ontomics

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 effectively describes what the tool returns ('entity names with their domain concept tags'), its semantic understanding capability ('understands which functions *implement* a concept, not just mention it'), and provides example use cases. However, it doesn't mention potential limitations like rate limits, authentication needs, or error conditions.

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 with zero wasted sentences. It front-loads the core purpose, provides behavioral context, contrasts with alternatives, and gives specific usage examples - all in 4 well-constructed sentences that each earn their place.

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 search/list tool with no annotations and no output schema, the description provides excellent context about what the tool does, when to use it, and what it returns. The main gap is the lack of output format details (beyond 'entity names with their domain concept tags'), but given the tool's relatively simple purpose and good parameter documentation, this is a minor omission.

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 4 parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema, but it does provide context about the 'concept' parameter through examples ('e.g. all loss functions, all network architectures'). This meets the baseline expectation when schema coverage is high.

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 ('Find all classes and functions matching a concept') and resources ('entity names with their domain concept tags'). It distinguishes from siblings by explicitly mentioning 'describe_symbol' as a drill-down alternative and contrasting with 'grep alone' which only finds mentions rather than implementations.

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 explicit guidance on when to use this tool vs alternatives: 'Use when asked 'what loss functions exist', 'show me the network classes', 'what uses concept X', or 'list all X''. It also specifies when NOT to use it ('Impossible with grep alone') and names an alternative tool ('describe_symbol') for drilling into results.

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