Get Database Stats

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

Annotations already indicate read-only, non-destructive, idempotent, and closed-world behavior. The description adds valuable context beyond this: it notes that only verified + partially_verified records are included (unverified reserve data excluded), and clarifies the dynamic nature versus static resources. No contradiction with 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 well-structured with clear sections (DESCRIPTION, USE WHEN, WORKFLOW, RETURNS, NOTE, DIFFERENCE, 中文). It is front-loaded with the core purpose and efficiently covers key points without redundancy, though slightly longer due to bilingual 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 0 parameters, rich annotations, and no output schema, the description provides comprehensive context: it explains what the tool does, when to use it, behavioral details (e.g., record inclusion rules), output structure, and differentiation from alternatives. This fully compensates for the lack of output schema.

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 input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately focuses on usage and output, not parameters, earning a high baseline score for not adding unnecessary information.

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: 'Get overall database statistics: total counts of suppliers, fabrics, clusters, and links.' It specifies the exact resources (suppliers, fabrics, clusters, supplier_fabrics) and distinguishes from siblings like database-overview resource by noting this provides dynamic counts versus static metadata.

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?

Explicit guidance is provided: 'USE WHEN user asks: "how big is your database", "what's the coverage", "data overview", "get_stats".' It also specifies when not to use it (e.g., for static metadata use database-overview, for per-product distribution use get_product_categories) and names alternatives clearly.

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