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tryp0xy1us

yifanli-mcp-add-demo

Server Quality Checklist

67%
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  • Latest release: v0.1.2

  • Disambiguation5/5

    With only one tool, there is no possibility of confusion or overlap between tools. The tool's purpose is clearly defined as adding two numbers, making it distinct by default.

    Naming Consistency5/5

    A single tool inherently has perfect naming consistency, as there are no other tools to compare it against. The tool name 'add' is simple and follows a verb-based pattern.

    Tool Count2/5

    One tool is too few for a server's purpose, as it severely limits functionality and suggests an incomplete or trivial implementation. A single addition operation does not justify a full server scope.

    Completeness1/5

    The server is severely incomplete, as it only supports adding two numbers with no other arithmetic operations (e.g., subtract, multiply, divide) or related functionalities. This creates significant gaps for any practical use.

  • Average 3.1/5 across 1 of 1 tools scored.

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

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  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

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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?

    With no annotations provided, the description carries the full burden of behavioral disclosure. 'Add two numbers' implies a simple computation but doesn't specify error handling, numeric limits, or return format. It lacks details about what happens with invalid inputs or edge cases.

    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 extremely concise with zero wasted words—'Add two numbers' is a single, clear sentence that front-loads the core functionality. Every word earns its place, making it efficient and easy to parse.

    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 (simple arithmetic) and the presence of an output schema (which handles return values), the description is minimally adequate. However, with no annotations and 0% schema coverage, it lacks details on behavioral traits and parameter semantics, leaving room for improvement.

    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 0%, so the schema provides no parameter descriptions. The description 'Add two numbers' implies parameters 'a' and 'b' are numbers to be added, adding basic meaning beyond the schema's type definitions. However, it doesn't specify integer-only addition or other constraints, leaving gaps.

    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 'Add two numbers' clearly states the tool's purpose with a specific verb ('Add') and resource ('two numbers'), making it immediately understandable. It doesn't need to distinguish from siblings since there are none, so a 4 is appropriate rather than a 5.

    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, prerequisites, or constraints. It simply states what the tool does without any context about appropriate use cases or limitations.

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

GitHub Badge

Glama performs regular codebase and documentation scans to:

  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

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