lines · 38 tokens per session scan A f5979480493f

Subscribe to this mod's changes

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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