search_knowledge_base

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

No annotations are provided, so the description carries the behavioral transparency burden. It discloses that the search spans all knowledge base files and returns matching sections from both reference docs and book extracts, which gives useful behavioral context. It doesn't describe edge-case behavior like no matches or result formatting, but for a read-only search tool the disclosed behavior is reasonably complete.

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 and well-structured: the purpose is front-loaded, followed by when-to-use guidance, parameter details with examples, a KB reference, and a usage example. Every section earns its place with no 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?

For a simple one-parameter search tool with an output schema present, the description covers the tool's purpose, trigger conditions, parameter semantics, examples, and a KB pointer. Nothing critical is missing for an agent to select and invoke the tool correctly.

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 only defines query as a string with no description, so schema description coverage is 0%. The description compensates by defining query as a 'Keyword or phrase to search for' and providing six concrete examples such as 'behavior tree task' and 'blend space,' making the expected input much clearer.

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 states a specific verb and resource: 'Search across all knowledge base files for a keyword or phrase.' It also clarifies that it returns matching sections from both hand-written reference docs and book extracts, which distinguishes it from sibling tools like list_knowledge_base_topics or get_knowledge_base that are about browsing or retrieving whole topics.

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 tells the agent when to use it: 'Use this when you need a specific term, function name, pattern, or concept and don't know which topic file covers it.' It gives a clear trigger condition, though it does not name alternative tools or explicitly say when not to use it, so it falls just short of a 5.

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