lean_leansearch

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

Annotations already indicate readOnlyHint, openWorldHint, and idempotentHint. The description adds the rate limit constraint, which is useful beyond annotations. It does not describe other behavioral details such as pagination or response format, but with full annotations and output schema, the burden is partially met.

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 extremely concise—three lines: rate limit, purpose, and examples. Every sentence adds value with no redundancy or filler.

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 simplicity (2 params, low complexity), the description is sufficient. It covers core functionality and rate limits. The output is documented via an output schema. Minor gap: no description of the output format, but the schema fills that.

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 coverage is 100%, so the baseline is 3. The description adds example queries but does not enrich parameter semantics beyond the schema (e.g., format of query, interpretation of num_results).

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 explicitly states 'Search Mathlib via leansearch.net using natural language', clearly defining the tool's action and target. Examples further illustrate usage. It effectively distinguishes from sibling tools like loogle and local_search which have different search targets or methods.

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 includes a rate limit (3req/30s) and provides example queries, indicating typical use cases. However, it lacks explicit guidance on when to use this tool over siblings (e.g., lean_loogle, lean_state_search), leaving some ambiguity.

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