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 calesthio/generative-media-skills --skill explainer-video-productiongit clone --depth 1 https://github.com/calesthio/generative-media-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/calesthio/generative-media-skills/explainer-video-production)<a href="https://agentmods.dev/skills/calesthio/generative-media-skills/explainer-video-production"><img src="https://agentmods.dev/badge/skills/calesthio/generative-media-skills/explainer-video-production/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/calesthio/generative-media-skills/explainer-video-production"><img src="https://agentmods.dev/badge/skills/calesthio/generative-media-skills/explainer-video-production.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00098 | $0.06413 |
| Opus 5 | $0.00049 | $0.03207 |
| Sonnet 5 | $0.00020 | $0.01283 |
| Haiku 4.5 | $0.00010 | $0.00641 |
Grade A, and why
explainer-video-production 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 11d 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 — 489 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Explainer video production
Produce an explainer only after defining what the audience should understand, believe, decide, or do differently after watching. Treat the video as a learning and decision artifact, not as a sequence of pretty scenes.
This skill is provider-independent. Use the available generation, editing, composition, captioning, and review tools in the host environment, but keep the explainer logic, factual discipline, accessibility, and QA standards intact across providers.
Non-negotiables
- Start from audience, prior knowledge, and a measurable learning or decision objective.
- Separate documented facts, source-backed inferences, production heuristics, and creative inventions.
- Maintain a claim log for factual, commercial, comparative, health, safety, legal, financial, scientific, and public-service claims.
- Escalate high-risk claims to the client, subject-matter expert, legal/compliance reviewer, medical reviewer, financial reviewer, or policy owner. Do not provide legal, medical, or financial advice.
- Build accessibility into script, storyboard, captions, audio, data visuals, and delivery variants. Retrofitting is weaker and more expensive.
- Re-check volatile provider/platform facts at production time: social aspect ratios, maximum lengths, safe areas, caption behavior, model inputs, model limits, pricing, regional availability, disclosure rules, and rights/licensing terms.
- Never ask an image or video generation model to invent evidence, render precise charts, preserve exact legal/medical/scientific statements, or create readable fine text. Use deterministic layout/composition for facts, citations, captions, tables, UI text, labels, and charts.
Intake: define the learning contract
Before writing or generating, answer:
- Audience: Who is this for, what do they already know, what do they misunderstand, what language/register do they use, and what accessibility/localization needs are known?
- Objective: What single sentence should the viewer be able to say, do, or decide after watching?
- Use case: education, product, onboarding, training, public-service, fundraising, policy, sales enablement, social awareness, internal change management, or technical concept.
- Success evidence: quiz answer, demo completion, reduced support question, sign-up, policy comprehension, behavior change, stakeholder approval, or share/save.
- Constraints: duration, platform, brand, required sources, must-include/must-avoid claims, restricted imagery, voice, captions, languages, review approvers, budget, and tool availability.
- Risk tier:
- Low: general concept, internal orientation, non-sensitive creative explanation.
- Medium: product benefits, nonprofit/public-service behavior guidance, data claims, employment/training requirements.
- High: health, safety, legal, financial, regulated products, children, political persuasion, crisis guidance, comparative advertising, public statistics with policy implications.
What ships with it
1 file 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.
- 11d ago First seen · 489 lines · 98 tokens per session scan A 6f13233a77b8
explainer-video-production is a skill published in the GitHub repository calesthio/generative-media-skills (170 stars, last pushed 1mo ago), licensed MIT. It adds 98 tokens to every session and 6,413 once invoked, about $0.0005 per session on Opus 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 2026-08-30.
Other skills, from other repositories
manim-composer
Trigger when: (1) User wants to create an educational/explainer video, (2) User has a vague concept they want visualized, (3) User mentions "3b1b style" or "explain like 3Blue1Brown", (4) User wants to plan a Manim video or animation sequence, (5) User asks to "compose" or "plan" a math/science visualization.…
video-tutorial-maker
Create scripted tutorial videos with narration, TTS, aligned subtitles, MP4 rendering, and platform variants. Use when Codex needs to create or revise tutorial, explainer, product walkthrough, course, demo, or short-form videos; generate 16:9 landscape output by default unless the user explicitly asks for 9:16, 1:1…
edu-math-tutorial
A Chinese-language guide for turning a maths problem into a step-by-step teaching video. It explains how to break down the solution, write narration, format equations, and structure scenes.
feature-demo-recording
Record a demo video of a web feature from a real browser. Two modes -- a NARRATED film where measured voiceover drives the timeline (designed slides, subtitles, punch-in camera, rendered from an HTML timeline), and a SILENT evidence clip for a PR or a QA pass. Use when the user asks to record a video, demo, or screen…
image-authoring
Author images and diagrams as code — SVG, Pillow, Excalidraw, mermaid. Load when asked to draw, illustrate, or make an image, icon, logo, poster, or diagram.
animation
Author animated technical explainer diagrams as .anim.json files for Nimbalyst's Animation editor. Use when the user wants to animate a diagram, show how a system/protocol/algorithm behaves over time, build a motion explainer, or turn a static architecture diagram into something that plays.