Server Quality Checklist

Tool Scores

• find_legal_specialistsA
  4.1/5.0
  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 that the tool returns canonical profile URLs, that matched categories are always returned separately, and that sending a real inquiry requires user sign-in on legal.ge. It also notes language support, adding behavioral context beyond the schema.

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

  Conciseness4/5

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

  The description is front-loaded with the core purpose and groups related information into four sentences. It includes useful examples and caveats without being overly verbose, though it could be slightly tightened without losing value.

  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 the moderate tool complexity and no output schema, the description adequately covers inputs, outputs, language support, and the sign-in caveat. It would be more complete if it explicitly mentioned how it relates to `classify_legal_intent`, but the purpose and usage are clear enough for an agent to select and call this tool correctly.

  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 coverage is 100%, so the baseline is 3. The description reinforces the meaning of `query` (natural-language description) and `locale` (supports ka/en/ru), but does not add meaningful detail beyond what the schema already provides. It does not explain `limit` behavior beyond the schema.

  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 opens with a specific verb ('Find') and resource ('verified legal specialists in Georgia'), clearly scoping to the country not the US state, and explains the input (natural-language description) and output (matched practice areas and ranked list with profile URLs). This distinguishes it from the sibling `classify_legal_intent`, which likely focuses on categorization rather than finding specialists.

  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?

  Provides explicit usage context: 'Use this tool when a user needs to find a lawyer or legal expert for a specific issue in Georgia' with examples. It also instructs to pass the user's language as `locale`. It doesn't state when not to use or mention the sibling as an alternative, so it's clear but lacks explicit exclusionary guidance.

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

• classify_legal_intentA
  4.4/5.0
  Behavior4/5

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

  With no annotations, the description bears full responsibility for behavioral disclosure. It clearly says the tool does not return specialists and that it returns 'matched categories with parent chains'. This provides concrete expectations beyond the basic purpose. It does not mention error handling or rate limits, but for a read-only classification tool, this is sufficient.

  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 four sentences, each contributing meaningfully: primary purpose, differentiation, usage context, and output detail. It is front-loaded and contains no filler or redundant repetition.

  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?

  Without an output schema, the description explains what is returned (matched categories with parent chains) and how to use it (cite specific service or broader practice area). It also covers when to use the tool. Minor gaps like limits or edge-case behavior are not addressed, but the tool is simple enough that this is reasonably complete.

  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 coverage is 100%: both 'query' and 'locale' have descriptions in the schema. The description adds no extra parameter-level detail beyond rephrasing that the input is a 'free-text legal question'. Since the schema already documents parameters fully, the baseline of 3 applies.

  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 verb 'classify' and the resource 'free-text legal question', with output 'matched practice areas'. It explicitly distinguishes itself from the sibling tool by stating 'without returning specialists' and 'Lighter weight than find_legal_specialists'.

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

  Usage Guidelines5/5

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

  The description gives explicit when-to-use guidance: 'Use this when you want to understand the legal domain of a query before deciding next steps, or when you only need the practice area, not specialist recommendations.' It also implies when not to use (when specialist recommendations are needed) and names the alternative find_legal_specialists.

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