A modular agent skill for renderer architecture, shader review, GPU profiling, context safety, and visual validation.
Repository | Capability Map | Installation | Validation
Use this skill when a user needs help with:
- WebGL 2.0 renderer architecture
- shader engineering and SDF math
- performance budgets and tiering
- runtime orchestration and context safety
- visual subject audits
- validation, CI, and production hardening
This is not a monolithic handbook stuffed into one prompt. The root SKILL.md is a router. The orchestrator loads only the modules relevant to the current task.
Implicit invocation should trigger on WebGL2 renderer architecture, GLSL shader review, GPU profiling, FBO or postprocess pipeline design, context-loss debugging, DPR/fill-rate optimization, visual regression, and migration planning.
- keep the root skill tiny
- separate invariants from heuristics
- favor measurements over lore
- model parallel and async work honestly
- produce outputs that are usable by both humans and downstream systems
A browser-friendly overview also lives at docs/index.html.
SKILL.md
AGENTS.md / CLAUDE.md / GEMINI.md
LICENSE
CHANGELOG.md / CONTRIBUTING.md / SECURITY.md
.gitignore
agents/
openai.yaml
docs/
index.html
assets/
architecture.svg
skill-infographic.svg
webgl2-systems-hero.png
webgl2-systems-infographic.png
references/
00-orchestrator.md
01-redesign-rationale.md
02-webgl2-source-table.md
skills/core/
01-triage.md
02-hardware-budget.md
03-pipeline-and-concurrency.md
04-subject-audit.md
05-shader-rules.md
06-runtime-ops.md
07-validation-and-ci.md
registry/
forbidden-slop.json
module-map.json
schemas/
authoring-base.json
runtime-compact.json
examples/
*.input.md
*.output.json
fixtures/
webgl2-smoke/
scripts/
validate_repo.py
.github/
ISSUE_TEMPLATE/
PULL_REQUEST_TEMPLATE.md
workflows/
validate.yml
SKILL.mdroutes to the orchestrator.- The orchestrator builds a task record and selects modules.
- Independent lanes can run in parallel:
- hardware and caps
- subject audit
- pipeline and async design
- shader/runtime review
- validation
- The answer is synthesized into prose or JSON.
This skill distinguishes between:
- truly parallel or asynchronous work
- pipelined work
- work that is still serial on a single WebGL context
That means the skill will recommend Promise.all, workers, OffscreenCanvas, or KHR_parallel_shader_compile only when they remove actual waiting, not because "async" sounds fashionable.
mkdir -p .agents/skills
cp -R webgl2-systems-architect-skill .agents/skills/webgl2-systems-architect-skillLoad SKILL.md from the copied folder.
The installed folder name should match the skill name in SKILL.md: webgl2-systems-architect-skill.
If a host prefers alternate entry points, load one of:
AGENTS.mdCLAUDE.mdGEMINI.md
Each wrapper points back to the canonical root skill so logic does not drift.
When structured output is requested, use:
schemas/authoring-base.jsonfor full authoring outputschemas/runtime-compact.jsonfor compact handoff or runtime use
Examples live in the examples/ directory.
The WebGL2 guidance is grounded in the reference matrix at references/02-webgl2-source-table.md. That file links the core modules to MDN WebGL best practices, the Khronos WebGL 2.0 specification, the WebGL extension registry, context-loss guidance, and browser/visual testing references.
The repo includes a small browser fixture at fixtures/webgl2-smoke/index.html. It creates a WebGL2 context, compiles and links one shader pair, draws a triangle, exposes a smoke-test result on window.__webgl2Smoke, and gives future Playwright checks a concrete target.
Run the validator:
python scripts/validate_repo.pyThe GitHub Actions workflow runs the same check on pull requests across Ubuntu and Windows.
Keep SKILL.md metadata, README badges, examples, changelog entries, and GitHub tags synchronized. Use semantic versioning:
- patch: wording, docs, validation, or compatible examples
- minor: new modules, fields, or behavior that remains backward compatible
- major: output schema or routing changes that can break existing consumers
This skill intentionally converts several blanket rules from the source doctrine into measured policies. Examples include:
- context attributes
- DPR caps
- workerization
- reversed-Z usage
- theoretical throughput math
Those are important ideas, but they are not universal constants. The skill treats them as conditional decisions backed by project class, capability detection, and measurements.
Created by Iamemily2050.
- GitHub: Emily2040
- Website: Iamemily2050.com
- X: @iamemily2050
- Instagram: @iamemily2050

