video-use

video-use is a skill for Claude Code, Codex from valtterimelkko/agent-workflow-skills. It costs 139 tokens per session (5,213 once invoked), scanned A, a copy of video-use, MIT.

A conversation-led video-editing workflow that uses speech transcripts and selected visual checks to turn raw footage into an edited video.

In plain words
What is it for?
Use it to remove filler, choose better takes, assemble multiple clips, and refine an edit after confirming the intended approach.
Why use it?
It helps decide where to cut, which takes to keep, and how to combine clips without reviewing every frame first.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions subagents.

Good fit Use it to remove filler, choose better takes, assemble multiple clips, and refine an edit after confirming the intended approach.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/valtterimelkko/agent-workflow-skills/video-use
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 valtterimelkko/agent-workflow-skills --skill video-use
Clone the repo
git clone --depth 1 https://github.com/valtterimelkko/agent-workflow-skills

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 video-use

README.md
[![agentmods](https://agentmods.dev/badge/skills/valtterimelkko/agent-workflow-skills/video-use/github.svg)](https://agentmods.dev/skills/valtterimelkko/agent-workflow-skills/video-use)
Your own site
<a href="https://agentmods.dev/skills/valtterimelkko/agent-workflow-skills/video-use"><img src="https://agentmods.dev/badge/skills/valtterimelkko/agent-workflow-skills/video-use/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.

agentmods 80×15 button for video-use

Your own site · 80×15
<a href="https://agentmods.dev/skills/valtterimelkko/agent-workflow-skills/video-use"><img src="https://agentmods.dev/badge/skills/valtterimelkko/agent-workflow-skills/video-use.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 139 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 5,213 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 86% 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 5.1 $0.00139 $0.05213
Opus 5 $0.00069 $0.02606
Sonnet 5 $0.00028 $0.01043
Haiku 4.5 $0.00014 $0.00521

Measured 12d ago against content hash 357ec49c77c6, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

video-use 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 12d ago.

The scan reads SKILL.md. This mod also ships 7 executable files (helpers/grade.py, helpers/pack_transcripts.py, helpers/render.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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

86% identical to video-use — 27 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.

skills/video-use/SKILL.md · 310 lines

How it starts

The opening of the file, as written. The whole thing — 310 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Video Use

Principle

  1. LLM reasons from raw transcript + on-demand visuals. The only derived artifact that earns its keep is a packed phrase-level transcript (takes_packed.md). Everything else — filler tagging, retake detection, shot classification, emphasis scoring — you derive at decision time.
  2. Audio is primary, visuals follow. Cut candidates come from speech boundaries and silence gaps. Drill into visuals only at decision points.
  3. Ask → confirm → execute → iterate → persist. Never touch the cut until the user has confirmed the strategy in plain English.
  4. Generalize. Do not assume what kind of video this is. Look at the material, ask the user, then edit.
  5. Artistic freedom is the default. Every specific value, preset, font, color, duration, pitch structure, and technique in this document is a worked example from one proven video — not a mandate. Read them to understand what's possible and why each worked. Then make your own taste calls based on what the material actually is and what the user actually wants. The only things you MUST do are in the Hard Rules section below. Everything else is yours.
  6. Invent freely. If the material calls for a technique not described here — split-screen, picture-in-picture, lower-third identity cards, reaction cuts, speed ramps, freeze frames, crossfades, match cuts, L-cuts, J-cuts, speed ramps over breath, whatever — build it. The helpers are ffmpeg and PIL. They can do anything the format supports. Do not wait for permission.
  7. Verify your own output before showing it to the user. If you wouldn't ship it, don't present it.

Hard Rules (production correctness — non-negotiable)

These are the things where deviation produces silent failures or broken output. They are not taste, they are correctness. Memorize them.

  1. Subtitles are applied LAST in the filter chain, after every overlay. Otherwise overlays hide captions. Silent failure.
  2. Per-segment extract → lossless -c copy concat, not single-pass filtergraph. Otherwise you double-encode every segment when overlays are added.
  3. 30ms audio fades at every segment boundary (afade=t=in:st=0:d=0.03,afade=t=out:st={dur-0.03}:d=0.03). Otherwise audible pops at every cut.
  4. Overlays use setpts=PTS-STARTPTS+T/TB to shift the overlay's frame 0 to its window start. Otherwise you see the middle of the animation during the overlay window.
  5. Master SRT uses output-timeline offsets: output_time = word.start - segment_start + segment_offset. Otherwise captions misalign after segment concat.
  6. Never cut inside a word. Snap every cut edge to a word boundary from the Scribe transcript.
  7. Pad every cut edge. Working window: 30–200ms. Scribe timestamps drift 50–100ms — padding absorbs the drift. Tighter for fast-paced, looser for cinematic.
  8. Word-level verbatim ASR only. Never SRT/phrase mode (loses sub-second gap data). Never normalized fillers (loses editorial signal).
  9. Cache transcripts per source. Never re-transcribe unless the source file itself changed.
  10. Parallel sub-agents for multiple animations. Never sequential. Spawn N at once via the Agent tool; total wall time ≈ slowest one.
  11. Strategy confirmation before execution. Never touch the cut until the user has approved the plain-English plan.
  12. All session outputs in <videos_dir>/edit/. Never write inside the video-use/ project directory.

Read the full file on GitHub · 310 lines

Files

What ships with it

30 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 12d ago First seen · 310 lines · 139 tokens per session scan A 357ec49c77c6

Subscribe to this mod's changes

video-use is a skill published in the GitHub repository valtterimelkko/agent-workflow-skills (2 stars, last pushed 2mo ago), licensed MIT. It adds 139 tokens to every session and 5,213 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 0 findings. It is 86% identical to video-use, differing in 27 lines, and is treated as a copy.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens

insight-error-page

Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…

vercel/next.js · 83 tokens