ensembl_compara

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 endpoint categories but doesn't describe what the tool actually returns (e.g., tree structures, alignment formats, homology lists), performance characteristics, rate limits, authentication needs, or error conditions. For a complex tool with 8 parameters and multiple analysis types, this is insufficient behavioral context.

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 efficiently structured in two sentences: first stating the broad purpose, then listing endpoint categories. It's appropriately sized for the tool's complexity. However, the endpoint listing could be more clearly integrated with the purpose statement rather than appearing as an afterthought.

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 complex comparative genomics tool with 8 parameters, multiple analysis types, no annotations, and no output schema, the description is incomplete. It doesn't explain what results to expect for different analysis types, how gene trees vs homology vs alignments differ in output, or provide any examples of typical use cases. The agent would struggle to understand what this tool actually returns.

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%, so the schema already documents all 8 parameters thoroughly with descriptions, enums, defaults, and constraints. The description adds minimal value beyond the schema - it mentions endpoint categories that loosely map to analysis_type values but doesn't provide additional parameter context, validation rules, or usage examples. Baseline 3 is appropriate when schema does the heavy lifting.

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 as 'Comparative genomics: gene trees, homology, species alignments, and evolutionary analysis' and mentions specific endpoint categories. It distinguishes from siblings by focusing on comparative genomics rather than feature overlap, lookup, mapping, etc. However, it doesn't explicitly contrast with each sibling tool.

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 provides no guidance on when to use this tool versus the sibling tools. While it mentions endpoint categories, it doesn't explain scenarios where comparative genomics analysis is preferred over feature overlap, sequence retrieval, variation analysis, or other sibling capabilities. No alternatives or exclusions are mentioned.

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