get_random_species

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions 'random species' and 'optional taxonomic filters' but doesn't describe what 'random' means (uniform distribution? seeded?), whether results are reproducible, rate limits, authentication requirements, or what format the species data returns. For a tool with 9 parameters and no annotation coverage, this is insufficient.

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 a single, efficient sentence that front-loads the core functionality ('Get random species') followed by key constraint ('from ITIS database') and important feature ('with optional taxonomic filters'). Every word earns its place with zero waste.

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 9 parameters, no annotations, and no output schema, the description is inadequate. It doesn't explain what 'random' means operationally, what data fields are returned, whether results are paginated, or any behavioral constraints. The single sentence leaves too many questions unanswered for proper agent usage.

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 9 parameters thoroughly. The description adds minimal value beyond what's in the schema - it mentions 'optional taxonomic filters' which aligns with the schema's taxonomic parameters, but doesn't provide additional semantic context. 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 verb 'Get' and resource 'random species from ITIS database', making the purpose evident. It distinguishes itself from siblings by focusing on random selection rather than search or exploration functions. However, it doesn't explicitly contrast with all siblings like 'get_statistics' which might also retrieve species data.

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 mentions 'optional taxonomic filters' which implies some context for usage, but provides no explicit guidance on when to use this tool versus alternatives like 'search_by_scientific_name' or 'search_by_vernacular_name'. There's no mention of when random sampling is preferable to targeted searches.

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