HydraMCP

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions parallel querying and synthesis but omits critical details like rate limits, authentication needs, error handling, or the synthesis process. The claim 'better than any single model' is vague and unsubstantiated.

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 and concise, using two sentences that efficiently convey the core functionality and outcome without unnecessary details. Every sentence adds value by explaining the process and benefit.

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?

Given the tool's complexity (6 parameters, no annotations, no output schema), the description is incomplete. It fails to explain behavioral traits, parameter interactions, or output format, leaving significant gaps for an AI agent to understand how to use it effectively beyond basic purpose.

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 50%, and the description adds no parameter-specific information beyond what the schema provides. It mentions querying 2-5 models and combining ideas, which aligns with the 'models' and 'prompt' parameters but does not explain other parameters like synthesizer_model or system_prompt. Baseline 3 is appropriate given the schema handles some documentation.

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 specific verbs ('query', 'combine', 'synthesize') and resources ('models'), and distinguishes it from siblings by emphasizing parallel querying and synthesis of multiple models into a superior answer, unlike simpler tools like ask_model or compare_models.

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 implies usage when needing a better answer than any single model provides, but lacks explicit guidance on when to choose this over alternatives like consensus or compare_models, and does not mention prerequisites or exclusions.

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