Server Quality Checklist

Tool Scores

• list_act_typesA
  4.2/5.0
  Behavior4/5

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

  The description explicitly details the output format (English enum + original Spanish label). As a read-only operation with no parameters, no hidden behavioral traits are missing.

  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?

  One concise sentence containing all essential information. No superfluous content.

  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 parameters and an output schema present, the description is sufficiently complete. It covers the single action the tool performs.

  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 no parameters, and schema description coverage is trivially 100%. The baseline for 0 parameters is 4; the description does not need to add parameter semantics.

  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 returns all normalized event types with both the English enum and original Spanish label. This is specific and distinguishes it from sibling tools like search_events which filter data.

  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 list of event types is needed, but it does not specify when to avoid using it or how it compares to siblings. No alternatives or exclusions are mentioned.

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

• company_by_nifA
  4.3/5.0
  Behavior4/5

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

  No annotations provided, so description must convey behavior. It adequately explains that the tool relies on cross-referenced open sources and covers only a subset (~232k companies). It does not mention authentication or rate limits but is transparent about lookups being non-destructive and the meaning of missing results.

  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 concise and well-structured, with a clear first sentence stating purpose, followed by context and recommendations. Every sentence adds value without 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?

  Given the presence of an output schema, the description adequately covers the tool's functionality, limitations, and suggested follow-up. It provides sufficient context for an agent to use the 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?

  Input schema has 0% description coverage for the single parameter 'nif'. The description adds meaning by explaining it's a tax ID and tying it to the tool's purpose, but does not specify format or validation rules. Partial compensation for lack of 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's purpose: 'Look up a Spanish company by its NIF/CIF tax ID.' It provides specific context about the data source (BORME cross-referencing) and distinguishes itself from siblings like recent_signals and list_act_types by being a lookup tool.

  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 on when to use and limitations: 'A miss means not matched yet, not does not exist.' It also recommends follow-up with company_history using the returned slug on a hit, providing a clear workflow.

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

• recent_signalsA
  4.5/5.0
  Behavior4/5

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

  With no annotations provided, the description carries full burden. It discloses the tool's read-only nature (sample), the temporal and size limits, and the list of signal types. It also mentions the pricing/availability context via the hosted API link, which helps the agent understand its scope and limitations.

  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 and a list of types. The first sentence immediately states the purpose and constraints, and the second sentence provides essential context for broader usage. Every sentence adds value 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?

  Given the tool's simple nature (one optional param, output schema exists), the description covers all necessary aspects: what it does, its limitations, the available signal types, and how to access more data. The presence of an output schema means return values need not be described, so this is complete.

  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 input schema has only one optional parameter (signal_type) with no description or enum, but the description lists all valid values (INSOLVENCY_FILED, ACCORDION, etc.) and implies filtering capability. This adds significant meaning beyond the schema, compensating for the 0% schema description coverage.

  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 it returns a 'sample of the latest derived risk signals' with specific temporal (last 7 publication days) and size (max 10 rows) constraints, and lists the possible signal types. This provides a specific verb+resource with scope, distinguishing it from sibling tools like company_by_nif and list_act_types which have different purposes.

  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 notes this is a 'teaser feed' and directs users to the full historical signals firehose via the hosted API, providing clear context for when to use this limited sample versus the full dataset. It does not explicitly mention when not to use it, but the limitations are clear, making it a strong usage guide.

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