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 skills add suryast/free-ai-agent-skills --skill narrated-motion-explainersgit clone --depth 1 https://github.com/suryast/free-ai-agent-skillsWrote 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.
[](https://agentmods.dev/skills/suryast/free-ai-agent-skills/narrated-motion-explainers)<a href="https://agentmods.dev/skills/suryast/free-ai-agent-skills/narrated-motion-explainers"><img src="https://agentmods.dev/badge/skills/suryast/free-ai-agent-skills/narrated-motion-explainers/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.
<a href="https://agentmods.dev/skills/suryast/free-ai-agent-skills/narrated-motion-explainers"><img src="https://agentmods.dev/badge/skills/suryast/free-ai-agent-skills/narrated-motion-explainers.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00055 | $0.00954 |
| Opus 5.5 | $0.00022 | $0.00382 |
| Sonnet 5.5 | $0.00011 | $0.00191 |
| Haiku 4.5 | $0.00006 | $0.00095 |
Grade A, and why
narrated-motion-explainers 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 5d 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.
How it starts
The opening of the file, as written. The whole thing — 38 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Narrated motion explainers
Deliver a video, not merely a renderer
- Establish audience, one message, runtime cap, aspect ratio, and narration rights. Write a fresh brief and short chapter script; retain source notes for factual claims without copying full source pages.
- For narration, obtain an authorized local recording or optional TTS output. Measure audio with ffprobe before setting chapter durations. Do not invent speech timing from word counts. Keep any external TTS provider optional; never bundle credentials. Match captions to actual speech, restoring punctuation only after token alignment and clamping overlapping cues.
- Render a short preview first. Use deterministic scene state at time
t, RGB Pillow frames, and FFmpeg rawvideo input. Animate the explanatory subject, not only the background or caption strip. Use legible captions, bounded text, and licensed fonts; avoid distributing font binaries without permission. - Encode H.264/yuv420p plus AAC at an explicit 48 kHz sample rate. Bound output duration and processing time. Preserve chapter JSON, captions, renderer and audio beside the MP4 so visual rerenders do not require network access.
- Probe the actual output's duration, dimensions, frame rate, codecs and audio. Decode the entire MP4. Extract paired interior frames per chapter and check subject motion separately from captions. Inspect decoded frames for clipping, layout and synchronization; a passed Python run is not video verification.
- Deliver the real verified MP4 plus source/caption assets, brief, source/rights notes and measured results. If narration is unavailable, label the output a tone/silent motion demo, not a narrated video. Do not ship a virtualenv, credentials or copyrighted source snapshots.
Runnable offline sample
The fresh sample explains a three-stage packet route in six seconds. Its generated quiet synthetic tone is not voiceover. render.py produces an MP4, WAV (tone mode), chapter copy and SRT. verify_video.py probes and fully decodes it, checks per-chapter subject motion, and saves decoded inspection PNGs. Dependencies are in requirements.txt; the brief is sample.json.
What ships with it
4 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.
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.
- 5d ago First seen · 38 lines · 55 tokens per session scan A 565ac75d38cc
narrated-motion-explainers is a skill published in the GitHub repository suryast/free-ai-agent-skills (2 stars, last pushed 6d ago), licensed MIT. It adds 55 tokens to every session and 954 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-11.
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