What is video-ingest?

A guide for processing and comparing WebM, MP4, and GIF recordings. It uses video frames and stored state information to examine what happens during a recording.

Use it with browser-test videos, bug reproductions, UI walkthroughs, or passing and failing visual-regression runs.

It helps turn long screen recordings into useful evidence about UI actions, bugs, failed tests, and visual differences.

video-ingest — Skill for Claude Code and Codex by putervision/spc

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.

Any agent

npx skills add putervision/spc --skill video-ingest

Clone the repo

git clone --depth 1 https://github.com/putervision/spc

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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/putervision/spc/video-ingest/github.svg)](https://agentmods.dev/skills/putervision/spc/video-ingest)

Your own site

<a href="https://agentmods.dev/skills/putervision/spc/video-ingest"><img src="https://agentmods.dev/badge/skills/putervision/spc/video-ingest/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/putervision/spc/video-ingest"><img src="https://agentmods.dev/badge/skills/putervision/spc/video-ingest.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 38 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 877 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.

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.

Model	Per session	Once invoked
Fable 5.1	$0.00038	$0.00877
Opus 5.5	$0.00015	$0.00351
Sonnet 5.5	$0.00008	$0.00175
Haiku 4.5	$0.00004	$0.00088

Measured 2mo ago against content hash a4ba4c1c9275, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, 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 2mo 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 — 0 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 · 69 lines

How it starts

The opening of the file, as written. The whole thing — 69 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.

3. Mandatory Dual-MCP Evidence Workflow

When diagnosing bugs or linking test runs to task nodes:

Ingest Video: Call manage_video (action: "ingest") with file path and action timestamps.
Extract Evidence Payload: Read the returned evidence_payload containing source_video_id, frame_range, and timestamps_ms.
Build Evidence Pack: Call create_evidence_pack linking keyframe_state_ids with state-memory-mcp task or blocker node IDs.
Compare Trajectories (On Failure): Call compare_states(video_a_id: "...", video_b_id: "...") to pinpoint exact frame divergence points.

Read the full file on GitHub · 69 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.

2mo ago First seen · 69 lines · 38 tokens per session scan A a4ba4c1c9275

Subscribe to this mod's changes

video-ingest is a skill published in the GitHub repository putervision/spc (20 stars, last pushed 2mo ago), licensed MIT. It adds 38 tokens to every session and 877 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to video-ingest, differing in 0 lines, and is treated as a copy.

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video-ingest next to 6 skills from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
video-ingestputervision/spc	Skill	20	2mo ago	MIT	A	38	Claude Code, Codex
analyzing-packed-malware-with-upx-unpackermukul975/Anthropic-Cybersecurity-Skills	Skill	36k	2mo ago	Apache-2.0	A	88	Claude Code
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analyzing-android-malware-with-apktoolmukul975/Anthropic-Cybersecurity-Skills	Skill	36k	2mo ago	Apache-2.0	A	84	Claude Code
cli-analysisludo-technologies/pyscn	Skill	1.1k	4d ago	MIT	A	59	Claude Code
health-checkludo-technologies/pyscn	Skill	1.1k	4d ago	MIT	A	49	Claude Code