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 ericrisco/rsc-harness --skill ai-mediagit clone --depth 1 https://github.com/ericrisco/rsc-harnessWrote 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/ericrisco/rsc-harness/ai-media)<a href="https://agentmods.dev/skills/ericrisco/rsc-harness/ai-media"><img src="https://agentmods.dev/badge/skills/ericrisco/rsc-harness/ai-media/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/ericrisco/rsc-harness/ai-media"><img src="https://agentmods.dev/badge/skills/ericrisco/rsc-harness/ai-media.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 178 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00082 | $0.03734 |
| Opus 5.5 | $0.00033 | $0.01494 |
| Sonnet 5.5 | $0.00016 | $0.00747 |
| Haiku 4.5 | $0.00008 | $0.00373 |
Grade A, and why
ai-media 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 3d 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 — 181 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ai-media
You are the cross-modal director. You decide which generative-media model to call per modality, in what order, with what params, then assemble the pieces with ffmpeg into one finished file. You do not own a single provider's API surface and you do not prompt still images — you orchestrate and glue.
Pipeline shape — decide what the goal needs
Map the goal to modalities and an ordered step list, and lock that plan before you generate a single asset — media generation is slow and metered, so a re-roll of a 10 s Veo clip or a 90 s music track costs real money and minutes. Fixing the scene list, aspect ratio, target loudness and model per modality first is cheaper than discovering at mux time that your clips are 9:16 and your VO is the wrong sample rate. The "delegate to" column is where the actual call mechanics live — you pick the model and params, those skills run the call.
| Goal | Needs | Ordered steps | Delegate calls to |
|---|---|---|---|
| Narrated explainer | stills + img→video + VO + music | script → per-scene stills → clip per scene → VO → music → conform → concat → mix+duck → loudnorm → MP4 | replicate-images, fal/replicate |
| Product teaser (1 hero) | 1 still + img→video + music | still → clip → music → mix → loudnorm → MP4 | replicate-images, fal/replicate |
| Faceless short | stills + img→video + VO + music + captions | (explainer pipeline) + burn captions | replicate-images; ../video-shorts/SKILL.md for the script |
| Just a voiceover | VO only | script → TTS → loudnorm | — |
| Just a clip from a still | img→video only | still (input) → clip | fal/replicate |
| Code-rendered explainer | none of the above | render from React/TS | stop — route to remotion-video |
If the video is rendered from data/code (charts, timelines, JSON-driven scenes), this is not your job → ../remotion-video/SKILL.md. You handle model-generated + ffmpeg-glued. If the clips will be scrubbed by scroll on a page instead of played as a file, the chain, its seams and the page are ../scroll-film/SKILL.md.
What ships with it
5 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.
- 3d ago Changed 57ae2c68527f
- 1mo ago First seen · 181 lines · 82 tokens per session scan A 8c4d5cca1d94
ai-media is a skill published in the GitHub repository ericrisco/rsc-harness (267 stars, last pushed 2d ago), licensed MIT. It adds 82 tokens to every session and 3,734 once invoked, about $0.0003 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 2026-08-30.
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Use when the user asks for a shared plan, a task needs at least three substantive execution steps, or a loose TODO is pending. Without an explicit plan request, not for one-shot answers or checks, or one- to two-step work that is not already in the list.
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Use when adding a new workflow skill to pi-thinkrail-workflow, changing an existing workflow skill's role, trigger, handoff, or structure, or checking a workflow skill against the workflow system's rules. Not for authoring general-purpose skills outside this package.
writing-specs
Use when a workflow step drafts or revises a spec artifact — a goal-and-requirements, an architecture, or a module SPEC — or when a workflow skill names it at such a step. The shared quality bar for specs — not a workflow, nothing to execute.
setting-up-a-project
Use when asked to set up, onboard, initialize, or spec a project with no spec graph, or when invoked by the app's Set-up-project card. Not for ordinary work in an already-specced project.
release-notes
Write release notes for a tagged release — a business-impact summary of what changed for the user, plus a thanks section naming every contributor whose commits are in the release. Short by construction.