get_api_doc

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

With no annotations, the description carries the full burden. It explains the retrieval and re-ranking behavior, the distinction between recall_num and return_num (with max values), and supported input types (natural language and code snippets). It doesn't state read-only behavior explicitly, but the search/ranking nature and absence of side effects is implied. It doesn't cover error cases or response format, but the output schema covers return structure.

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 well-structured with a front-loaded purpose sentence, a clear 'Args:' section with bullet-point examples, and a concise 'Hints:' section. Each part adds value; no filler or redundancy. The formatting aids readability and 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?

The tool is a search/retrieval operation with 5 parameters, all covered in the description. The description provides use cases, parameter details, and hints. Since an output schema is present, not explaining return values is acceptable. The only minor gap is the lack of explicit mention about read-only nature or potential limitations, but overall it is complete for its complexity.

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 description adds significant meaning beyond the schema. It provides defaults for recall_num (10) and return_num (3), enumerates valid values for language ('Python') and domain ('name'/'description'), and gives illustrative query examples for instructions ('Model.addConstr()' and a description query). Schema descriptions are generic, so the description compensates effectively with concrete usage details.

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: to recall and rank the most similar API docs based on query instructions, specifically for COPT API usage. It distinguishes from sibling tools (get_citation, get_reference) by focusing on API documentation search, and uses a specific verb ('召回并排序') that conveys the retrieval and ranking behavior.

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 ('when you are unclear about COPT's relevant API usage') and provides hints on selecting 'name' vs 'description' fields for different query scenarios. It doesn't explicitly mention when not to use it or name alternatives, but the context and field-level recommendations offer clear guidance.

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