Get Hedra Model Details

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, covering the safety profile. The description adds valuable behavioral details beyond annotations: the exact error message format for NOT_FOUND, the return type (JSON object), and the limitation that this tool alone is not enough to construct a valid submit_job call. It does not contradict annotations, and it enriches the agent's understanding of edge cases.

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 well-structured with separate sections (main purpose, alternative guidance, Args, Returns, Error Handling) and is not overly verbose. Each sentence contributes meaningful information. A minor deduction for the redundant Args section that largely mirrors the schema, but overall it is efficient and front-loaded with the core purpose.

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 tool with one parameter, no output schema, and strong annotations, the description covers all essential contexts: what the tool returns (including specific fields), how to handle errors, and its relationship to sibling tools for job submission. The absence of an output schema is compensated by the field list and error format, making the description complete for an agent to invoke the tool correctly.

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 already provides the required 'model_id' with examples and a note to get valid IDs from hedra_list_models. The description's Args section repeats this information without adding meaning beyond a single example. Since the schema carries the semantic load, the description adds minimal incremental value, meeting the baseline of 3.

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 description clearly states the tool's purpose with a specific verb ('Get full catalog details for one Hedra model') and enumerates the exact fields returned (display name, modality, description, capability metadata). It explicitly distinguishes itself from the sibling hedra_get_model_input_schema, making the purpose clear in context.

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?

The description gives explicit when-to-use guidance: it provides a human-readable overview, while instructing to use hedra_get_model_input_schema instead for exact machine-typed parameters needed to submit a job. It also directs users to hedra_list_models for valid IDs and mentions checking it on error. This is a model of clear alternative usage.

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