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 sandraschi/blender-mcp --skill pipeline-automationgit clone --depth 1 https://github.com/sandraschi/blender-mcpWrote 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/sandraschi/blender-mcp/pipeline-automation)<a href="https://agentmods.dev/skills/sandraschi/blender-mcp/pipeline-automation"><img src="https://agentmods.dev/badge/skills/sandraschi/blender-mcp/pipeline-automation/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/sandraschi/blender-mcp/pipeline-automation"><img src="https://agentmods.dev/badge/skills/sandraschi/blender-mcp/pipeline-automation.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 | $0.00029 | $0.00621 |
| Opus 5 | $0.00015 | $0.00311 |
| Sonnet 5 | $0.00006 | $0.00124 |
| Haiku 4.5 | $0.00003 | $0.00062 |
Grade A, and why
pipeline-automation 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 — 45 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pipeline Automation Skill
Description: 3D pipeline technical artist skill for batch processing multiple assets with consistent optimization settings. Covers batch rendering, asset pipeline, format conversion, headless batch operations, material baking, and platform-specific export configurations.
Trigger Phrases
- "Batch optimize all assets for [platform]"
- "Export the entire scene for Unity"
- "Bake materials on all selected objects"
- "Convert all FBX files to GLB"
- "Run headless batch render on all cameras"
- "Set up a render farm job for this scene"
- "Apply LODs to all high-poly meshes"
Tools
intelligent_3d_processing(prompt="...")— Multi-step batch processing with natural language prompt. Handles decimation, material unlinking, export, and optimization.optimize_3d_scene(target_platform="...", decimation_ratio=0.5)— Get an optimization plan for a specific platform (Unity, Unreal, VRChat, Web).batch_render(output_path="...", format="PNG", cameras=["..."])— Batch render all or selected cameras.convert_format(input_path="...", output_format="glb", ...)— Convert between 3D formats (FBX, GLB, OBJ, STL, BLEND).apply_modifier(modifier_type="decimate", ratio=0.5)— Apply geometry modifiers in batch.
Workflow
- Target identification: Determine target platform — Unity (Prefab + FBX/GLB), Unreal (FBX + LODs), VRChat (GLB + optimized mesh), Web (GLB with compression).
- Plan generation: Use
optimize_3d_scene(target_platform="...")to get per-platform optimization guidelines (poly count budgets, texture sizes, material limits). - Batch execution: Use
intelligent_3d_processing(prompt="...")to execute decimations, material unlinking, and export in one pass. Specify the platform's format requirements. - Verification: Check export paths and file formats match platform specs. Validate poly counts and texture references.
Examples
Batch Optimization
"Optimize all meshes in the scene for VRChat and export as GLB." → optimize_3d_scene(target_platform="vrchat") → intelligent_3d_processing(prompt="Batch decimate to 50% and export as GLB for VRChat")
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 · 45 lines · 29 tokens per session scan A 3a1eb86aef80
pipeline-automation is a skill published in the GitHub repository sandraschi/blender-mcp (44 stars, last pushed 4d ago), licensed MIT. It adds 29 tokens to every session and 621 once invoked, about $0.0001 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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