Server Quality Checklist

Tool Scores

• verify_and_kernel_checkA
  3.6/5.0
  Behavior4/5

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

  No annotations provided. Description explains that the Lean proof is downloaded and run locally, and kernel_check is null for non-VALID verdicts. Discloses that result is on user's machine, not Prova's. Does not mention side effects but reasonable for a verification 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?

  Description is front-loaded with main action and uses clear structure. Bullet points for return values are helpful. Slightly verbose but still efficient. Could be more concise without losing clarity.

  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 4 parameters with 0% schema coverage and no param descriptions, the description is incomplete. It covers behavioral output well but leaves parameter semantics entirely unaddressed, which is critical for correct invocation.

  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%. Description provides no information about parameters (reasoning, retain, source_url, domain). Agent cannot infer their meaning or constraints beyond schema types.

  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 'Verify reasoning, then locally kernel-check the emitted Lean proof.' and distinguishes from siblings by combining both steps in one call. Specific verb (verify, kernel-check) and resource (reasoning, Lean proof).

  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?

  Description says 'The complete trust loop in one call.' implying when to use. It explains that INVALID verdicts skip kernel step but does not explicitly mention when not to use or alternatives. Usage context is clear but lacks exclusions.

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

• download_lean_proofA
  3.9/5.0
  Behavior3/5

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

  With no annotations, the description must carry full burden. It discloses the error condition for invalid certificates and the return structure. However, it omits safety aspects (read-only implied but not stated) and does not detail behavior like idempotency or rate limits.

  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?

  Very concise: two sentences and a return list. Front-loaded with purpose, no fluff. Every sentence adds value.

  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 one required parameter and an output schema described in text, the description covers return values and integration with kernel_check_proof. Lacks details on potential limitations (e.g., proof size), but is largely complete.

  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?

  The parameter certificate_id has 0% schema coverage and the description does not explain what it is or how to obtain it. It only uses the term 'certificate' in context, which weakly implies the ID's role. This is insufficient.

  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?

  Clearly states 'Download the self-contained Lean 4 proof for a VALID certificate', using a specific verb and resource. Distinguishes from siblings like kernel_check_proof (verification) and get_certificate (retrieval).

  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?

  Explicitly mentions that the returned lean_source can be passed to kernel_check_proof, suggesting a usage flow. Also warns that INVALID certificates result in an error. Lacks explicit exclusion of alternatives like verifying locally without downloading.

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

• get_certificateA
  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 the full burden. It indicates a read-only fetch operation and mentions that the return format matches verify_reasoning, which adds behavioral context. It does not disclose authentication or error conditions, but for a simple retrieval tool, 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 concise sentences in the first paragraph and a brief second paragraph. It front-loads the purpose and uses no superfluous words. Every sentence earns its place.

  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), the presence of an output schema (so return values are defined elsewhere), and the clear references to sibling tools, the description provides sufficient context for an agent to understand when and how to use it.

  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 0% description coverage and only a parameter name 'certificate_id'. The description adds value by providing an example format ('PRV-2026-A7X4') and clarifying that it is a certificate ID, which goes beyond what the schema offers.

  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 verb ('Fetch'), the resource ('previously issued certificate'), and the unique identifier ('by ID'). It provides an example format ('PRV-2026-A7X4') and distinguishes the tool from siblings like verify_reasoning by specifying its use case for re-checking, sharing, or inspecting failures from other pipelines.

  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 suggests when to use this tool (re-check a verdict, share a link, inspect a failure) and implicitly contrasts it with verify_reasoning by saying it returns the same summary. It does not explicitly state when not to use it, but the context is clear enough for an agent to decide.

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

• verify_reasoningA
  4.5/5.0
  Behavior4/5

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

  No annotations are provided, so the description carries the full burden. It discloses the return value (verdict, confidence_score, certificate_id, etc.) and explains the meaning of VALID/INVALID verdicts. It does not mention any side effects or state changes, but the tool appears read-only.

  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 well-structured: purpose sentence, usage context, parameter list, and return summary. It is concise yet comprehensive, with no extraneous words.

  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 5 parameters, 1 required, and no annotations, the description adequately covers the tool's behavior and return values. It could mention prerequisites or error handling, but the output schema exists to supplement this.

  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 has 0% description coverage, but the description provides detailed explanations for each parameter: reasoning (plain text), retain (default from env var), source_url (optional), domain (hints for classification), and metadata (constraints on keys and size). This adds significant value beyond the 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 clearly states the tool verifies a multi-step reasoning chain and returns a Prova certificate summary. It specifies the intended use case ('before producing a final answer') and the tool's distinct role compared to sibling tools that focus on formal proof verification.

  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 explicit guidance on when to use the tool ('on any draft chain-of-thought before producing a final answer') and what to do in case of an INVALID verdict (repair and re-verify). However, it does not explicitly mention alternatives or when not to use this tool.

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

• kernel_check_proofA
  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 fully discloses behavior: it runs locally, exit code 0 means accepted, else proof is wrong, requires lean binary, and overridable via environment variable. It also describes the return format including fields like accepted, exit_code, etc.

  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 well-structured: purpose first, then trust significance, exit code meaning, prerequisites, and return format. Every sentence adds value without 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?

  The tool has one parameter and an output schema. The description covers prerequisites, error handling (non-zero exit), return fields, and even an environment variable override. It is fully complete for a tool of this complexity.

  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 single parameter lean_source has 0% schema description coverage, but its name and title are self-explanatory. The description mentions 'proof string' in the first line, giving context. A direct parameter description would improve clarity, but it is still adequate.

  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 'Run the Lean 4 kernel on a proof string locally', specifying the verb, resource, and scope. It distinguishes from siblings like download_lean_proof (download) and verify_reasoning (other verification) by emphasizing it is the trust anchor and runs locally.

  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 explains the exit code meaning and the requirement for the lean binary, including installation via elan. While it doesn't explicitly contrast with siblings, the context of being the trust anchor implies when to use this tool for final kernel verification.

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