list_topics

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

No annotations are provided, so the description carries full burden for behavioral disclosure. It states the tool lists topics but doesn't describe return format (e.g., list structure, pagination), performance characteristics (e.g., latency for large bases), or side effects (e.g., whether it's cached or triggers updates). This leaves significant gaps for an agent to understand how to handle results.

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 a single, clear sentence with zero waste—it directly states the tool's purpose without fluff or repetition. It's front-loaded and efficiently communicates the core functionality, making it easy for an agent to parse 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 low complexity (0 parameters, no output schema, no annotations), the description is minimally adequate but lacks completeness. It doesn't address behavioral aspects like return format or usage context, which are important even for simple tools. However, it covers the basic purpose sufficiently for a straightforward list operation.

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 0 parameters with 100% description coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, and the baseline for 0 parameters is 4, as it avoids unnecessary detail while matching the schema's simplicity.

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 ('List') and resource ('all knowledge topics in your base'), making the purpose immediately understandable. It doesn't explicitly differentiate from sibling tools like 'get_topic' or 'search_knowledge', but the verb 'List all' implies a comprehensive retrieval rather than filtered search or single-item fetch.

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?

No guidance is provided on when to use this tool versus alternatives like 'get_topic' (for a specific topic), 'search_knowledge' (for filtered queries), or 'query_knowledge' (which might have different semantics). The description implies usage for retrieving all topics but doesn't specify contexts, prerequisites, or exclusions.

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