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 music-supervision-scoringgit 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/music-supervision-scoring)<a href="https://agentmods.dev/skills/calesthio/generative-media-skills/music-supervision-scoring"><img src="https://agentmods.dev/badge/skills/calesthio/generative-media-skills/music-supervision-scoring/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/music-supervision-scoring"><img src="https://agentmods.dev/badge/skills/calesthio/generative-media-skills/music-supervision-scoring.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 | $0.00099 | $0.04980 |
| Opus 5 | $0.00049 | $0.02490 |
| Sonnet 5 | $0.00020 | $0.00996 |
| Haiku 4.5 | $0.00010 | $0.00498 |
Grade A, and why
music-supervision-scoring 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 12d 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 — 290 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Music supervision and scoring direction
Treat music as a production decision, not decoration. A strong music plan explains what the audience should feel, where music should enter and leave, what rights path is safe, how the cue will survive edit changes, and how the final mix will protect speech, captions, audio description, and delivery specs.
Use this skill to produce a music supervision plan, score brief, licensed-track shortlist, AI-music prompt, cue sheet draft, mix handoff, or music QA review for audiovisual work.
Evidence labels
Use these labels when making claims or giving recommendations:
- Documented fact: supported by law, standards, official platform docs, PRO guidance, or other authoritative sources. Date volatile facts.
- Empirical observation: based on inspecting the actual edit, stems, waveform, transcript, delivery specs, or generated outputs.
- Production heuristic: a practical recommendation that often works but depends on the brief, audience, platform, and mix.
Do not turn a heuristic into a rule. For example, "trailer drums should always rise" is weak; "this trailer's second act needs rhythmic acceleration because the edit compresses from 3-second shots to 0.8-second shots" is useful.
First pass: define the music job
Before choosing music, answer these production questions:
- Deliverable: format, duration, target platform, aspect ratio, paid/organic use, territory, term, client/brand sensitivity, and whether this is editorial, commercial, internal, broadcast, festival, game, or social.
- Narrative function: what music must do that picture, edit, voice, and sound design cannot do alone.
- Rights path: original score, generated music, stock/library track, licensed commercial recording, public-domain composition with newly licensed recording, client-supplied track, or no music.
- Mix priority: dialogue/narration, on-screen sounds, sound effects, music, captions, audio description, and silence.
- Music identity: genre, tempo range, instrumentation, era, geography, performance texture, harmonic color, density, vocal/instrumental choice, and brand fit.
- Deliverables: full mix, instrumental, no-drums, no-lead, stems, loops, cutdowns, stings, alt endings, and cue sheet data.
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.
- 12d ago First seen · 290 lines · 99 tokens per session scan A b6c94b209dd9
music-supervision-scoring is a skill published in the GitHub repository calesthio/generative-media-skills (170 stars, last pushed 2mo ago), licensed MIT. It adds 99 tokens to every session and 4,980 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.
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