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

It reveals multiple behavioral traits: static curated knowledge base, no LLM-generated answers, no network calls, fallback behavior, and exact return format (answer length, related topic list, source URL). This significantly exceeds what annotations would provide.

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 four sentences, each conveying essential information: purpose, knowledge base nature, output structure, and fallback. It is front-loaded with the primary purpose and remains readable.

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?

Given the simple one-parameter schema and no output schema, the description covers all essential aspects: what it does, how it behaves, what it returns, and fallback behavior. It is sufficiently complete for an agent to use 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 schema has a single 'query' parameter with no enum and no description. The tool description indirectly defines the query by listing the topics it can answer (methodology, deal types, pricing, etc.), which helps the agent construct a relevant query, but it does not explicitly explain the parameter's format or provide examples.

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 answers structured questions about Refpro's methodology and lists specific topics (deal types, pricing, output formats, etc.), making the purpose distinct. However, it does not explicitly contrast with sibling tools, so it doesn't fully achieve sibling differentiation.

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 for methodology questions but provides no explicit guidance on when to use it vs deal_quick_check or sample_report_fetch, nor does it mention exclusions or alternatives.

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