brain_search

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

With no annotations provided, the description carries the full burden. It discloses a key behavioral trait: 'if the semantic index is not built they are all that works', revealing a dependency on the index and a fallback limitation. It also notes that variants 'raise recall noticeably', providing insight into search behavior. However, it could add detail on result ranking or pagination, but the core behavioral trait is covered.

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 compact—three sentences—with the core purpose front-loaded. Each sentence adds distinct value: purpose, usage context, and behavioral instruction. There is 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 no output schema and 5 parameters, the description provides the essential context for a search tool: what it does, when to use it, and a critical caveat about the index. It also references usage of variants as a prerequisite for best results. The limit and includeAuxiliary parameters are documented in the schema, so the description need not repeat them. Slight lack of return-format detail is acceptable without an output schema.

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 baseline is 3. The description adds value beyond the schema by explaining the purpose and composition of variants: 'several phrasings of the same concept (synonyms, translation, a broader and a narrower term)' and their impact ('raise recall noticeably'). This enriches the schema's parameter descriptions.

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 opens with 'Finds thoughts by meaning', a specific verb+resource statement. It further distinguishes itself by contrasting with exact title lookup ('rather than exact title'), which clearly separates it from siblings like brain_get_thought.

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 call it: 'Call it when looking for something by description rather than exact title' and gives a concrete example ('check whether a thought on this topic already exists'). It also provides directive usage guidance: 'Always pass variants' with explanation, making the usage context very clear.

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