Aris Ingest Models

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

With no annotations, the description carries the full burden. It does disclose a genuinely useful behavioral trait — best-effort semantics and the exact failure payload {"ingested": None} when no engine is reachable. It omits other important traits for a graph-writing tool: whether ingestion is idempotent, whether it overwrites/deletes existing nodes, and any permission or rate-limit constraints.

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

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

The core purpose and the failure behavior are front-loaded in tight sentences. The trailing 'CONCEPT:AU-KG.ingest.enterprise-source-extractor' tag is opaque jargon that costs a line without helping an agent decide or invoke.

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

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

For a mutation tool with no annotations and no output schema, the description covers the purpose, the underlying clients, and the failure mode, which is decent. It still leaves the agent without any idempotency, overwrite, or permission context, so it is only marginally complete for the risk profile.

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

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

Schema description coverage is 100% and the single parameter's schema text already explains both the empty/default (whole inventory) and model_id (single model with EPC objects and flowsTo edges) modes in detail. The description adds no syntax or format meaning beyond that, so the baseline 3 is appropriate.

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

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

States a specific verb (ingest) plus the resource (ARIS models) and the destination (epistemic-graph as typed nodes), which is far more informative than the tautological title. It does not, however, explicitly distinguish itself from the sibling aris_ingest_model_export, which an agent could easily confuse it with.

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

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

There is no when-to-use/when-not guidance and no routing to alternatives. The only usage signal is buried in the params_json schema description (empty → whole inventory, model_id → one model), and even that is parameter behavior rather than tool selection guidance.

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