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shinpr

Smart Image Generator

by shinpr
OverviewSchemaRelated ServersScoreDiscussions
TypeScript
Hybrid

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    Only one tool exists, so there is no possibility of confusion or overlap. The tool's purpose is clearly defined around image generation and editing.

    Naming Consistency5/5

    The single tool follows a clear verb_noun pattern ('generate_image'), and with only one tool, there are no naming conflicts or inconsistencies to worry about.

    Tool Count3/5

    A single tool is on the thinner end, but for a focused image generator it can be sufficient. However, it lacks the typical 3+ tools that provide a richer surface, so it feels slightly minimal.

    Completeness5/5

    The tool covers both generation and editing within one operation, which addresses the core domain completely. No additional tools are strictly necessary for the server's stated purpose of generating images.

  • Average 3.9/5 across 1 of 1 tools scored.

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

    • 4 of 4 community issues answered or closed in the last 6 months
    • 46 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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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

  • Behavior3/5

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

    With no annotations, the description carries the full burden. It discloses that the tool 'Saves the result and returns a file resource,' which is a key side-effect. However, it does not clarify whether the original image is modified, mention any required permissions, rate limits, or provider-specific side effects. The schema provides some provider behavior, but the description adds limited 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 two concise sentences with no wasted words. It front-loads the purpose and then states the output/side-effect. Excellent structure for quick parsing.

    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 complex 11-parameter tool with no output schema, the description provides a high-level purpose and return type but omits prerequisites, error behavior, and provider differences. The extensive schema descriptions fill many gaps, making the description minimally complete for initial understanding, though more context would be beneficial.

    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?

    All 11 parameters have detailed descriptions in the schema (100% coverage), so the baseline is 3. The tool description itself adds minimal parameter-level meaning beyond referencing inputImagePath for editing. The rich schema descriptions carry the semantic load, and the description does not need to compensate.

    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 explicitly states the tool 'Generate a new image from a text prompt or edit an existing image using inputImagePath' and 'Saves the result and returns a file resource.' This is a specific verb+resource with clear scope, distinguishing the two main operation modes. Though no sibling tools exist, the purpose is unambiguous.

    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 implies usage: use this tool to generate from text or edit when an inputImagePath is provided. It clearly indicates the editing condition by referencing inputImagePath. However, it does not explicitly provide when-not-to-use guidance or name alternatives, though the schema descriptions further clarify parameter-specific 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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  • Evaluate tool definition quality.

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