query_simulation_knowledge

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

No annotations are provided, so the description must fully disclose behavioral traits. It only describes purpose and topics, but fails to mention any behavioral aspects such as read-only nature, response format, potential latency, or limitations (e.g., no guarantees on result quality). This is a significant gap for a tool with no safety 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 concise sentences: the first states the action and scope, the second gives usage guidance. No superfluous words; every sentence provides necessary information. It is well front-loaded with the action and primary content.

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 tool's moderate complexity (two parameters, no output schema), the description covers purpose and usage but omits expected output behavior (e.g., returns text answer, list of references) and any constraints (e.g., scope of knowledge base). While adequate for basic understanding, it lacks completeness for robust agent decision-making.

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 coverage is 100% with both parameters having clear descriptions. The description adds value by enumerating the types of knowledge covered (troubleshooting, DFM rules, etc.), which enriches the meaning of the 'question' and 'context' parameters beyond the schema's generic phrasing. This helps agents formulate effective queries.

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 uses a specific verb 'Search' and identifies the resource as 'injection molding simulation knowledge base'. It lists covered topics (troubleshooting, DFM rules, mesh guidelines, process parameter recommendations), clearly distinguishing this general knowledge search tool from siblings that target specific tasks like comparing materials or generating checklists.

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 states 'Use for general questions about molding, simulation setup, or problem-solving', which gives clear context for when to use this tool. However, it does not provide exclusions or alternative tools for cases that are better handled by siblings, so it lacks explicit when-not-to-use guidance.

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