Scenario Agent Skills is a collection of instructions that teaches AI coding agents to create images, video, audio, textures, skyboxes, and 3D assets through the Scenario MCP server, an interface to Scenario’s generation tools and custom-trained models. It serves game, entertainment, marketing, and other creative work, and also includes workflows for digital content creation software and game engines. The catalogue entries are these skills, along with plugins, commands, agents, instructions, settings, and hooks for using Scenario or driving supported creative applications.
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 scenario-labs/skills --skill scenario-maya-fxgit clone --depth 1 https://github.com/scenario-labs/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/scenario-labs/skills/scenario-maya-fx)<a href="https://agentmods.dev/skills/scenario-labs/skills/scenario-maya-fx"><img src="https://agentmods.dev/badge/skills/scenario-labs/skills/scenario-maya-fx/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/scenario-labs/skills/scenario-maya-fx"><img src="https://agentmods.dev/badge/skills/scenario-labs/skills/scenario-maya-fx.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00123 | $0.04480 |
| Opus 5.5 | $0.00049 | $0.01792 |
| Sonnet 5.5 | $0.00025 | $0.00896 |
| Haiku 4.5 | $0.00012 | $0.00448 |
Grade A, and why
scenario-maya-fx 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 20d 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 — 126 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Maya FX (Nucleus, Bifrost, MASH, caches)
An expert FX TD fixes scale and inputs before touching a knob, changes few settings one at a time, never judges a live solve, and proves the result on the cache in numbers (penetration, stretch, pops, convergence) and in renders from the shot camera. If a sibling skill named here is missing from your available skills, ask the user to install it (npx skills add scenario-labs/skills --skill <name>); unattended, proceed from tool schemas and flag the gap.
REQUIRED BACKGROUND: scenario-maya-expert (execution channel, review loop, 2027 version traps).
Status (2026-09-24): Maya 2027 is not installed. The pure-Python layer of scripts/mx_fx.py passed offline (tests/code/maya-fx/test_fx_offline.py); every Maya call is not yet run in Maya; names marked [verify] are answered by job_00_fx_probe.py (python3 tests/code/maya-fx/run_all.py).
Stance (the expert delta)
- Scale before anything. Nucleus and Bifrost compute in meters whatever Maya's unit: Space Scale and
scene_units_in_meters0.01 in a cm scene, or a 182 cm character is 182 m to the solver (2027 Help; SARKAMARI [00:29:22]; Stamatelos [00:30:21]). MPMdetail_sizeis in meters, so a unit change silently changes resolution (Gast [00:07:29]). - Never simulate the production mesh. Duplicate the skinned body and garment, drive the duplicates with a blend shape at weight 1, hide the originals (SARKAMARI [00:10:04]).
- Give the solver a clean start. Hold 25 frames, blend 25 frames into the first pose, action at 0, Nucleus start -50 (SARKAMARI [00:05:26]); Julan: A-pose at 0, walk by 24.
- Substeps before stiffness. Collision iterations below the substep count do nothing; high stretch resistance at low substeps cannot converge (2027 Help, Tips). SARKAMARI's remaining penetration vanished at 30 substeps and 35 iterations, with Space Scale moved to 0.25 in the same pass [00:29:22] [00:29:57].
- Cache, judge the cache, render the cache. nCache before every playblast; the render scene holds Alembics only (SARKAMARI [00:19:32], [00:40:07]).
- Bifrost fails silently. Unpulled outputs are never computed, empty arrays are valid data, mismatched arrays truncate (Jason E3aOt5wuvoo [00:22:49]; Nordenstam [00:38:11]; graph doc). A sim solves only forward from its own start frame: default 1, and it must exist in the timeline (sim guide; Nordenstam [00:56:23]).
- Do not simulate what you do not need. Start a snowball at the collider with its impact velocity (Gast [00:55:18]); layer garments through Alembic colliders (SARKAMARI [00:32:06]); coarse background sources (Stamatelos [00:21:25]).
- One change per run, logged (Jason cd3HgvM8sXg [00:21:43]);
mx_fx.set_attrsreturns the log.
What ships with it
6 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.
- 20d ago First seen · 126 lines · 123 tokens per session scan A fa565f75f427
scenario-maya-fx is a skill published in the GitHub repository scenario-labs/skills (1,034 stars, last pushed today), licensed MIT. It adds 123 tokens to every session and 4,480 once invoked, about $0.0005 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 2026-09-27.
Other skills, from other repositories
motion
Reconstruct a skeleton from calibrated mesh projections and sequential VLM joint annotations, then fit joints and skin weights. Generate motion from joint-position trajectories, rhythm and contact constraints through IK; refine bone orientation against the action, then export, retarget and validate on the target mesh.
3d_object
Judge whether a generated mesh is fit to ship in a browser game, from the same rendered sheet the orientation review uses.
3d_scene
Choose how to build a 3dscene asset. Do not default to one pipeline for every task: what the user specified about the scene's appearance matters more than the scene type, and generative reconstruction is the least stable route here.
cg_video
Use this Skill for text-to-video, first-frame-to-video, first/last-frame transitions, and reference-image-conditioned CG-video generation. Generate video only after the game plan defines its narrative purpose, visual style, shot, duration, and acceptance criteria.
image
Use this Skill when a game plan needs a single-subject concept image, a character reference cleaned for image-to-3D, or a front-facing transparent T-pose image for downstream character reconstruction. T-pose generation is an image-generation and image-editing task; it is not a separate asset category.
audio
Use this Skill when a game plan requires dialogue, voice lines, sound effects, foley, ambience, or other offline WAV assets. This is asset generation, not a runtime audio-playback contract; use the selected engine context after an asset has passed review.