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Server Quality Checklist

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  • Latest release: v1.0.1

  • Disambiguation5/5

    Each tool has a clearly distinct purpose: generate_image for creating/editing images, maintenance for system cleanups, show_output_stats for monitoring, and upload_file for file uploads. There is no ambiguity between them.

    Naming Consistency4/5

    Most tool names follow a verb_noun pattern (generate_image, show_output_stats, upload_file). 'Maintenance' is a single noun but still clear and fits the overall style. Minor inconsistency does not cause confusion.

    Tool Count5/5

    Four tools is well-scoped for an image generation server. Each tool addresses a key aspect: generation, upload, maintenance, and statistics. The count is neither too few nor excessive.

    Completeness4/5

    The tools cover core image operations (generation, upload, maintenance, stats). A minor gap is the lack of a dedicated delete tool for images, but maintenance can clean up expired files, so it's workable.

  • Average 3.8/5 across 4 of 4 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
    • Last stable release on
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is passing
  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

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      ]
    }

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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?

    The description states the tool performs maintenance operations (including destructive actions like cleanup), but annotations include readOnlyHint=true, creating a contradiction. The tool's mutability is not clarified, and the reference to workflows.md patterns is vague.

    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, with a clear opening sentence and a bullet list of operations. It front-loads the purpose and avoids unnecessary words.

    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?

    The tool has no output schema, and the description does not explain what the tool returns (e.g., reports, status messages). It also omits details about error handling or sequencing of full_cleanup.

    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%, so the input schema already provides detailed descriptions for all parameters. The description adds the operation list but does not provide additional meaning 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 tool performs maintenance operations and lists specific operations like cleanup_expired, check_quota, etc. It distinguishes itself from siblings (generate_image, show_output_stats, upload_file) by focusing on maintenance tasks.

    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?

    While the description mentions following workflows.md patterns, it does not explicitly state when to use this tool versus alternatives. The operations are self-explanatory, but there is no guidance on exclusions or conditions for use.

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

  • Behavior1/5

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

    The description claims 'edit existing images' which contradicts the readOnlyHint=true annotation, indicating a potential write operation. No disclosure of destructive effects or permissions. Annotation contradiction detected.

    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?

    Well-structured with bullet points, front-loaded with main purpose, and every sentence adds value. Concise yet comprehensive.

    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?

    Covers input modes, automatic detection, and return format. Lacks error handling details, but sufficient for given complexity. No output schema so return description is adequate.

    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% with detailed parameter descriptions. The description adds minimal extra value for parameters, so baseline 3 is appropriate.

    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 generates or edits images using natural language, with specific subsections for different modes. It differentiates from sibling tools by focusing on image generation/editing.

    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?

    Lists four distinct input modes and mentions automatic mode detection, providing clear guidance on when to use each. Lacks explicit when-not-to-use or alternatives, but sibling tools are unrelated.

    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?

    Annotations (readOnlyHint=false, openWorldHint=true) already indicate a mutating, side-effectful operation. The description adds the outcome of returning URI and metadata but lacks details on permissions, error handling, or specific behavioral traits beyond what annotations provide.

    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 sentences long, front-loaded with the core purpose, and the second sentence adds a valuable usage hint. Every sentence is purposeful and there is no unnecessary information.

    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 no output schema, the description adequately states the return type (URI and metadata). It covers the tool's purpose and usage context. Minor gaps exist regarding file type restrictions or error handling, but overall it is fairly complete for a simple upload tool.

    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?

    The input schema has 100% parameter description coverage, so the baseline is 3. The description does not add meaning beyond what the schema provides; the mention of 'image' in the usage hint slightly conflicts with the general 'file path' parameter, but not severely.

    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 'upload', the resource 'local file through the Gemini Files API', and the outcome 'return its URI & metadata'. It effectively distinguishes from sibling tools like generate_image and maintenance, which have different purposes.

    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 a specific use case: 'Useful when the image is larger than 20MB or reused across prompts.' This gives clear context for when to use the tool, though it does not explicitly state when not to use it or provide alternative tools.

    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?

    Annotations already declare readOnlyHint: true, and the description adds that it shows stats and recently generated images. No contradiction; the description appropriately complements the annotations for a read-only tool.

    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 that conveys the tool's purpose without waste. Every word earns its place.

    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?

    For a simple stat tool with no parameters or output schema, the description is adequate. It could list specific statistics, but given low complexity, it is sufficiently complete.

    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 no parameters, so schema coverage is 100%. Baseline score of 4 is appropriate; no parameter documentation is needed.

    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 uses a specific verb 'show' and resource 'statistics about the output directory and recently generated images', clearly differentiating it from sibling tools like generate_image (creates images) and maintenance (presumably maintenance tasks). It is unambiguous and sets clear expectations.

    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?

    While the description implies the tool is for viewing output stats, it does not explicitly state when to use it versus siblings or provide exclusions. The usage context is inferred but not guided.

    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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