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

With no annotations provided, the description carries the full burden of behavioral disclosure, and it delivers: it specifies True Solar Time correction, historical daylight-saving handling, and the tentativeness of the hour pillar when birth time is unknown via the schema. It also makes clear that gender is needed for luck-pillar direction. This is a rich, honest account of how the computation behaves.

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 three focused sentences: the first states the core purpose and outputs, the second explains computation specifics, and the third gives coordinate/city guidance. It is front-loaded with the tool's primary function and every sentence contributes meaningful information without redundancy.

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 tool with 13 parameters, no annotations, and no output schema, the description is strong: it names the full set of return fields and explains the key computational approach. It does not describe the exact structure of the return object or what happens when neither city nor longitude/utcOffset is supplied, but the input schema covers the parameter rules and the listed outputs are broad enough for an agent to understand 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 description coverage is 100%, so the baseline is 3, and the description goes beyond it by explaining the relationship between city and longitude/utcOffset and linking these to true-solar-time accuracy. It adds cross-parameter context that the schema alone does not fully convey, though much of the parameter detail is already present in the schema descriptions.

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 names a specific action ('Compute a full Chinese Bazi chart'), identifies the required inputs (birth date, time, place), and enumerates the detailed output components. It clearly distinguishes this tool from its sibling search_cities, which is only referenced as a helper for resolving city names, not as an alternative computation path.

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 gives actionable usage guidance: use search_cities to resolve a birth city for accurate true solar time, or pass longitude and utcOffset directly. It does not explicitly state when not to use the tool, but there is no competing sibling tool, so the context is clear enough for an agent to select and invoke it correctly.

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

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

No annotations are provided, so the description carries the burden. It states the tool searches a built-in, finite list and names the returned fields: country, longitude, and IANA time zone. This makes the read-only, bounded nature clear, though matching behavior and result limits are not detailed.

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?

Two sentences deliver the core purpose, result contents, and downstream use case with no filler. The most useful guidance (returns fields and compute_bazi_chart integration) appears early and compactly.

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 single-parameter search tool, the description is complete enough: it names the input language options, the source list size, the return fields, and the intended downstream workflow. Since there is no output schema, listing the return fields in prose is especially valuable.

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 description coverage is 100%, and the query parameter already documents types and examples. The tool description adds contextual value by explaining the purpose of the query but does not substantially extend parameter semantics 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 action ('Search the built-in city list') and the resource, with specificity about the ~490 cities and name input. It also distinguishes itself from sibling compute_bazi_chart by positioning itself as the lookup step before that chart computation.

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 explicitly connects usage to compute_bazi_chart: 'so you can pass an exact city to compute_bazi_chart for accurate True Solar Time.' This gives clear context for when to use the tool, though it does not explicitly mention when not to use it.

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