ontomics

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It describes the tool's behavior well by stating it returns a 'ranked shortlist' and 'saves reading dozens of grep matches', which adds useful context about efficiency and output format. However, it lacks details on potential limitations, error handling, or performance characteristics, leaving some behavioral aspects unclear for the agent.

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 with the core purpose in the first sentence, followed by efficiency benefits and usage guidelines. Every sentence earns its place by adding value—explaining what the tool does, why it's useful, and when to use it—without any redundant or vague language. The structure is efficient and well-organized for quick comprehension.

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 (concept location with ranking and contrastive elements), no annotations, and no output schema, the description is mostly complete. It covers purpose, benefits, and usage well, but lacks details on output format (e.g., structure of the shortlist) and potential edge cases. This gap prevents a perfect score, but it's sufficient for basic agent understanding.

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?

The input schema has 100% description coverage, with the parameter 'term' documented as 'Concept to locate (e.g. 'transform')'. The description does not add any further semantic details about the parameter beyond what the schema provides, such as formatting constraints or examples. Since the schema coverage is high, the baseline score of 3 is appropriate, as the description does not compensate but also does not detract.

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', 'returns') and resources ('entry points', 'key functions, classes, and files', 'contrastive concepts'). It explicitly distinguishes from sibling tools by focusing on concept location rather than description, mapping, listing, or tracing, making it easy to differentiate from tools like describe_symbol, concept_map, list_concepts, or trace_concept.

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, listing specific query patterns ('how does X work', 'where should I look for X', 'where are X defined'). It also implies when not to use it by contrasting with sibling tools—for example, use locate_concept for finding entry points, not describe_symbol for detailed descriptions or concept_map for relationships. This clear context helps the agent choose correctly among alternatives.

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