| ---
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| pretty_name: Aether Build Protocol Examples
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| license: mit
|
| language:
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| - en
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| tags:
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| - manufacturing
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| - fabrication
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| - cad
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| - rfq
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| - mcp
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| - openapi
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| - ai-agents
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| - machine-to-machine
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| - design-to-manufacturing
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| - physical-ai
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| - json-schema
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| - digital-thread
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| - human-in-the-loop
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| task_categories:
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| - text-generation
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| - question-answering
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| size_categories:
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| - n<1K
|
| ---
|
|
|
| # Aether Build Protocol Examples
|
|
|
| Aether Build Protocol Examples is a small public dataset of machine-readable physical build intent artifacts.
|
|
|
| It is designed for AI developers, agent-framework builders, CAD/design workflows, fabrication review systems, and researchers studying machine-to-machine physical transaction protocols.
|
|
|
| GitHub source of truth:
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| https://github.com/chevy155/Aether-build-protocol
|
|
|
| Live demo:
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| https://huggingface.co/spaces/lonestar155/aether-cad-to-agent-sandbox
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|
|
| Open issues / feedback:
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| https://github.com/chevy155/Aether-build-protocol/issues
|
|
|
| ## What is included
|
|
|
| This dataset contains example artifacts from Aether Build Protocol:
|
|
|
| - Build Packet example
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| - Quote Request example
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| - Quote Response example, if present
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| - Human Approval Event example
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| - Machine Response Envelope example
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| - Agent Readiness Report example
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| - M2M Print Transaction Summary example
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|
|
| ## Why this exists
|
|
|
| AI agents cannot safely coordinate physical work from ambiguous PDFs, screenshots, email threads, and loose CAD notes.
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|
|
| They need structured data contracts, permission boundaries, deterministic response envelopes, and human approval gates.
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|
|
| Aether provides example artifacts for the emerging layer between design intent and physical execution.
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|
|
| ## Primary use cases
|
|
|
| - machine-readable physical build intent research
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| - RFQ normalization experiments
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| - quote-response validation
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| - agent-safe manufacturing workflow design
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| - human-gated design-to-fabrication coordination
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| - MCP/OpenAPI manufacturing protocol exploration
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| - digital-thread and provenance research
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|
|
| This dataset is also useful as a small example corpus for an agent-safe design-to-fabrication workflow, an MCP/OpenAPI manufacturing protocol, a human-gated physical transaction pathway, RFQ validation, and quote-response validation.
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|
|
| ## For AI agents and developers
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|
|
| This dataset is intended as a small example corpus for machine-readable physical build intent.
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|
|
| Suggested path:
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| 1. Inspect the examples in this dataset.
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| 2. Open the GitHub repo.
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| 3. Read machine/llms.txt.
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| 4. Inspect the schema index and permission manifest.
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| 5. Run the fresh-clone agent-readiness check.
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| 6. Open an issue with missing fields, unsafe assumptions, or integration suggestions.
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|
|
| ## Guardrails
|
|
|
| These are synthetic examples only.
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|
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| This dataset is a local-only sandbox for structured physical build intent examples.
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|
|
| No real shop was contacted.
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| No quote was routed.
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| No print was approved.
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| No fabrication was approved.
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| No engineering approval was granted.
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| No payment was approved.
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| No load certification was granted.
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| No delivery authorization was granted.
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|
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| Human approval required before any external interpretation or real-world action.
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|
|
| ## Feedback requested
|
|
|
| Useful feedback includes:
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|
|
| - What fields are missing for real fabrication review?
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| - What would a shop need before quoting?
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| - Which schema fields are unclear?
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| - What additional artifacts would help designers and fabricators?
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| - What should an AI agent never be allowed to do in this workflow? |
