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 describes what the tool returns ('ordered call chain with file locations and producer/consumer roles') and the tracing mechanism ('shows which functions produce the concept, which consume it, and the call path between them including bridge functions'). However, it doesn't mention limitations like performance impact, memory usage, or whether it requires specific codebase states, leaving some behavioral aspects unclear.

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 two sentences: the first explains the tool's functionality, and the second provides usage guidelines. Every sentence adds value without redundancy, and the purpose is front-loaded clearly. It avoids unnecessary details while covering essential aspects.

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 (tracing concept flow through codebase call chains) and the absence of both annotations and output schema, the description does a good job explaining what the tool does and when to use it. However, it doesn't describe the output format in detail (e.g., structure of the 'ordered call chain') or potential errors, which could be important for an agent to interpret results correctly.

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 schema description coverage is 100%, so the schema already documents both parameters ('concept' and 'max_depth') adequately. The description doesn't add significant meaning beyond what the schema provides, such as explaining what constitutes a valid 'concept' or how 'max_depth' affects results. It only mentions 'concept X' generically, matching 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 ('trace', 'shows', 'returns') and resources ('domain concept', 'codebase', 'function call chains'). It distinguishes from siblings by focusing on tracing concept flow through call chains, unlike tools like 'locate_concept' or 'query_concept' which likely serve different purposes.

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 explicitly states when to use the tool with concrete examples: 'Use when asked 'how does concept X propagate', 'what calls what for X', or 'trace X through the code''. This provides clear guidance on appropriate contexts and distinguishes it from alternatives like 'trace_type' or 'type_flows' which might focus on different tracing aspects.

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