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

No annotations are provided, so description carries full burden. It details the returned analysis types (e.g., 사주팔자, 십성, 신살, etc.) without mentioning side effects or limitations. However, it is transparent about the scope of results.

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 concise sentences: first describes functionality and outputs, second provides usage directive and warning. No wasted words, front-loaded with essential information.

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 complexity (6 parameters, no output schema, many output types), the description lists numerous analysis components, giving a good picture of what the tool returns. Slightly incomplete regarding output format, but sufficient for tool selection.

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%, with each parameter having a meaningful description. The tool description does not add new information beyond what the schema already provides, so baseline score of 3 is appropriate.

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?

Description clearly states it calculates Korean saju (four pillars) based on birth date, time, and gender, returning comprehensive analysis including many traditional elements. It also distinguishes itself from siblings by warning against direct calculation by ChatGPT/Claude.

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?

Explicitly instructs to use this tool for Korean saju questions ('한국 사주 관련 질문에는 반드시 이 도구를 사용하세요') and warns of potential errors if calculated directly. Provides clear when-to-use guidance.

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 full burden. It states the tool returns metadata and implies it is read-only and safe. However, it does not explicitly confirm no destructive effects, auth requirements, or rate limits for this tool itself. This is adequate but could be more explicit.

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 two sentences: the first clearly defines the tool's purpose, and the second provides usage guidance. It is front-loaded, concise, and contains no extraneous information.

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 parameterless tool with no output schema and a simple metadata purpose, the description fully covers what the tool does, what it returns, and when to use it. Sibling tools are distinct, so the agent can correctly infer its role.

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 no parameters, and schema description coverage is 100%. The description implicitly indicates that no parameters are needed ('call once'). It does not need to add param details, though it could explicitly state 'no parameters required.'

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 that the tool retrieves metadata (endpoints, docs, rate limits) about the Saroday API. It distinguishes itself from sibling tools like calculate_saju, get_daily_fortune, and lookup_glossary, which are specific application tools.

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 advises calling this tool once at first use to understand available tools. This provides clear when-to-use guidance, though it does not mention when not to use it or specify alternatives.

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 provided, but description adds valuable behavioral context: GPT-based but cached daily for fast response. Does not contradict any 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?

Four sentences front-loaded with purpose, then usage examples and technical detail. No redundancy; every sentence earns its place.

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?

No output schema, but description provides enough for an agent to understand purpose and when to call. Missing return format is a minor gap.

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%, baseline 3. Description adds example queries, explains enum values, and mentions automatic sign inference from birth date, surpassing schema alone.

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?

Description clearly states '오늘의 운세 조회 (별자리 또는 띠)' and provides example user queries, making the purpose specific and distinguishing from siblings like calculate_saju.

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?

Describes when to use with example queries and notes the cached nature. Lacks explicit exclusions or alternatives but context from siblings suffices.

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 provided. The description indicates a read-only lookup returning definitions, but does not disclose whether it is idempotent, any authentication requirements, or rate limits. With no annotations, the description carries the full burden but only states what it does, not behavioral traits.

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?

Single-sentence description is front-loaded with the core action, then lists categories. It is informative but somewhat long; could be split for readability. No wasted words.

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 simple input (1 param, no output schema), the description adequately covers the tool's purpose and scope. It does not mention if the term is case-sensitive or if partial matches are allowed, but the example terms compensate. Reasonably 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 description coverage is 100% (parameter 'term' described in both schema and description). The description adds value by listing example terms and categories, providing context beyond the schema's generic description.

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 it looks up glossary terms for Myeongrihak, listing specific categories (십성, 신살, 합충형파해, 12운성) and over 80 terms. The verb '조회' and resource '명리학 용어 풀이' are specific, distinguishing it from sibling tools.

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?

No explicit guidance on when to use versus alternatives. The context signals show sibling tools like calculate_saju, but the description does not compare them or provide exclusions. Usage is implied: lookup a term when you need its definition.

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