Server Quality Checklist

Tool Scores

• verifier_platform_verifyA
  4.1/5.0
  Behavior4/5

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

  The description adds meaningful behavioral detail beyond the annotations: it retrieves from a server-side UOB local knowledge base first, reuses the server-side DeepSeek API Key for web search, and returns an Ed25519 signature. It does not contradict the annotations, though it omits potential side effects or rate-limit considerations.

  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, front-loaded with the core purpose, and every clause adds useful information. It packs required fields, behavior, webSearch semantics, and return contents into a short, readable paragraph without redundancy.

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

  Completeness3/5

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

  The main call path is well covered: required inputs, knowledge-base retrieval, optional web search, and signed output. But the tool has 7 parameters and a complex nested execution object that is never mentioned, and the guidance could more explicitly address when to prefer the sibling tools. The output schema mitigates the return-value gap, but parameter coverage remains incomplete.

  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 0% schema description coverage, the description must compensate, and it does for question, answer, reasoning, and webSearch—including the maxResults 5/10 constraint and optional query. However, it completely omits context, execution, and requestId, leaving the nested execution object undocumented and the agent without guidance on how to supply audit metadata.

  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 a specific action—verifying and signing an externally generated answer with auditable reasoning—and names the independent verifier_platform resource. It also distinguishes the tool from its siblings by emphasizing the signing output and the verification workflow.

  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 clear context: use this tool when an external model's answer needs independent verification and a signed result. It does not explicitly discuss when to use verifier_platform_verify_signature or verifier_platform_status instead, so it stops short of full exclusionary guidance.

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

• verifier_platform_verify_signatureA
  4.2/5.0
  Behavior4/5

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

  The annotations already establish read-only, non-destructive, idempotent behavior. The description adds meaningful behavioral detail beyond that: RFC 8785 JCS canonicalization of the payload, Ed25519 signature verification, optional SHA-256 verification, and the guarantee that no model call occurs. No contradiction with annotations.

  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, front-loaded sentence that conveys read-only/offline status, the algorithm, the payload normalization behavior, and the no-model-call guarantee. Every phrase earns its place with little 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 rich nested schema, output schema, and safety annotations, the description sufficiently completes the picture for selecting and invoking the tool. Minor gaps remain: it never explicitly routes between sibling tools, and the 'optional SHA-256' is slightly underspecified, but these do not prevent correct use.

  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 description coverage is 0%, so the description must compensate for missing parameter documentation. It usefully explains that the payload is RFC 8785 JCS canonicalized and that a SHA-256 is optionally verified, which maps to expectedPayloadSha256. However, it does not precisely explain the semantics of sigB64/publicKeyPem or what the optional hash is over, leaving some burden on the schema names and the agent's inference.

  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 a specific action and resource: offline verification of verifier_platform's Ed25519 audit signature, with optional SHA-256 verification. It also differentiates from the likely model-calling sibling verifier_platform_verify by explicitly saying '不会调用模型' (does not call a model).

  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 clear context for when to use the tool: as a read-only, offline signature verification operation that does not invoke a model. It does not explicitly name alternatives or exclusion conditions, so it stops short of the strongest usage guidance, but the intended use case is clear.

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

• verifier_platform_statusA
  4.3/5.0
  Behavior4/5

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

  The annotations already convey readOnlyHint, idempotentHint, and destructiveHint=false. The description adds meaningful behavioral context beyond those annotations, especially '不会调用模型' (does not call the model), which is a useful runtime expectation for an agent. Saying '只读' is partially redundant with the annotation, but the overall behavioral disclosure is solid.

  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 entire description is one compact sentence, front-loaded with the read-only nature, then listing the specific data categories. It contains no redundant filler and every phrase adds useful information.

  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 read-only status tool with an output schema and rich annotations, the description is complete. It states what is exposed, affirms that no model call is made, and lets the output schema define return details. Nothing critical is missing for an agent to invoke this tool correctly.

  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 there are no parameter semantics to clarify. The baseline for a zero-parameter tool is 4, and the description does not need to compensate for any parameter documentation gap.

  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 names a specific verb ('查看' / view), a specific resource ('verifier_platform'), and enumerates the exact facets returned: desensitized configuration, policies, audit status, and signing public key. This clearly distinguishes it from the sibling verification tools, which perform actions rather than retrieving status.

  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 its usage context: use this read-only tool to inspect configuration/status, not to perform verification. However, it does not explicitly contrast itself with the sibling tools 'verifier_platform_verify' or 'verifier_platform_verify_signature', nor does it state situations where those should be preferred.

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