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devlimelabs

Lulu Print MCP Server

by devlimelabs
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TypeScript
Remote

Server Quality Checklist

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

  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools have completely distinct purposes: one calculates costs for print jobs, while the other retrieves product specifications. There is no overlap in functionality, making it impossible for an agent to confuse them.

    Naming Consistency3/5

    Both tools use a verb-object naming pattern, but they mix conventions: 'calculate-print-job-cost' uses kebab-case, while 'get-product-details' uses hyphenation inconsistently with the first. The verbs 'calculate' and 'get' are clear but not perfectly aligned in style.

    Tool Count2/5

    With only two tools, the server feels thin for a print service domain. It lacks essential operations like creating print jobs, managing orders, or handling payments, which are core to such a service. The count is too low for the apparent scope.

    Completeness2/5

    The tool surface is severely incomplete for a print service. It covers cost calculation and product details but misses critical operations such as job creation, order submission, status tracking, and payment processing, leaving significant gaps that will cause agent failures.

  • 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 is failing

  • 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

  • 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. The description states it 'gets' details, implying a read-only operation, but doesn't clarify permissions, rate limits, error conditions, or what 'specifications and details' includes. For a tool with zero annotation coverage, this is insufficient behavioral context.

    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, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded with the core action and resource, making it easy to parse. Every word earns its place, achieving optimal conciseness.

    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 low complexity (single parameter, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose but lacks details on behavior, usage context, and output format. Without annotations or output schema, the agent must rely heavily on the description, which is incomplete for informed tool selection.

    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 schema description coverage is 100%, with the single parameter 'product_id' documented as 'Lulu product ID'. The description doesn't add any parameter-specific information beyond what the schema provides, such as format examples or constraints. With high schema coverage, the baseline score of 3 is appropriate.

    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 action ('Get') and resource ('specifications and details for a Lulu product'), making the purpose understandable. However, it doesn't differentiate from the sibling tool 'calculate-print-job-cost', which appears unrelated but could potentially overlap in product context. The description is specific but lacks sibling distinction.

    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 guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites, context, or exclusions. With only one sibling tool that seems unrelated (cost calculation), the lack of explicit usage guidelines leaves the agent to infer based on tool names alone.

    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 full burden for behavioral disclosure. It clearly indicates this is a read-only calculation tool (not creating anything), which is helpful. However, it doesn't mention potential limitations like rate limits, authentication requirements, or what specific cost components are included in the calculation.

    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, efficient sentence that communicates the essential purpose without any wasted words. It's appropriately sized for a simple calculation tool and front-loads the key information.

    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 2-parameter calculation tool with no annotations and no output schema, the description provides adequate but minimal context. It clearly states the purpose but doesn't explain what the output looks like (cost format, currency, breakdown) or any prerequisites for successful calculation.

    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 schema already fully documents both parameters. The description doesn't add any additional meaning or context about the parameters beyond what's in the schema. This meets the baseline expectation when schema coverage is complete.

    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 specific action ('calculate the cost') and resource ('print job'), and explicitly distinguishes it from the alternative action of creating a print job. This provides excellent clarity about what the tool does and what it doesn't do.

    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 clear context about when to use this tool ('without creating it'), which implicitly suggests it's for cost estimation before actual creation. However, it doesn't explicitly mention when NOT to use it or provide specific alternatives beyond the implied contrast with creation tools.

    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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  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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