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black940514

gpt-cross-validator

by black940514
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Server Quality Checklist

58%
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  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools have clearly distinct scopes: one critiques plans/designs while the other reviews code quality. Despite both using Gemini, the target artifact is unambiguously different, so an agent can easily select the appropriate tool.

    Naming Consistency5/5

    Both tools follow the consistent `<provider>_<verb>` pattern (gemini_critique, gemini_review), using lowercase and underscores. The naming style is uniform and predictable.

    Tool Count3/5

    With only two tools, the server is minimal but each tool serves a specific validation type. While it doesn't reach the typical 3-15 range, the narrow scope of cross-validation makes the count borderline acceptable.

    Completeness5/5

    The server covers the two main artifact types (plans/designs and code) that would need independent validation. No additional validation types are implied by the server's purpose, so the surface is fully sufficient.

  • Average 3.5/5 across 2 of 2 tools scored.

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

    • No community issues in the last 6 months
    • 0 commits 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

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  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

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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

  • Behavior2/5

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

    No annotations are provided, so the description carries the full burden of behavioral disclosure. It indicates it uses Gemini Pro, which implies external service calls, but doesn't mention side effects, data privacy, retry behavior, or what the output looks like. The absence of read-only hints or side-effect disclosures 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.

    Conciseness5/5

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

    The description is extremely concise: two short sentences. It front-loads the core purpose and provides a brief usage context. Every word is meaningful, with no fluff.

    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?

    There is no output schema and no annotations, so the description must compensate. It fails to explain what the review returns, how to interpret results, or any potential side effects. With 4 parameters and a complex task, this is incomplete for reliable tool invocation.

    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 100% and each parameter has a description, so the baseline is 3. The tool description adds no extra parameter semantics beyond what's already in the schema, but the schema itself is adequate. 'code' is clearly the focus from the required field and 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 clearly states the tool reviews code quality using Gemini Pro, which is a specific verb + resource. It also mentions cross-validation independent of Claude, giving context. However, it doesn't distinguish itself from the sibling 'gemini_critique', so it's slightly short of full differentiation.

    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 a use case: cross-validation independent of Claude. This gives some context on when to use the tool, but it doesn't explicitly state when not to use it or provide alternatives like gemini_critique. There's no clear comparative guidance.

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

  • Behavior3/5

    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 that the tool uses Gemini Pro, implying an external API call, and the intent of independent review. However, it does not mention side effects, latency, permissions, or the nature of the output, leaving gaps in behavioral transparency.

    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, concise sentence that front-loads the core purpose and usage context. Every word contributes value, with no redundancy or fluff.

    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?

    Given the tool's simplicity (2 parameters, no output schema, no annotations), the description covers the primary purpose and usage context. It lacks details on return values and prerequisites, but for a basic critique tool, it provides minimally sufficient information.

    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 100%, with both 'plan' and 'context' having descriptions in the schema. The tool description adds no extra parameter-level information, so it stays at the baseline for fully covered schemas.

    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 states the tool uses Gemini Pro to review plans/designs, providing a specific verb and resource. It also adds the purpose of independent cross-validation with Claude, which distinguishes its intent somewhat. However, it does not explicitly contrast with the sibling tool gemini_review, preventing a higher score.

    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 states 'for independent cross-validation with Claude', giving a clear context for when to use this tool. It does not mention exclusions or alternative tools, but the stated purpose is specific enough to guide the agent on appropriate usage.

    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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