Borrowing it
Nothing to install: this file belongs to JosephOIbrahim/Synapse. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/JosephOIbrahim/Synapse/master/.claude/skills/solaris-render/SKILL.mdgit clone --depth 1 https://github.com/JosephOIbrahim/SynapseWrote 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/josephoibrahim/synapse/solaris-render)<a href="https://agentmods.dev/skills/josephoibrahim/synapse/solaris-render"><img src="https://agentmods.dev/badge/skills/josephoibrahim/synapse/solaris-render.svg" alt="Measured on agentmods" 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 | $0.00000 | $0.01005 |
| Opus 5 | $0.00000 | $0.00502 |
| Sonnet 5 | $0.00000 | $0.00201 |
| Haiku 4.5 | $0.00000 | $0.00101 |
Grade A, and why
solaris-render 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 6d 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 — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Solaris Scene Rendering Pipeline
Progressive validation pipeline for creating and rendering Solaris scenes via the SYNAPSE MCP connection to Houdini. Do NOT skip stages.
Stage 1: Scene Setup
- Create scene geometry and light rig
- After creation, query the stage and confirm all expected prims exist at correct paths
- List any missing prims before proceeding
- Wire nodes in correct order: geometry -> merge -> materials -> camera -> render_settings -> karma
USD layering gotchas (verified 21.0.671, 2026-05-30)
sublayerLOP ordering is the OPPOSITE of raw USD. It composesfilepathN(highest index) as the STRONGEST layer — whereas rawsubLayerPathsindex 0 is strongest. To make arenderdepartment layer win, fill weakest-first (filepath1=layout … filepath5=render).node.editableStage()isNoneoutside an active Python-LOP cook. It is not a general authoring surface. Author via LOP nodes + parms, read vianode.stage(), and write USD attrs via a pythonscript-LOP (whereeditableStage()IS valid in-cook). A pythonscriptsubLayerPathsedit does NOT compose downstream — use a realsublayerLOP + files instead.
Stage 2: Material Assignment
- Assign materials to geometry using exact USD prim paths (NOT wildcard patterns)
- After assignment, validate by querying each prim's material binding
- Print: prim path + bound material for every assigned prim
- Fix mismatches before proceeding
- Use material library nodes with subnets (not separate matlib + assign)
Stage 3: Render Output Config
- Set up render product and output path
- Set
pictureon the Karma LOP ANDoutputimageon the ROP - Validate the output directory exists and is writable
- Print the resolved output path
Stage 4: Test Render
- Execute a minimal-resolution render: max 256x256, no SSS, no displacement, low samples (4-8)
- Wait for completion with a 60-second timeout
- Do NOT use
soho_foreground=1for heavy scenes (blocks Houdini entirely) - If Houdini becomes unresponsive, report failure and STOP — do NOT attempt higher quality
- Use
iconvert.exefrom$HFS/bin/for EXR-to-JPEG preview conversion
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.
- 6d ago First seen · 72 lines · 0 tokens per session scan A e64c7da186f7
solaris-render is a skill published in the GitHub repository JosephOIbrahim/Synapse (10 stars, last pushed today), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,005 tokens. 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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