search_knowledge

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

With no annotations, the description carries the full burden. It specifies that the search is case-insensitive and returns matching topics and relevant lines. It also states it searches all saved knowledge, which is important behavioral context.

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 concise, well-structured with Args and Returns sections, and every sentence adds value. No unnecessary details.

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 explains the return value, and the output schema is present. It covers the essential aspects of the tool, though it doesn't mention potential size limits or pagination, which is acceptable for this tool.

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 schema has one parameter 'query' with no description. The description adds that the search is case-insensitive, providing semantic value beyond the schema. With 0% schema coverage, this compensation is appropriate.

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 searches saved knowledge for specific information, using the verb 'search' and resource 'knowledge'. It distinguishes from sibling tools like get_all_knowledge and save_knowledge.

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 a use case: 'finding previously learned information about specific tables, columns, or concepts'. However, it does not explicitly mention when not to use or suggest alternatives among the many sibling tools.

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