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

No annotations are provided, so the description carries the full burden of behavioral disclosure, and it delivers thoroughly. It discloses the return format, the 20-category scope, the deliberate non-hardcoding of inventory numbers (pointing the agent to initialize/GET /mcp to avoid copy drift), the substring/non-fuzzy/non-correcting keyword semantics with concrete failure examples, exact-match category behavior with alias pitfalls, and the default exclusion of 3 market-intelligence entries. This is exemplary behavioral transparency that directly prevents agent mistakes.

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, front-loaded with purpose before scope and caveats. Every sentence earns its place, including the pragmatic inventory-drift caveat which prevents stale hardcoded numbers. It is appropriately sized for the tool's complexity and does not pad or repeat schema 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?

For a 4-parameter search tool with no annotations and no output schema, the description is largely complete: purpose, filters, return fields, category scope, and a guidance pointer for inventory. The main gap is the absence of explicit differentiation from semantic_search, a close sibling whose matching behavior could confuse an agent; mentioning when to use each would make this fully 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 coverage is 100% and the schema descriptions are themselves exceptionally rich (concrete examples, matching semantics, alias caveats). Since coverage is high, baseline is 3. The description adds marginal but real value by specifying what the summary return contains and the 20-category coverage, which helps an agent choose keyword/category values. It does not contradict the schema and complements rather than repeats it.

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 states a specific verb and resource ('搜索机器人零部件' – search robot components), lists the filter dimensions (category, keyword), and specifies the returned summary fields (id/name/category/manufacturer/key specs/evidence level). It is clear, but it does not explicitly name a sibling it is not – notably semantic_search, which is the closest alternative and likely differs on matching semantics. The keyword param's '非模糊' (not fuzzy) hint implies the differentiation without naming it.

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?

Parameter-level usage guidance is excellent: keyword explains substring matching, the disjoint Chinese/English result sets with concrete test data ('六维力' hits 16, 'force torque' hits 2, intersection 0), and the single-word-then-narrow-by-category recommendation ('harmonic drive 20Nm' returns 0, 'harmonic' returns 9). Category explains exact-match semantics and that category does not map 1:1 to ID prefixes. However, there is no tool-selection guidance – the description never says when to prefer this over semantic_search or get_component_detail, so no exclusions/alternatives are stated.

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