Get Documentation Topic

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 key traits: it's a read operation ('Fetch'), returns chunked content optimized for LLMs, and implies no destructive actions. However, it doesn't mention potential errors (e.g., invalid IDs), rate limits, or authentication needs, leaving some behavioral aspects uncovered.

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 highly concise and front-loaded in a single sentence, with no wasted words. It efficiently communicates the core action, inputs, and output format, making it easy for an agent to parse and understand quickly.

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 moderate complexity (4 parameters, no output schema, no annotations), the description is reasonably complete. It covers the purpose, input methods, and output format, but lacks details on error handling, performance constraints, or examples, which could enhance completeness for a retrieval tool.

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 fully documents all four parameters. The description adds no specific parameter semantics beyond what the schema provides, such as explaining relationships between 'topic_id' and 'url' or detailing 'max_chunks' behavior. Baseline 3 is appropriate as the schema handles 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 action ('Fetch'), resource ('documentation topic'), and method ('by ID or URL'), distinguishing it from siblings like 'search_docs' or 'list_section_topics' which handle broader queries or lists. It specifies the return format ('chunked content optimized for LLM consumption'), making the purpose explicit and differentiated.

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 implies usage for retrieving specific topics via identifiers, but does not explicitly state when to use this tool versus alternatives like 'search_docs' for broader queries or 'list_section_topics' for section-based listings. It provides context (fetching by ID/URL) but lacks explicit guidance on exclusions or named alternatives.

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