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 linegel/threejs-complete-set-of-skill --skill threejs-compatibility-fallbacksgit clone --depth 1 https://github.com/linegel/threejs-complete-set-of-skillWrote 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/linegel/threejs-complete-set-of-skill/threejs-compatibility-fallbacks)<a href="https://agentmods.dev/skills/linegel/threejs-complete-set-of-skill/threejs-compatibility-fallbacks"><img src="https://agentmods.dev/badge/skills/linegel/threejs-complete-set-of-skill/threejs-compatibility-fallbacks/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/linegel/threejs-complete-set-of-skill/threejs-compatibility-fallbacks"><img src="https://agentmods.dev/badge/skills/linegel/threejs-complete-set-of-skill/threejs-compatibility-fallbacks.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 | $0.00048 | $0.01372 |
| Opus 5.5 | $0.00019 | $0.00549 |
| Sonnet 5.5 | $0.00010 | $0.00274 |
| Haiku 4.5 | $0.00005 | $0.00137 |
Grade A, and why
threejs-compatibility-fallbacks 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 1mo 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 — 134 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Three.js Compatibility Fallbacks
Treat fallback as an explicitly authorized product branch. Canonical WebGPU/TSL work and native WebGPU quality tuning remain with their owning skills.
1. Activate the branch
Record all of the following before selecting an implementation:
- the user's explicit request for unavailable-WebGPU fallback;
- either a positively identified initialized non-WebGPU backend, or a
reproducible capability-related initialization failure on the named target;
record which state occurred, rather than inferring a backend from a missing
isWebGPUBackendproperty; - the canonical owner and exact feature;
- the accepted scope of visual, physical, temporal, interaction, performance, and maintenance loss;
- the compatibility branch's maintenance owner.
Inspect backend identity only after await renderer.init() succeeds. In r185,
renderer.backend.isWebGLBackend === true positively identifies the initialized
WebGL backend; an absent/unknown flag is not proof. When initialization rejects,
record its exact error and leave initialized-backend identity unknown. Route an
application/configuration exception through debugging instead of disguising it
as unavailable hardware. When WebGPU initializes, return to the canonical owner.
Without an explicit fallback request, report the canonical blocker. Clean up the
probe's resources/listeners using the installed API's initialized or partial-init
cleanup path, and use a separate fresh canvas for a different renderer stack.
This step is complete when the five activation facts are recorded and the canonical implementation remains unchanged.
2. Classify canonical behavior
List the canonical feature's geometric, radiometric, color, temporal, interaction, state-ownership, and lifecycle invariants. Classify each one:
preserved: the same quantity and proof still apply;weakened: keep the quantity, name the changed error, support, cadence, staleness, or envelope, and freeze a new gate;removed: mark the capability unsupported and remove dependent claims.
What ships with it
4 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.
- 1mo ago Changed · +16 lines · -1 tokens per session 12180eba12ab
- 2mo ago First seen · 118 lines · 49 tokens per session scan A 994261c1bd2d
threejs-compatibility-fallbacks is a skill published in the GitHub repository linegel/threejs-complete-set-of-skill (11 stars, last pushed 1mo ago), licensed ISC. It adds 48 tokens to every session and 1,372 once invoked, about $0.0002 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 2026-08-31.
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