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

Beyond the readOnly/openWorld annotations, the description discloses that live data from certain platforms requires AICI_RESEARCH_PROXY_URL with CN residential routing, and that without it only AliExpress and curated fallback are available. It also specifies input format requirements (platform:id) for seller_profile and price_history, adding valuable behavioral context beyond the 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 long but well-structured: it opens with audience and platforms, then enumerates the five modes in a consistent bullet-like format, followed by a data quality note and input format examples. Each sentence serves a purpose; no fluff or redundancy. It could be slightly more concise, but the organization makes it 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?

Given the tool's complexity (5 parameters, 5 modes, platform-dependent behavior), the description covers all essential context: mode definitions, platform coverage, proxy reliance, and input format specifics. An output schema exists, so the description doesn't need to detail return values. Missing would be auth details or rate limits, but those are not critical for selection and invocation.

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 already provides 100% coverage for all parameters with descriptions, so baseline is 3. The tool description adds extra meaning by detailing valid query formats (e.g., 'aliexpress:123456', '1688:87654321') and clarifying mode-specific behavior for platform and region parameters. This extra context about input syntax justifies a score above baseline.

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's purpose: Chinese e-commerce intelligence across major Chinese platforms, with five explicitly named modes (product_search, seller_profile, price_history, brand_monitoring, market_intel). It specifies the target audience and platform coverage, effectively distinguishing it from sibling tools like china_market_data.

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 provides clear use-case context (diaspora, import-export, brand IP enforcement, sourcing entrepreneurs) and explains what each mode does. It also gives critical operational guidance about proxy requirements for live data and fallback options. However, it does not explicitly compare to alternative tools or state when not to use this tool, so it lacks explicit exclusions.

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