Server Quality Checklist

Tool Scores

• m2m_tax_matrixC
  2.1/5.0
  Behavior2/5

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

  No annotations provided, and the description fails to disclose behavioral traits such as read-only nature, error handling, currency assumptions, or whether reverse-charge mechanisms are supported. For a tax-related tool, this is a significant gap.

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

  Conciseness3/5

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

  The description is a single sentence without clear structure. While concise, it lacks the necessary detail for effective tool selection and invocation.

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

  Completeness1/5

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

  Given the absence of output schema, annotations, and parameter descriptions, the tool is severely underdocumented. Critical information about return values, currency, tax calculation logic, and potential errors is missing.

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

  Parameters1/5

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

  Schema description coverage is 0%, and the description adds no meaning to the four parameters. While parameter names are somewhat self-explanatory, no details are given about allowed values, format, or semantics (e.g., country codes, VAT ID validation).

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

  Purpose3/5

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

  The description 'Cross-border EU VAT tax matrix for M2M transactions between AI agents' suggests the tool computes or returns VAT tax data, but the verb is implied and 'matrix' is ambiguous. It does not clearly state what action the tool performs (e.g., calculates, retrieves, or validates tax rates).

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

  Usage Guidelines2/5

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

  No guidance on when to use this tool versus alternatives like 'm2m_predictive_rates' or 'm2m_global_tenders'. The description does not specify prerequisites, contexts, or exclusions.

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

• m2m_global_tendersC
  2.4/5.0
  Behavior2/5

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

  With no annotations provided, the description carries full burden. It mentions 'live' but fails to disclose read-only nature, authentication needs, rate limits, or what 'open to AI agent bidding' implies operationally. Critical 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.

  Conciseness3/5

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

  The description is a single concise sentence without fluff. However, it omits necessary details that could be added without sacrificing conciseness, such as parameter usage or output hints.

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

  Completeness2/5

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

  Given no output schema and no annotations, the description should provide more context on output format, pagination, or constraints. It is too sparse for an agent to understand how to use the tool effectively.

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

  Parameters1/5

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

  The single parameter 'country' is not explained in the description; schema coverage is 0%. The description adds no meaning beyond the schema, leaving the agent to guess how to use the parameter and default behavior.

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

  Purpose4/5

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

  The description clearly identifies the tool as providing live global public procurement tenders. It uses the specific resource 'tenders' and implies a retrieval action, distinguishing it from siblings focused on verification and rates/taxes.

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

  Usage Guidelines2/5

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

  No guidance is given on when to use this tool versus siblings like m2m_predictive_rates or kyb_verify_agent. The description lacks context on prerequisites, use cases, or scenarios where this tool is appropriate.

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

• m2m_predictive_ratesC
  2.4/5.0
  Behavior2/5

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

  No annotations are provided, so the description bears the full burden. It does not disclose whether the tool is read-only, what side effects exist, or any rate limits. The vague 'AI-driven' label adds no behavioral specifics.

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

  Conciseness3/5

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

  The description is a single sentence, which is concise but overly brief. It front-loads the purpose but omits critical details, making it less effective than a slightly longer but more informative description.

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

  Completeness1/5

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

  Given the absence of annotations, output schema, and parameter descriptions, the description is severely incomplete. It fails to equip the agent with enough information to use the tool correctly, such as what the input strings represent or what data the tool returns.

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

  Parameters1/5

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

  Schema description coverage is 0% for both parameters (base, target). The description does not explain what these parameters represent or expected formats, leaving the agent with no clue beyond type 'string'.

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

  Purpose4/5

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

  The description states the tool provides 'FX volatility forecasting for stablecoin treasury management,' which clearly indicates a forecasting purpose. However, it lacks specificity about the output format or how it compares to siblings like m2m_global_tenders, though the function is distinct enough.

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

  Usage Guidelines2/5

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

  No guidance is given on when to use this tool versus alternatives like m2m_global_tenders or m2m_tax_matrix. The description does not mention any context or prerequisites for use.

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

• kyb_verify_businessC
  2.8/5.0
  Behavior2/5

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

  With no annotations, the description carries full burden for behavioral context. It mentions 'lookup and AML risk profile' but does not disclose side effects (e.g., read-only nature), required permissions, rate limits, or data source limitations. This is insufficient for an agent to safely invoke the tool.

  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 a single sentence that efficiently conveys the core purpose with the acronym expansion and scope. However, it could benefit from slight restructuring to improve readability and emphasis on key actions.

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

  Completeness2/5

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

  Given the tool has two required parameters, no output schema, and no annotations, the description is too minimal. It does not explain return values, error handling, or how to properly use parameters. Additional context is needed for the agent to invoke the tool correctly.

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

  Parameters1/5

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

  Schema coverage is 0%, and the description adds no detail about the two required parameters ('country' and 'identifier'). It does not specify expected formats, allowed values, or examples, leaving the agent unable to construct valid inputs accurately.

  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 is a Know Your Business tool for corporate registry lookup and AML risk profiling, specifying the resource (corporate registry) and geographic scope (EU and Australian companies). This differentiates it from sibling tools like kyb_verify_agent (likely an agent version) and other unrelated tools.

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

  Usage Guidelines2/5

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

  The description provides no guidance on when to use this tool versus alternatives, no exclusions, and no context about prerequisites or use cases. The agent is left to infer usage from the name and brief description alone.

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

• kyb_verify_agentB
  3.4/5.0
  Behavior3/5

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

  No annotations provided. Description mentions verification of identity and authorization, implying a read-only check, but does not disclose side effects, rate limits, or authentication requirements.

  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?

  Single, well-front-loaded sentence. However, it wastes the opportunity to include parameter details.

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

  Completeness2/5

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

  Given no output schema or annotations, the description fails to explain return values, prerequisites, or error conditions. A verification tool should describe what happens on success/failure.

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

  Parameters2/5

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

  Schema has 0% description coverage and 2 required string parameters (agent_id, owner_address). Description does not explain what these parameters represent, leaving interpretation to the agent.

  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?

  Description clearly states the tool's purpose: verifying AI agent identity, ownership proof, and on-chain authorization. It distinguishes from sibling tools like 'kyb_verify_business'.

  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?

  Description implies use for AI agents but lacks explicit guidance on when to use vs alternatives (e.g., kyb_verify_business). No 'when not to use' stated.

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