knitbrain_brain_search

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

The description discloses that results are ranked and tagged by store, which adds behavior context. However, with no annotations, it does not explicitly state read-only nature, rate limits, or safety aspects, leaving some transparency gaps.

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 three concise sentences, each adding unique value: function, benefit vs. alternatives, and follow-up action. No wasted words.

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 description covers output format, stores searched, and usage guidance, but fails to explain the 'limit' parameter or ranking details. Given no output schema, a fuller description of return structure would improve completeness.

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 0%, so description must explain parameters. It implicitly describes 'query' but does not mention 'limit' at all, leaving its purpose and constraints ambiguous.

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 it is a unified search across learnings, wiki, and knowledge graph, returning ranked hits with store tags. It explicitly distinguishes from sibling tools like search_learnings, wiki_query, and query_* by noting it replaces multiple calls.

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 provides explicit guidance: use this tool instead of separate search_learnings, wiki_query, and query_* calls. It also suggests drilling into hits with the matching typed tool, giving clear follow-up instructions.

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