motion-design-video-analysis

motion-design-video-analysis is a skill for Claude Code from desplega-ai/agent-swarm. It costs 107 tokens per session (3,332 once invoked), scanned A, original, MIT.

A workflow for examining a short motion-design or product-update video and writing down how it was made. It produces an analysis and a build specification covering timing, composition, transitions, animation and likely tools.

In plain words
What is it for?
Use it to analyse a clip under a minute, sample its frames, document cuts and transitions, and create a specification for rebuilding the video.
Why use it?
It gives a builder concrete timing and visual details instead of requiring repeated guesswork from the original video.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: positional $N argument.

Part of the agent-swarm plugin — 30 skills, 11 commands, 5 agents, 6 hooks, 1 MCP server shipped together

Good fit Use it to analyse a clip under a minute, sample its frames, document cuts and transitions, and create a specification for rebuilding the video.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/desplega-ai/agent-swarm/motion-design-video-analysis
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 desplega-ai/agent-swarm --skill motion-design-video-analysis
Clone the repo
git clone --depth 1 https://github.com/desplega-ai/agent-swarm

Made for: Claude Code.

Or install agent-swarm, the plugin that ships this one along with the rest of its 30 skills, 11 commands, 5 agents, 6 hooks, 1 MCP server.

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 motion-design-video-analysis

README.md
[![agentmods](https://agentmods.dev/badge/skills/desplega-ai/agent-swarm/motion-design-video-analysis/github.svg)](https://agentmods.dev/skills/desplega-ai/agent-swarm/motion-design-video-analysis)
Your own site
<a href="https://agentmods.dev/skills/desplega-ai/agent-swarm/motion-design-video-analysis"><img src="https://agentmods.dev/badge/skills/desplega-ai/agent-swarm/motion-design-video-analysis/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 motion-design-video-analysis

Your own site · 80×15
<a href="https://agentmods.dev/skills/desplega-ai/agent-swarm/motion-design-video-analysis"><img src="https://agentmods.dev/badge/skills/desplega-ai/agent-swarm/motion-design-video-analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 107 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,332 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe.
Origin original 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 5.1 $0.00107 $0.03332
Opus 5.5 $0.00043 $0.01333
Sonnet 5.5 $0.00021 $0.00666
Haiku 4.5 $0.00011 $0.00333

Measured 14d ago against content hash 7ad53ef3a261, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

motion-design-video-analysis scanned grade A with 1 finding 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 14d 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.

Runs shell commandslowCapability

Expected in a hook, worth knowing in a rule or an instructions file.

grab = lambda t: np.frombuffer(subprocess.run(["ffmpeg","-v","error","-ss",str(t),"-i",v,"-frames:v","1","-vf","scale=640:360","-f","rawvideo","-pix_fmt","rgb24","-"],capture_output=True).stdout,np.uint8).reshape(-1,3)
templates/community/open-prompt-showreel/skills/motion-design-video-analysis/SKILL.md · 116 lines

How it starts

The opening of the file, as written. The whole thing — 116 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Motion-design video analysis

Turns a short (under ~1 min) motion-design clip into two things: an analysis (how it was made and how it feels) and a rebuild spec (numbers someone can build from without reopening the video). Validated on a 28.6 s product-update clip (Linear's "Loops updates") and reused as the judge on a replica of it.

The model is a fast first reader. You are the ground truth. Both models tested on the Linear clip confidently described a "flat 2D view that becomes 3D at 7.5s"; the frames show a 3D scene from t=0. Plan for that class of error.

Prerequisites

  • ffmpeg on PATH. Worker images have a full static build at /usr/local/bin/ffmpeg (has fps, tile, scale, crop, hstack; no drawtext, no ffprobe: read ffmpeg -i stderr, or run the community template's setup.sh to add ffprobe). The Remotion-bundled ffmpeg under node_modules/@remotion/compositor-* is stripped (no fps, tile or hstack); don't use it for analysis.
  • Pixel maths: python3 -m venv /tmp/venv && /tmp/venv/bin/pip install numpy pillow (system pip is blocked by PEP 668; this venv install was run and works).
  • An OpenRouter credential the script can use. In an Agent Swarm, bind it as an egress credential so the key never enters the script (the header Authorization: Bearer [REDACTED:OPENROUTER_API_KEY] resolves at egress in ephemeral script-run only, see Execution notes). Outside a swarm, any way of calling OpenRouter works.
  • Getting bytes off agent-fs: agent-fs download <path> -o <file>. Viewer URLs serve an SPA shell, not the file; use agent-fs signed-url <path> --json when a script needs to fetch it. Upload binaries with agent-fs write <path> --file <local> (binary-safe).

Step 1 — probe the file

ffmpeg -hide_banner -i in.mp4 2>&1 | grep -E "Duration|Stream"

Record container duration, resolution, fps, and whether an audio stream exists. These go straight into the rebuild spec.

Step 2 — audio: verify, then exercise transcription for real

Read the full file on GitHub · 116 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. 14d ago First seen · 116 lines · 107 tokens per session scan A 7ad53ef3a261

Subscribe to this mod's changes

motion-design-video-analysis is a skill published in the GitHub repository desplega-ai/agent-swarm (890 stars, last pushed today), licensed MIT. It adds 107 tokens to every session and 3,332 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-02.

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