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palimpsest-labs

image-analysis-mcp

by palimpsest-labs
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Server Quality Checklist

58%
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  • Latest release: v0.1.0

  • Disambiguation3/5

    ocr_image and image_metadata have clearly distinct purposes, but extract_text is a combined wrapper that overlaps with both, creating potential confusion about which tool to use for a given task. The descriptions help clarify that extract_text is a convenience option, but the presence of a full-coverage tool makes the specific tools somewhat redundant.

    Naming Consistency3/5

    Tool names are all snake_case, but the patterns vary: ocr_image uses an acronym as a verb, image_metadata is a noun-noun compound with no action verb, and extract_text is a clear verb-noun pair. While still readable, this mix prevents a predictable verb_noun convention across the set.

    Tool Count4/5

    Three tools is on the lower end of typical server scope, but is appropriate for a focused image analysis tool that covers OCR and metadata extraction. The count is not excessive, and each tool fills a specific need, though the combined wrapper could be seen as unessential.

    Completeness4/5

    For the apparent domain of text extraction and metadata retrieval, the set is fairly complete: ocr_image covers text, image_metadata covers metadata, and extract_text provides a combined result. However, other common image analysis operations (e.g., object detection, format conversion) are absent, though they may be out of scope for this server.

  • Average 3.9/5 across 3 of 3 tools scored.

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

    • No community issues in the last 6 months
    • 2 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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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 must carry the full burden. It discloses the return format but does not mention any behavioral traits such as supported image formats, file size limits, or safety implications. The 'must be under home directory' constraint is a parameter limitation, not a behavioral disclosure.

    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 efficient: a one-line purpose, a brief explanation of behavior, and a parameter doc. It is front-loaded with the core action and contains no redundant 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?

    For a simple one-parameter tool, the description adequately covers the argument, the extraction behavior, and the return format (text blocks with confidence and bounding boxes). The output schema exists, so return details are not needed. A minor gap is the lack of failure scenarios, but this is not critical given the tool's simplicity.

    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 gives only a field name and type, with 0% schema description coverage. The description's Args section adds essential meaning: 'Absolute path to the image file (must be under home directory)'. This compensates well for the schema's lack of detail.

    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 opens with 'OCR text from an image', clearly naming the action and resource. It distinguishes the tool from siblings by specifying OCR on images, and the mention of 'text blocks with confidence scores and bounding boxes' further defines its scope.

    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?

    No explicit guidance on when to use this tool versus the sibling 'extract_text'. The description implies use for image OCR but does not state exclusions or alternatives, leaving the agent to infer.

    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 must disclose behavior. It states the path constraint (must be under home directory) and lists the types of data returned, but does not mention permissions, supported formats, or error conditions. It's a read-only operation by nature, but that is not explicitly stated.

    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?

    The description is structured with a lead sentence, a bullet-like list of returned metadata, and an Args section. It is appropriately sized and the first sentence front-loads the purpose. A slight reduction in detail would be possible, but it is not bloated.

    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?

    The output schema exists, so return values are already documented. The description covers the parameter, the main behavior, and the path constraint. It lacks details on error cases or supported formats, but for a metadata extraction tool with an output schema, this is sufficient.

    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 only defines 'path' as a string with no description (coverage 0%). The description compensates by specifying 'Absolute path to the image file (must be under home directory)', giving both format and a critical constraint. This is full explanatory coverage for the single parameter.

    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 uses the verb 'Extract' with a clear object ('full metadata from an image') and enumerates the metadata categories (file info, image properties, EXIF). However, it does not explicitly distinguish from sibling tools like ocr_image or extract_text, so it's clear but lacks explicit sibling differentiation.

    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 for metadata extraction but does not state when to prefer this over OCR or text extraction. It provides context about what the tool returns but no exclusions or alternative references.

    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?

    With no annotations provided, the description carries the burden. It adds a path constraint (must be under home directory) and mentions a single JSON response, but does not explicitly state read-only behavior or potential limitations, though 'extract' implies non-destructive.

    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 summary and an Args section for parameter details. Every sentence earns its place without unnecessary fluff.

    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 output schema exists, the description needn't explain return values in-depth. It covers the tool's combined purpose, the parameter constraint, and the response format. Missing details like supported image formats are minor given the schema.

    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?

    Schema coverage is 0%, but the description compensates by explaining image_path is an absolute path and must be under the home directory, adding meaning beyond the bare string type.

    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 extracts all text and metadata from an image. It explicitly positions itself as a convenience wrapper combining OCR and metadata, distinguishing it from siblings like ocr_image and image_metadata.

    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 clearly indicates this tool is for when both text and metadata are needed, as it combines both. Sibling tool names imply the alternatives, though no explicit 'when not to use' is 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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