Server Quality Checklist

Tool Scores

• get_law_articleA
  3.7/5.0
  Behavior2/5

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

  No annotations provided, so description must cover behavioral traits. It only states the function and accepted formats, but does not disclose error handling, required permissions, or whether law_id must exist.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  Single sentence, front-loaded with key information, no wasted words.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness3/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  For a simple tool with 2 parameters and no output schema, the description is adequate. However, it lacks details on return values or error conditions, leaving gaps for the agent.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters4/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema coverage is 100%. The description adds value by noting the accepted formats for article number (e.g., '3', '第3条', '第三条の二', '3の2'), which is not in the schema descriptions.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states the tool retrieves the text of a law article using law_id and article number. It distinguishes from siblings: get_law_structure (structure) and search_laws (search).

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines3/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description implies when to use (to get article text) but does not explicitly state when not to use or provide alternatives. It lacks guidance on comparing with sibling tools.

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

• search_lawsA
  4.2/5.0
  Behavior4/5

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

  With no annotations, the description carries the full burden. It discloses the data source (e-Gov, government database), implies a read-only operation, and explains the two search behaviors. It does not mention rate limits or response format, but for a search tool this is adequate. 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.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is concise: four sentences, front-loaded with purpose, no wasted words. Each sentence adds value—source, modes, post-processing steps.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness4/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given no output schema, the description could explain the result fields more, but it does mention law_id and ties to sibling tools. The search modes are clearly explained. Slightly incomplete for a complex search tool, but still adequate.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters3/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema description coverage is 100%, so baseline is 3. The description reiterates the search_in enum values but adds no new meaning beyond what the schema already provides. It does not elaborate on query or limit beyond schema descriptions.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states the tool searches Japanese current laws from the e-Gov database, distinguishes two search modes (full-text and title), and explicitly connects to sibling tools (get_law_structure/get_law_article) via the law_id. This is a specific verb+resource with sibling differentiation.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines4/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description explains when to use each search mode via the search_in parameter and tells the user how to proceed (pass law_id to siblings). However, it lacks explicit exclusions or alternatives beyond the siblings, so it stops short of a 5.

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

• get_law_structureA
  4.5/5.0
  Behavior4/5

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

  With no annotations, the description bears full responsibility. It clearly describes what the tool does (retrieve structure) and implies it is a read-only operation. It does not discuss side effects, errors, or permissions, but for a simple retrieval tool this is likely adequate.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is extremely concise: two sentences. The first states the core action, the second gives usage context. No unnecessary words, every sentence earns its place.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness5/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  For a simple tool with one parameter and no output schema, the description covers everything needed: what it does, the input, and the use case. The sibling tools provide context. No gaps.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters4/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema coverage is 100% (one parameter: law_id). The description adds value by noting that law_id comes from search_laws results, which helps users obtain the correct value. This goes beyond the schema's basic description.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states the tool retrieves the structural outline (chapters, sections, articles) of a law given its ID, and explicitly mentions its use for browsing which articles to read. It distinguishes itself from sibling tools: search_laws (to find law IDs) and get_law_article (to retrieve a specific article).

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines4/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description implicitly guides when to use: 'どの条文を読むべきか当たりを付けるのに使う' indicates it's for initial orientation. Although it does not explicitly state when not to use or list alternatives, the sibling context and the distinct purpose provide sufficient guidance for an AI agent.

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