score_products

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

With no annotations, the description carries the full behavioral burden. It discloses the scoring model, default weights, and the special handling for competition and compliance_risk (lower is better, encoded as high scores). However, it does not describe the output format, sorting direction, or behavior with missing/invalid fields.

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 compact and front-loaded: the main purpose appears in the first sentence, followed by a tight parameter breakdown. Every sentence contributes meaningful information with no redundancy or filler.

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 description is adequate for a simple scoring/ranking tool and gives enough input detail to invoke it. However, with no output schema and no annotations, the absence of return-format information and edge-case behavior leaves a moderate gap in 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 coverage is 0%, so the description compensates by documenting each product field with explicit 0-100 ranges and clarifying scoring direction for competition and compliance_risk. It also lists default weights for the optional weights parameter, though it does not specify whether weights must sum to 1 or how custom weights behave.

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 scores and ranks multiple candidate products using weighted multi-criteria, with the specific purpose of aiding product selection. It names the resource ('products') and the operation ('score and rank'), though it does not explicitly differentiate from siblings like scan_market or calc_quotation.

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 phrase '辅助选品决策' implies use during product selection when comparing candidates, but there is no explicit when-to-use guidance, exclusions, or mention of alternative tools. Usage context is inferable rather than stated.

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