query_agent_kb

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

No annotations are provided, so the description must carry all behavioral context. It mentions AI-powered semantic search and citations, but does not explain that results are stored in a variable (as per output_variable_name parameter), nor any limitations or cost considerations. Adequate but not thorough.

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 a single, clear sentence that front-loads the purpose and core functionality. Every word contributes meaning, with no fluff or repetition.

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?

With 5 parameters, no output schema, and no annotations, the description is brief but covers the main purpose. However, it lacks details on how the output variable works (output_variable_name) and how metadata filtering is used. More context 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 description coverage is 100%, meeting the baseline. The description adds general context (AI search, citations) but does not elaborate on any specific parameter beyond what the schema already provides. No added semantic value for parameters.

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 the action (search/recall), the resource (agent's memories), and the method (AI-powered semantic search). It mentions output includes citations, which helps distinguish it from related tools like list_agent_memories or save_to_agent_kb.

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 implies the tool is used for recalling past context via semantic search, but it does not explicitly differentiate from siblings like list_agent_memories. No when-not or alternative usage is provided, leaving the decision partially to the agent's inference.

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