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 hassancs91/claude-youtube-editor --skill suggest-sfxgit clone --depth 1 https://github.com/hassancs91/claude-youtube-editorWrote 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/hassancs91/claude-youtube-editor/suggest-sfx)<a href="https://agentmods.dev/skills/hassancs91/claude-youtube-editor/suggest-sfx"><img src="https://agentmods.dev/badge/skills/hassancs91/claude-youtube-editor/suggest-sfx/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/hassancs91/claude-youtube-editor/suggest-sfx"><img src="https://agentmods.dev/badge/skills/hassancs91/claude-youtube-editor/suggest-sfx.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 | $0.00206 | $0.03182 |
| Opus 5 | $0.00103 | $0.01591 |
| Sonnet 5 | $0.00041 | $0.00636 |
| Haiku 4.5 | $0.00021 | $0.00318 |
Grade A, and why
suggest-sfx 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 — 155 lines — stays where its author put it; the contents beside it link to each section on GitHub.
suggest-sfx — the SFX pass
Step 4 of the pipeline: take a video with its master cut + baked visual beats and add tasteful sound effects, synced to the visual beats and the narration, drawn from a shared, growing SFX library. Work collaboratively and beat-by-beat; the user audits the plan and gives notes.
Same shape as the rest of the pipeline: a declarative plan (sfx-plan.json) is the source of
truth → a tool consumes it (tools/mix_sfx.py) → a library grows (media/library/sfx/) → a hard
USER-AUDIT gate before anything is mixed.
Sound taste is a brand contract — read brand.md §10 every time. The house style is calm/premium
(Linear / Anthropic / Vercel), felt-not-heard, always under the voice. NOT MrBeast-loud.
Inputs (read these first, every session)
brand.md§10 (Sound design) — the SFX taste contract: subtlety, density, palette, levels, sync, signature motifs, source policy. Non-negotiable.videos/video-N/work/timeline.json— the shots and their master spans +type(cutaway/overlay). The cut-in/out boundaries are your transition (whoosh) candidates.videos/video-N/work/edited-transcript.json— word-level times (ms) in the MASTER timeline. Sync cues to these words (a pop on "boom", a chime on "free").- The shot sources
remotion/src/shots/video-N/*.tsx— the INTERNAL animation frames are where the real visual beats are (toggle flip, image reveal, page flip, badge pop). Read the shot, convert its local frame to master time:at_s = shot.master_in_s + local_frame / shot.fps. Do not guess — the cue must land on the exact frame the thing happens. media/library/sfx/catalog.json+palette.json— the library you draw from and grow.
The library (media/library/sfx/) — the durable asset
media/library/sfx/palette.json— generation recipes: generic, reusable sound ids + prompts + duration + tags. The source of truth for what the library SHOULD contain.media/library/sfx/catalog.json— the manifest of what EXISTS:{id, file, category, tags, duration_s, peak_dbfs, loudness_lufs, source, model, license, prompt, used_in}per clip. Written bygen_sfx.py.media/library/sfx/clips/*.mp3— loudness-normalized clips (~−20 LUFS, −1.5 dBFS ceiling) so a plan's per-cuegain_dbis perceptually meaningful.- Library-first, always. Reuse an existing clip before generating. Name/tag clips GENERICALLY
(
ui-toggle-on,whoosh-soft,pop-reveal) so future videos reuse them — the library is the durable asset, each video is one draw from it. Only genuinely-missing sounds get added topalette.jsonand generated. (SFX that must live INSIDE a Remotion shot instead go inmedia/library/sfx/viastaticFile().)
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 · 155 lines · 206 tokens per session scan A 49bb5f855f7f
suggest-sfx is a skill published in the GitHub repository hassancs91/claude-youtube-editor (303 stars, last pushed 25d ago), licensed MIT. It adds 206 tokens to every session and 3,182 once invoked, about $0.0010 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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AI video generation with LTX-2.3 22B — text-to-video, image-to-video clips for video production. Use when generating video clips, animating images, creating b-roll, animated backgrounds, or motion content. Triggers include video generation, animate image, b-roll, motion, video clip, text-to-video, image-to-video.
runpod
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