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

Annotations declare readOnlyHint, idempotent, and destructive hints, but the description adds behavioral context beyond that: it details what the tool computes (including weekend makeup workdays and multi-day holiday periods from State Council notices) and provides the exact formula for decision-making. It also discloses the output fields and source basis, giving the agent full transparency into the logic and results. 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 fairly long but well-structured with clear sections (use case, exclusions, computation, examples, inputs, outputs, formula, fallback). It is front-loaded with the primary purpose and usage guidance. Each section provides value, though it could be slightly more compact. It scores a 4 for efficiency and organization.

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 simplicity (1 parameter) and the presence of an output schema, the description is thoroughly complete. It includes examples, exclusions, formula, REST fallback, and documentation link. An agent has all necessary information to call this tool correctly and interpret the result.

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% (the date parameter is fully described with format and range). The description adds some extra clarity with examples and a note about the date format, but this largely replicates schema information. The baseline is 3 when the schema does the heavy lifting, and the description does not add substantial new meaning beyond the schema.

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 checks whether a specific date is a working day in mainland China, and explicitly distinguishes from related tools by mentioning exclusion of Hong Kong, Macao, Taiwan, and other calendar types. It uses a specific verb ('check') and resource ('working day in mainland China'), making it distinct from siblings like check_uk_working_day.

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 explicit when-to-use ('when you need to know whether a specific 2024-2026 date is a working day in mainland China, especially around Spring Festival, National Day or another adjusted holiday') and when-not-to-use ('Do not use when you need a Hong Kong, Macao, Taiwan, local minority, school, employer, bank-settlement or stock-exchange calendar, or a year outside 2024-2026'). It also instructs to call the tool directly rather than answering from memory, which is clear guidance.

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