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mathieusarrue-alt

StratVerity MCP Server

Server Quality Checklist

58%
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  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool targets a clearly distinct function: quick_check performs static diagnostics, verify_hash authenticates proofs, and get_badge generates badge URLs. There is no overlap or ambiguity between them.

    Naming Consistency4/5

    All tools share the stratverity_ prefix and snake_case style, but quick_check uses an adjective-noun pattern while verify_hash and get_badge follow verb_noun. This is a minor deviation from an otherwise consistent convention.

    Tool Count5/5

    Three tools is at the lower end but appropriate for the server's narrow audit-verification purpose. Each tool earns its place and the set is well-scoped without unnecessary bloat.

    Completeness4/5

    The core workflow is covered: run a quick diagnostic, verify a sealed proof, and generate a badge. A minor gap is the lack of a way to retrieve audit details or history, but agents can work around this for the main use cases.

  • Average 3/5 across 3 of 3 tools scored. Lowest: 1.9/5.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 1 commit in the last 12 weeks
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI status not available
  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

  • Behavior1/5

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

    With no annotations provided, the description carries the full burden. It only states that a badge URL is generated, but discloses nothing else—no side effects, authentication needs, return format, or what the URL represents. This is a significant gap for an action that produces an artifact.

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

    Conciseness2/5

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

    The description is a single short sentence, which is concise. However, 'concise' does not mean 'empty': the sentence is so terse that it fails to convey any meaningful detail, borderlining on under-specification rather than efficient communication.

    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?

    For a tool with three parameters, no output schema, and no annotations, this description is woefully incomplete. It does not explain how the badge URL is constructed, what status values imply, or what the caller can expect in return. An agent would have no idea how to correctly use the parameters.

    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 input schema has 0% description coverage for its three parameters (audit_id, score, status). The description only implies the role of audit_id via 'for an audit' but does not clarify the meaning or valid combinations of score and status. It adds almost no value beyond the schema's bare property names.

    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 a clear verb ('Generate') and resource ('badge URL for an audit'). It is specific enough to understand the tool's primary function, though it does not differentiate it from the siblings beyond a general sense of generating output.

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

    Usage Guidelines1/5

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

    No guidance is provided on when to use this tool versus stratverity_quick_check or stratverity_verify_hash. There is no mention of context, prerequisites, or alternatives.

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

  • Behavior2/5

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

    No annotations are provided, so the description carries full responsibility for behavioral disclosure. It indicates only that the tool 'verifies' and does not disclose whether the operation is read-only, whether it makes a network call, what happens for an invalid or unknown hash, or what response is returned.

    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, well-structured sentence with no filler words. The action, resource, and method are all present and the essential 'SHA-256 hash' constraint is included.

    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?

    For a single-parameter tool with no nested objects and no annotations, the description is minimally sufficient to know what input to provide and why. However, with no output schema or annotations, it leaves the success/failure behavior and response format unspecified, which an agent would need to interpret the tool's result.

    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 already documents the lone 'hash' parameter with 100% coverage. The description adds value by clarifying that the hash is a SHA-256 hash of a sealed audit proof, which connects the parameter to the tool's purpose.

    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 a specific action ('Verify') and resource ('authenticity of a sealed audit proof by its SHA-256 hash'), which is substantive and more informative than the tool name alone. However, it does not explicitly distinguish this from sibling tools like stratverity_quick_check, which may also perform verification.

    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 implies the tool should be used when a caller has a SHA-256 hash and needs to confirm proof authenticity, but it gives no explicit when-to-use guidance, no exclusions, and no mention of alternatives such as stratverity_quick_check or stratverity_get_badge. An agent cannot tell when this tool is preferred over its siblings.

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

  • Behavior4/5

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

    No annotations are present, so the description carries full responsibility. It discloses one key behavioral trait — 'Never executes the code' — which clearly signals a safe, read-only static operation and distinguishes it from potentially code-executing alternatives. It does not disclose result accuracy or best-effort nature, but the single core safety disclosure is meaningful.

    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?

    A single sentence that fronts the purpose, lists the specific diagnostic categories in a parenthetical, and closes with the safety caveat. Zero filler or 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 definition is adequate for a simple 2-param tool, covering what it checks and the safety behavior. However, with no output schema present and no mention of return value format, diagnostic result semantics, or what the agent should do with the output, there is a notable gap for a tool whose sole deliverable is a diagnostic result.

    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 coverage is 50%. The 'source' parameter is documented in schema ('Strategy source code excerpt'), which is adequate but not enriched by the description. 'language' is self-documenting via its enum (pinescript/python/mql5) and default. The description adds nothing beyond the schema, so baseline 3 applies.

    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-resource pair ('diagnostic of strategy code') and enumerates three concrete checks (look-ahead, repainting, overfitting), which sharply distinguishes it from the siblings stratverity_verify_hash and stratverity_get_badge. Purpose is explicit and unique.

    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 intended use (static analysis of strategy source) is clear, but there is no explicit when-to-use/when-not-to-use guidance or reference to the sibling tools (verify_hash, get_badge). The phrase 'Never executes the code' hints at safety rather than usage conditions S46. No exclusions or alternative-selection conditions are provided.

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

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