get_model

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

With no annotations, the description carries full responsibility, and it discloses key behaviors: it returns data for any status, error is non-null only when status is 'failed', and the configuration echo omits some accepted create_model inputs. This is substantive behavioral context beyond the bare 'get' action.

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 description is front-loaded with the essential scope and usage, then organized into returns and caveats with clear formatting. The length is justified because there is no output schema to carry the return-field details.

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 one-parameter read tool with no annotations and no output schema, the description provides comprehensive detail: behavior, return fields, failure semantics, and a known caution about omitted echo fields. Nothing required to call it correctly is missing.

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?

The only parameter, model_hash, is described in Args with the added semantic 'any status', clarifying that the tool works with failed models. Schema coverage is 0%, but the single parameter is simple and the description gives enough context for correct invocation, though it does not give a format or example.

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?

The first sentence names the action ('Get'), the resource ('model's metadata and configuration echo'), and scope ('works for EVERY status, including failed models'). It explicitly differentiates from get_model_results, which needs status 'complete', so an agent can disambiguate without reading definitions of other tools.

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?

It states concrete use cases: inspect configuration, diagnose failure, or locate a model. It also names the alternative get_model_results as not applicable to failed models, giving an explicit when/when-not condition. The note about checking financials results for stored margin adds additional guidance.

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