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Aris Ingest Model Export

aris_ingest_model_export

Store base64-encoded ARIS model exports as content-addressed knowledge graph blobs, linking them to process models for durable media ingestion.

Instructions

Store a raw ARIS model export (bytes) as a content-addressed KG blob.

The export bytes are supplied base64-encoded (rendered/exported out-of-band by the caller), stored via MediaStore as a :Blob + :ModelExport node linked to its :ProcessModel. Best-effort no-op when no engine is reachable. CONCEPT:AU-KG.ingest.list-durable-media.

Input Schema

NameRequiredDescriptionDefault
params_jsonNoJSON args to store a raw model export blob as a :ModelExport (:MediaAsset): {"model_id":.., "data_b64":<base64 bytes>, "mime_type":"application/xml", "model_name":.., "export_format":"bpmn|aml|svg|pdf"}.{}

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.3.1

TDQS

B3.4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden and does so well: it discloses content-addressed storage, the base64 input contract, the KG linkage to :ProcessModel, and importantly the 'best-effort no-op when no engine is reachable' silent-failure mode. It omits auth/permission requirements and the returned value, so it is not fully complete.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences, purpose front-loaded, and each sentence adds distinct information (storage semantics, input contract, failure mode). Dense internal jargon like ':Blob + :ModelExport node' slightly hurts readability but nothing is wasted.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema and no annotations, so the description should ideally state what the call returns (a blob/asset id) and any auth prerequisites. It covers storage and failure behavior well but leaves the return value and permission model unstated, which is a meaningful gap for an ingest operation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% and the params_json description already enumerates every field (model_id, data_b64, mime_type, model_name, export_format). The prose adds context that the bytes are base64 and out-of-band, but no syntax or field meaning beyond the schema, so the 3 baseline applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource ('Store a raw ARIS model export ... as a content-addressed KG blob') and names the concrete node types it creates (:Blob + :ModelExport linked to :ProcessModel). This clearly separates it from read/list siblings like aris_get_model and aris_list_models, though it does not explicitly contrast with the singular-plural sibling aris_ingest_models.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description notes bytes are 'rendered/exported out-of-band by the caller', which hints at the precondition, but never says when to choose this tool over aris_ingest_models or the attribute-setting siblings. There are no exclusions or alternative-routing guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.