Server Quality Checklist

Tool Scores

• get_companyA
  4/5.0
  Behavior3/5

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

  With no annotations, the description carries the burden of behavioral disclosure. 'Get' implies a read-only operation, and 'enrichment data' hints at additional information, but no details on caching, permissions, or error behavior are provided. This is minimally transparent but not misleading.

  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 a single sentence followed by a one-line argument explanation. Every word earns its place, and the main purpose is front-loaded.

  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 tool has only one parameter and an output schema exists, the description is sufficiently complete. It explains the core function and the parameter, though 'enrichment data' is vague. It covers what is needed for a simple lookup tool.

  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?

  The schema only says 'Company Id' (type string), while the description adds 'The unique identifier of the company (employer_id)' which clarifies the semantic meaning. Since schema coverage is 0%, the description compensates well for the single required parameter.

  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 'Get detailed information about a specific company, including enrichment data', which is a specific verb+resource. It distinguishes itself from sibling 'search_companies' by focusing on retrieving one known company rather than searching.

  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 usage when a specific company_id is known, but does not explicitly state when to use this tool versus alternatives like search_companies. It provides clear context but lacks explicit exclusion or alternative guidance.

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

• get_jobA
  4/5.0
  Behavior3/5

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

  With no annotations, the description must carry the transparency burden. It discloses that the return includes the job's full description, but it does not mention other behavioral aspects such as read-only status, auth requirements, rate limits, or potential errors. For a simple getter, this is adequate but not exhaustive.

  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 highly concise: one sentence stating the purpose, followed by a brief Args section. The main purpose is front-loaded, and every word earns its place. No unnecessary repetition or fluff.

  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 tool's simplicity (one parameter, clear purpose) and the presence of an output schema, the description is sufficiently complete. It covers what the tool does and the parameter. It does not address error cases or non-usage scenarios, but these are less critical for a single-job retrieval tool.

  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?

  The description explains that job_id is 'the unique numeric identifier of the job,' adding semantic meaning beyond the schema's type integer and title. This clarifies the purpose and uniqueness of the parameter, which is the only parameter. The added meaning compensates for the empty schema 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 states 'Get detailed information about a specific job, including its full description,' which clearly identifies the verb (get), the resource (job), and the scope (specific job by ID). The explicit mention of 'full description' adds specificity and distinguishes it from search_jobs, which is a search/filter operation.

  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 usage for retrieving a specific job, but it does not explicitly state when to use this tool over search_jobs or provide exclusions or prerequisites. The context is clear enough for basic use, but guidance on when not to use it is missing.

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

• suggest_locationsA
  4.3/5.0
  Behavior3/5

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

  With no annotations, the description carries the full burden. It accurately describes a read-only lookup operation and the purpose, but does not disclose behaviors such as response format, error handling, or edge cases (e.g., no matches). It is not misleading, but it lacks depth beyond the basic action and parameters.

  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 compact and well-structured: a one-sentence purpose followed by a clear argument list. Every line earns its place, with no redundant information or fluff.

  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 tool's simplicity (3 parameters, no output schema, no annotations), the description covers the essential context: purpose, relationship to search_jobs, and parameter details. It does not explicitly describe the return value format, but for a location ID lookup the purpose implies the return type. Overall, it is sufficiently complete for an AI agent to select and invoke the tool; a small margin for improvement remains.

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

  Parameters5/5

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

  Schema description coverage is 0%, so the description fully compensates by clearly explaining each parameter: 'query' (search query with examples), 'kinds' (location types, default all), and 'limit' (max results, 1-30). It adds value beyond the schema, including defaults and constraints.

  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's function: 'Look up city/state/country IDs by name for use in search_jobs filters.' It uses a specific verb ('look up'), identifies the resource (location IDs), and explicitly ties it to a sibling tool (search_jobs), distinguishing it from the other search/retrieval tools.

  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 provides clear usage context by stating the purpose is 'for use in search_jobs filters.' This implies when to use the tool (before calling search_jobs with location filters). However, it does not explicitly mention alternatives or when not to use it, though the sibling tools are obviously different in scope.

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

• search_jobsA
  4.4/5.0
  Behavior4/5

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

  With no annotations, the description carries the burden of behavioral disclosure. It covers pagination cursors, default limit/count behavior, the extra query cost of count=true, and include_description being excluded by default. It does not mention auth/rate limits, but these are not critical for a read-only search, and the output schema covers return shape.

  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 front-loaded with a one-sentence purpose, then a concise pagination note, then a clear bulleted arg list. For a tool with 22 parameters, it is well-organized and every line provides necessary information without filler.

  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 complex 22-parameter search tool with no annotations and no schema descriptions, the description is highly complete. It explains pagination, parameter dependencies, defaults, and behavioral caveats. Combined with the output schema, an agent has enough information to invoke search_jobs correctly.

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

  Parameters5/5

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

  Schema description coverage is 0%, so the description must fully compensate. It documents all 22 parameters with specific meanings, allowed enum values (remote_type, experience_level, employment_type), syntax for max_age, and semantic details like location being used only when no IDs are provided. This goes far beyond the raw 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 'Search for jobs using the CleanJobData API,' which clearly states the verb ('search') and the resource ('jobs'). It is distinct from siblings like get_job (fetching a single job) and search_companies (searching companies), so an agent can easily differentiate when to select this tool.

  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?

  While the description provides useful usage context (e.g., pagination cursor flow, suggest_locations for IDs, and sort_by requiring title), it does not explicitly compare against alternatives or state when not to use search_jobs versus get_job or search_companies. The appropriate use is implied rather than directly contrasted.

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

• search_companiesA
  4.7/5.0
  Behavior5/5

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

  With no annotations provided, the description takes full responsibility for behavioral disclosure. It reveals fuzzy matching, relevance-ranked results, a default for active (true), limits, and offset behavior, offering rich insight beyond the raw 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 well-structured with a summary line and an Args list, and every sentence adds valuable detail. It is slightly verbose due to explaining mode interactions, but this is necessary for correct tool usage.

  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?

  Given an output schema exists, return format details are unnecessary. The description covers all six parameters, mode priority, defaults, constraints, and search behavior, making it complete for an agent to select and invoke the tool correctly.

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

  Parameters5/5

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

  The input schema has no parameter descriptions (0% coverage), but the description's Args section thoroughly explains every parameter, including mutual exclusivity, accepted formats, defaults, and max values, fully compensating for the schema's silence.

  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 'Search for companies using the CleanJobData API' and enumerates three distinct lookup modes (query, website_url, employer_id), making the tool's purpose specific and distinguishable from job-focused siblings.

  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?

  It explicitly explains that query, website_url, and employer_id are mutually exclusive and checked in priority order, providing clear guidance on when to use each mode. However, it does not directly compare this tool with sibling tools like get_company or search_jobs.

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