query_organizational_knowledge

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safe, bounded nature is known. The description adds behavioral context by noting it 'Understands natural language questions' and enumerating content types (decisions, documentation, meeting outcomes, technical rationale), which helps the agent anticipate response relevance. No contradiction with annotations.

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 two sentences, front-loaded with the core action, and every word contributes. Examples are compressed and illustrative without redundancy.

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 tool with a nested context object and no output schema, the description covers the main search purpose and natural language capabilities. However, it omits any mention of the optional scoping parameters (context.aboutSystem, aboutProject, aboutEmployee), which are important for narrowing searches. The schema partially compensates, but the description could have been more complete.

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 50%: the 'question' parameter is well-described with examples, but 'context' and its nested properties are not explained in the description. The description's examples clarify the question parameter but offer no guidance on scoping via context, leaving the agent partially reliant on the schema.

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 tool's purpose: 'Search the organizational knowledge base for decisions, documentation, meeting outcomes, or technical rationale.' It also provides specific examples of natural language questions and explicitly positions it as the primary tool for 'why' and 'how' questions, distinguishing it from sibling tools focused on ownership and dependency analysis.

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 gives clear context on when to use the tool: 'Use this as the primary tool for answering "why" and "how" questions about the organization's technical history.' It does not explicitly name alternative tools or exclusions, but the guidance is specific enough to guide appropriate use.

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