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

With no annotations, the description carries the full burden. It discloses the core behavior: seven-dimensional weighted scoring and an output of feasibility plus first validation steps. But it does not explain how weights work, what score thresholds mean, how optional parameters affect the result, or the interpretation of the 'can it be done' verdict. This is adequate but has clear gaps.

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 compact sentence with no filler. It front-loads the core action and includes the most important output expectation, making it efficient and easy to parse.

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 input schema is rich and fully documented, and presence of an output schema covers return-format details. However, the description alone does not give enough guidance on when to use the tool or how the scoring behavior is calibrated, so the overall context is not fully complete for an agent.

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%, so the parameter semantics are fully documented in the schema. The description adds no additional parameter-level meaning beyond the schema, so the baseline score of 3 applies.

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-resource pair ('给一个产品想法做七维加权评分') and names concrete outputs ('能不能做 + 要做先验证什么'). It is clear about what the tool does and differentiates it semantically from the sibling tools by focusing on scoring, though it does not explicitly name or contrast those siblings.

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 usage context: it is for scoring a product idea and producing a feasibility verdict with first validation steps. However, it gives no explicit guidance on when to choose this over niche_validation_framework or seasonal_launch_calendar, and no exclusions or alternative conditions.

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