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pirocheto

MCP Invoice Generator

by pirocheto
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Server Quality Checklist

67%
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  • Latest release: v0.1.0

  • Disambiguation5/5

    The two tools have clearly distinct purposes: one retrieves configuration defaults, the other generates the invoice. There is no overlap or confusion between them.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun pattern with lowercase and underscores ('get_default_values', 'generate_invoice'). The style is uniform across the set.

    Tool Count3/5

    With only two tools, the server feels thin for an invoice generator, though the core functionality (fetching defaults and generating) is present. It falls at the lower end of acceptable tool counts.

    Completeness4/5

    The set covers the essential flow of retrieving defaults and generating an invoice, but lacks auxiliary operations such as listing previously generated invoices or managing invoice data. These are minor gaps that agents can work around.

  • Average 3.6/5 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

  • 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 a key side effect (saving the invoice to the outputs directory) and the return value (the path). However, it does not mention potential errors, overwriting behavior, permissions, or the fact that the operation creates a file, which is only implied. It provides basic transparency but lacks depth.

    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, front-loaded with the main action, and every word earns its place. It is succinct, clear, and free of unnecessary detail, making it easy to parse quickly.

    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?

    Despite having an output schema, the description is inadequate for the complexity of the input. It does not explain the structure or purpose of the 'data' parameter, nor does it mention that the data must include issuer, client, and service details. The sole focus on output leaves a significant gap in understanding how to correctly invoke the tool.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters1/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    Schema description coverage is 0%, and the description does not explain what data should contain or provide any context for the numerous required fields. The schema's field names are self-explanatory to some degree, but the description adds no value beyond the schema, leaving the agent to guess at the meaning and format of the nested data object.

    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 generates an invoice for a client in PDF format, and it distinguishes itself from the sibling tool get_default_values by indicating its unique output (PDF saved to outputs directory). It uses a specific verb and resource, making the purpose unambiguous.

    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?

    The description provides no guidance on when to use this tool versus alternatives, such as get_default_values. It does not mention any prerequisites, exclusions, or scenarios where a different tool would be more appropriate. Users are left to infer usage from the description 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 must carry the full burden of behavioral disclosure. The verb 'Get' implies a read-only operation, but the description does not explicitly state the absence of side effects, permissions required, or other behavioral traits. It is adequate but could be more transparent.

    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, substantive sentence that front-loads the action and resource. Every word earns its place, with no redundancy or filler.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness5/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    For a no-parameter tool with a simple retrieval function, the description is complete. It lists the key components of the response, and the presence of an output schema covers return value details. No additional context is needed.

    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 tool has zero parameters, so the baseline is 4. The description adds value by detailing what the default values include (issuers, services, clients), which is helpful context even though there are no input parameters to document.

    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's purpose with a specific verb ('Get') and resource ('default values for invoices'), and it enumerates the contents (issuers, services, clients). This distinguishes it from the sibling 'generate_invoice' tool, which focuses on creation rather than retrieval.

    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 usage as a preparatory step for generating invoices, but it does not explicitly state when to use this tool over generate_invoice or provide alternative scenarios. The context is clear but lacks explicit when/when-not guidance.

    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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