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 agentsope/SkillAlchemy --skill agentsope-ai-video-directorgit clone --depth 1 https://github.com/agentsope/SkillAlchemyWrote 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/agentsope/skillalchemy/agentsope-ai-video-director)<a href="https://agentmods.dev/skills/agentsope/skillalchemy/agentsope-ai-video-director"><img src="https://agentmods.dev/badge/skills/agentsope/skillalchemy/agentsope-ai-video-director/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/agentsope/skillalchemy/agentsope-ai-video-director"><img src="https://agentmods.dev/badge/skills/agentsope/skillalchemy/agentsope-ai-video-director.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 | $0.00093 | $0.02953 |
| Opus 5.5 | $0.00037 | $0.01181 |
| Sonnet 5.5 | $0.00019 | $0.00591 |
| Haiku 4.5 | $0.00009 | $0.00295 |
Grade A, and why
agentsope-ai-video-director 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 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.
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 — 221 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Video Director
Activation Rules
Use this skill for an authorized video-production task, including:
- “用一句话做一个 15 秒产品发布视频。”
- “Turn this data into a 30-second animated explainer.”
- “Make a narrated video from these authorized docs.”
- “Write the coding-agent prompt and render this Remotion/HyperFrames video.”
- “The captions overlap in this code-video project; inspect and repair it.”
Do not activate solely for:
- A general question about cinema history or a filmmaker.
- A request to summarize a document with no video deliverable.
- A still-image request with no video intent.
- An unrelated React/Vite bug without a video composition.
- A diffusion-model prompt request alone: that extension has not been distilled.
Agentic Protocol
Execute the following authored application chain (C01–C09). Every step produces a retained result before its dependent step starts. Read operation cards and match each operation’s exact scope before use. Do not turn a source-local case into a rule for a new film.
1. Turn the sentence into a brief
Read prompt fields.
Extract goal, audience, main message, platform, supplied facts, duration/aspect,
language, audio intent, assets, engine preference and delivery requirements.
Preserve explicit values. Mark inferred audience, style and format as assumptions.
If unstated, use these reversible package defaults, subject to user context:
15s for a short product/social draft; 30s for a compact data explanation;
60s for a compact docs/knowledge draft; 30fps; 16:9 for general explainers,
9:16 when vertical social is explicit; original geometric visuals and system fonts.
These values are authored conventions, not evidence-proven creative optima.
Retain supplied facts with their source. Record unknown facts and synthetic placeholders separately.
A missing product metric must not become a fabricated benefit claim.
Clarify only critical facts, permissions or assets that prevent the requested result;
continue a provisional brief and authorized work while those inputs are pending.
Output director_brief with declared, assumptions, facts, unknowns and audio_intent.
What ships with it
26 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.
- examples/data-explainer.md 10 KB
- examples/hyperframes-prompt.md 5.3 KB
- examples/narrated-docs.md 8.8 KB
- examples/product-launch.md 9.7 KB
- examples/remotion-prompt.md 6.1 KB
- examples/sentence-to-director-plan.md 3.9 KB
- LICENSE 1.5 KB
- README.md 7.5 KB
- references/case-studies.md 88 KB
- references/director-playbook.md 37 KB
- references/engine-adapters.md 85 KB
- references/prompt-patterns.md 14 KB
- references/provenance.json 670 KB
- references/quality-rubric.md 15 KB
- references/research_notes.md 7.4 KB
- references/sop_models.md 111 KB
- references/sources.md 72 KB
- references/video-types.md 24 KB
- skill.json 2.3 KB
- tests/engine-routing.json 3.9 KB
- tests/manual-review.md 12 KB
- tests/missing-and-errors.json 3.6 KB
- tests/quality-checklist.md 3.0 KB
- tests/sentence-inputs.json 2.8 KB
- tests/validate_outputs.py 31 KB runs code
- tests/validate_package.py 14 KB runs code
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.
- 14d ago First seen · 221 lines · 93 tokens per session scan A e194e2fb4612
agentsope-ai-video-director is a skill published in the GitHub repository agentsope/SkillAlchemy (445 stars, last pushed 14d ago), licensed MIT. It adds 93 tokens to every session and 2,953 once invoked, about $0.0004 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 2026-10-09.
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