Goose Skills is a library of workflows and data APIs that lets coding agents handle growth and go-to-market work such as advertising, social media, content, SEO, lead generation, and customer research. It is intended for teams using Claude Code, Cursor, Codex, and similar agents. The catalogue entries are its reusable skills.
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 gooseworks-ai/goose-skills --skill render-3d-character-explainergit clone --depth 1 https://github.com/gooseworks-ai/goose-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/gooseworks-ai/goose-skills/render-3d-character-explainer)<a href="https://agentmods.dev/skills/gooseworks-ai/goose-skills/render-3d-character-explainer"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/render-3d-character-explainer/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/gooseworks-ai/goose-skills/render-3d-character-explainer"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/render-3d-character-explainer.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 | $0.00295 | $0.02145 |
| Opus 5 | $0.00148 | $0.01073 |
| Sonnet 5 | $0.00059 | $0.00429 |
| Haiku 4.5 | $0.00030 | $0.00215 |
Grade A, and why
render-3d-character-explainer 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 11d 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 — 108 lines — stays where its author put it; the contents beside it link to each section on GitHub.
render-3d-character-explainer
The free, deterministic renderer for the 3d-character-explainer video ad format — the glossy Pixar-style 3D spot built on an "N types of X" listicle spine, where a recurring human protagonist plus a locked cast of N persona characters (one per list item) carry a hook → "deeper story" → cast-reveal → one beat per list item → kicker → product test → relieved payoff. This capability is the FREE assembly stage only. All generative work (Nano-Banana cast anchors + per-scene keyframes, Kling-V3 i2v clips, ElevenLabs VO + music, or a source ad's audio reused verbatim) happens upstream in the recipe and is handed to this capability as files.
It ports the validated compose recipe from the Bristle "Six Types" restyle run
(_render_full.sh — per-scene trim → normalize 1080×1920/fps30 → concat -c copy → mux the
source audio, with a static-still fallback on any failed clip). The assembly is
deterministic — iterate the cut for free, re-roll only the offending paid beat.
Two modes
- Restyle mode (
audio_mode: "restyle", the reference run) — re-tell a finished source ad, beat for beat, as 3D character comedy. The source ad's audio mix (VO + music bed) is reused VERBATIM (source_audio), and the per-scenetarget_sectable is inherited from the source's scene timing. No new VO or music is rendered. The trims must sum to the source audio length. - Original mode (
audio_mode: "original") — the ad authors its own narration. Each scene carries a measured VO cue (scenes[].vo,target_sec= the ffprobe'd VO duration) which is concatenated into a VO track (loudnorm I=-14) and optionally mixed under amusic_bed(loudnorm I=-26 thenvolume,amix normalize=0).
What it does (the deterministic recipe)
- Per-scene retime. Each i2v clip is trimmed to its scene
target_secand normalized to identical dims/fps/SAR (scale=W:H:force_original_aspect_ratio=decrease,pad=W:H:(ow-iw)/2:(oh-ih)/2:color=<pad>,fps=30,setsar=1). A clip shorter than its window is extended withtpad=stop_mode=clone; a longer one is-ttrimmed. Decrease+pad (never crop) preserves the full 9:16 keyframe framing. - Static-still fallback. For any scene whose
clipis missing or failed to render, the scene'skeyframePNG is looped (-loop 1) fortarget_sec, so the master always assembles. Fallback scenes are printed at the end. - Identical re-encode + concat. Every segment is re-encoded
libx264 -crf 18 -pix_fmt yuv420p -r 30even if already correct — a dims/framerate mismatch makes the concat demuxer silently drop frames — then concatenated via the concat demuxer (-c copy). - Audio. Restyle:
source_audiomuxed verbatim (-map 0:v -map 1:a), clamped to the video length. Original: per-scene VO track (optionalatempo,apad,-tclamp) → loudnorm → optionally mixed under the music bed. - Captions last.
make_captions.pyemits a libass.ass(one cue per scene,start = scene_start + 0.08s, suppressed on any scene with no caption — e.g. a product/end-card beat carrying its own typeset copy).compose.pyburns it as the final filter so captions sit on top. Word-level energy-pop captions (Whisper on the narration) are the recipe's upstream option — produce that.assexternally and pointcaptions_assat it; compose burns whatever.assit's handed.
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.
- 11d ago First seen · 108 lines · 295 tokens per session scan A 045c929fbf7a
render-3d-character-explainer is a skill published in the GitHub repository gooseworks-ai/goose-skills (1,201 stars, last pushed 10d ago), licensed MIT. It adds 295 tokens to every session and 2,145 once invoked, about $0.0015 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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