Server Quality Checklist

Tool Scores

• lookup_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 transparency burden. It discloses the one-credit cost, which is useful. However, it does not mention potential errors, rate limits, or the return format details beyond listing fields. Acceptable for a simple read tool but not rich.

  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?

  Two sentences: first defines the operation and outputs, second gives usage guidance and cost. Every sentence adds value, front-loaded, no filler.

  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?

  The tool is simple (one input, one table of outputs). The description covers purpose, input, output fields, usage context, and cost. Missing only edge-case behavior, which is minor for this straightforward lookup.

  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?

  The schema already provides 100% coverage for the single parameter 'domain' with a clear format example. The description adds no new parameter details but reinforces the input type. This aligns with the baseline of 3.

  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 resolves a domain to company details (name, industry, city, country, address, LinkedIn URL). This distinguishes it from sibling tools like lookup_technology or lookup_companies by its specific domain-to-firmographics purpose.

  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 use cases: 'when asked who owns or operates a website, or to enrich a domain into firmographics.' It does not list exclusions or direct comparisons to alternatives, but gives sufficient context for when to choose this tool.

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

• lookup_domain_technologiesA
  4/5.0
  Behavior3/5

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

  No annotations are provided, so the description carries the transparency burden. It discloses the credit cost and outlines the response structure (category and site count), but does not address edge cases like invalid domains, empty results, or rate limits beyond cost.

  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 two sentences, with the main action in the first and a use case plus cost in the second. Every sentence provides value, with no redundancy.

  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?

  For a simple lookup tool with no output schema and high schema coverage, the description covers the core purpose, output content, and usage scenario. It falls short of full completeness by not explicitly addressing alternative tools or failure modes, but overall it is 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?

  With 100% schema description coverage, the schema already documents both 'domain' and 'limit' with clear descriptions. The tool description adds no additional parameter meaning, merely restating that a domain is input.

  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: given a domain, list detected technologies with category and usage count. It provides a specific use-case question ('what is this site built with?') and implicitly differentiates from siblings like lookup_technology by focusing on the domain rather than a single technology.

  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 gives explicit context for when to use the tool via 'Use this to answer...' but does not mention when not to use it or contrast with alternatives. It provides a clear scenario but lacks exclusion criteria.

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

• lookup_technologyA
  4.2/5.0
  Behavior4/5

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

  With no annotations provided, the description discloses an important behavioral trait: 'Costs 1 credit.' It also describes the high-level output (usage and top countries), giving the agent an idea of what to expect. It does not mention rate limits or auth, but for a simple read-only lookup, this is 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 two sentences long and front-loaded with the core functionality. The second sentence adds a usage example and cost information, both valuable. No redundant phrases or filler.

  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?

  For a tool with one parameter and no output schema, the description covers the essential aspects: what it does, when to use it, an example, and a cost note. It does not detail the exact response format, but the description's statement that it returns 'how widely used' and 'top countries by adoption' gives sufficient context for a simple lookup tool.

  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?

  The schema already provides a thorough description for the 'technology' parameter, including examples (Shopify, Klaviyo, Cloudflare), so schema coverage is 100%. The description only reinforces 'technology name' without adding new constraints or formatting details, placing it at the baseline.

  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: given a technology name, it returns usage breadth and top adopting countries. It includes a concrete example ('how many sites run Shopify, and where?') that distinguishes it from sibling tools like lookup_company (company-focused) and lookup_domain_technologies (domain-focused).

  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 explicitly advises when to use the tool: 'Use this to size a market or compare platforms.' It provides a practical use case but does not name alternatives or state exclusions, so it stops short of a full 5.

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

• check_creditsA
  4.7/5.0
  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 explicitly states 'Free - does not consume a credit', disclosing the cost behavior, and implies it returns a balance. This is adequate for a simple read-only tool.

  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 two sentences, front-loaded with the purpose and then the usage context. Every word earns its place with no redundancy.

  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 zero-parameter, simple tool, the description provides purpose, cost behavior, and usage timing. No output schema exists, but the tool's simplicity means return value can be inferred. Complete and sufficient.

  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 tool has zero parameters, so the schema covers everything. The baseline for 0 params is 4, and the description adds no unnecessary parameter details.

  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 purpose with a specific verb ('Check') and resource ('StackScan credit balance'). It is distinct from sibling lookup tools, which focus on company/technology lookups.

  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?

  Provides explicit guidance on when to call the tool: 'Call this before a batch of lookups so you know how many you can afford.' This gives clear usage context and implies it is a prerequisite check before other operations.

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

• lookup_companiesA
  5/5.0
  Behavior5/5

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

  With no annotations provided, the description fully carries the behavioral disclosure burden. It explains cost per domain, free misses/malformed domains, and deduplication of duplicates and www variants, giving the agent a clear picture of side effects and edge-case behavior.

  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 and front-loaded with the core purpose. Every sentence adds critical information: bulk capability, alternative usage, and cost/dedup rules. No wasted words.

  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 the tool's simplicity (one parameter, no output schema), the description covers everything needed: what it does, when to use it, cost structure, and edge-case handling. It is complete without being verbose.

  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 schema already documents the 'domains' parameter with format and maxItems. The description adds valuable nuances beyond the schema: duplicates and www variants collapse and are charged once, which is not in the schema description. This enriches the semantic meaning.

  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: looking up companies behind up to 20 domains in a single call, returning a compact table. It also distinguishes itself from the sibling tool 'lookup_company' by emphasizing the bulk capability.

  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?

  Explicit guidance is provided: 'Prefer this over repeated lookup_company calls whenever you have several domains in hand.' It also explains the cost per domain and the handling of duplicates/www variants, helping decide when to use it.

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