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 media-qc-deliverygit 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/media-qc-delivery)<a href="https://agentmods.dev/skills/calesthio/generative-media-skills/media-qc-delivery"><img src="https://agentmods.dev/badge/skills/calesthio/generative-media-skills/media-qc-delivery/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/media-qc-delivery"><img src="https://agentmods.dev/badge/skills/calesthio/generative-media-skills/media-qc-delivery.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 | $0.00117 | $0.06936 |
| Opus 5 | $0.00059 | $0.03468 |
| Sonnet 5 | $0.00023 | $0.01387 |
| Haiku 4.5 | $0.00012 | $0.00694 |
Grade A, and why
media-qc-delivery 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 13d 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 — 508 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Media QC and delivery
Use this skill at the finish line of media production: after creative approval or near-final assembly, before the files are sent to a client, platform, publisher, broadcaster, streamer, localization vendor, or ad operations team.
Do not invent universal export specs. Delivery is governed in this order:
- The signed client/platform/broadcaster delivery specification.
- The campaign media plan, insertion order, distribution platform, or localization brief.
- Official public platform specs verified for the current date.
- A conservative house mezzanine plus platform-ready derivatives, clearly labeled as a production heuristic.
If the destination is unknown, ask for it. If the user needs a fast default, deliver a high-quality mezzanine plus common web/social derivatives and state that the package is provisional until the destination spec is confirmed.
Evidence labels to use in every QC decision
Separate the basis for each QC call:
- Documented fact: Comes from a client spec, official platform doc, standards body, or file probe. Cite or name the source and verification date for volatile platform requirements.
- Empirical observation: Comes from watching/listening to the asset, reading scopes/meters, test-upload behavior, automated QC output, or a comparison render. Say how it was observed.
- Production heuristic: A practical default used when no binding spec exists. Label it as a heuristic, not a rule.
Example evidence language:
Documented fact: YouTube upload guidance, verified 2026-07-10, recommends uploading at the same frame rate as recorded and lists H.264 High Profile, progressive scan, CABAC, closed GOP, variable bitrate, 4:2:0 chroma subsampling, and audio codec options including AAC-LC, Opus, or Eclipsa for upload encodes.
Empirical observation: ffprobe reports the delivered file is 29.97 fps CFR; visual review shows no cadence judder in the 00:00:07-00:00:12 pan.
Production heuristic: For an unspecified 1080p web review file, H.264 MP4 with AAC-LC stereo at 48 kHz is a low-friction review encode, but it is not a broadcast master.
What ships with it
3 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.
- 13d ago First seen · 508 lines · 117 tokens per session scan A f8969a80361b
media-qc-delivery is a skill published in the GitHub repository calesthio/generative-media-skills (170 stars, last pushed 2mo ago), licensed MIT. It adds 117 tokens to every session and 6,936 once invoked, about $0.0006 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
cliptalk-cover-director
Produces evidence-backed cover candidates and reviewable cover variants for a ClipTalk video. Use when the user asks for a cover, poster frame, thumbnail, or multiple cover directions; do not use for timeline editing or social-video reframing.
cliptalk-smart-reframe
Creates a subject-aware, time-varying crop track and a review-only social-format preview from an accepted ClipTalk cut. Use for automatic vertical, square, or portrait reframing; do not use for a fixed manual crop or before content editing is accepted.
cliptalk-content-extractor
Locates and assembles source passages matching a semantic request. Use for extracting explanations, topics, quotes, demonstrations, or other specifically described content.
cliptalk-interview-editor
Produces a coherent interview edit by combining speaker discovery, topic selection, dialogue context, cleanup, subtitles, and preview. Use for interviews, podcasts, testimonials, or question-and-answer recordings.
cliptalk-shortform-hook-director
Finds and assembles a reviewable short-form cut with a strong opening hook. Use for Shorts, Reels, social clips, talking-head cutdowns, or requests for a punchier opening.
cliptalk-social-reframe-exporter
Creates a review-only 9:16, 4:5, 1:1, or 16:9 version from an existing accepted ClipTalk cut, then checks the rendered preview. Use only when a cut already exists and the user asks to adapt it for Shorts, Reels, Douyin, Xiaohongshu, WeChat Channels, or square feeds; do not use when the user still needs content found…