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xiaobenyang-com

Markdown-To-Notion

by xiaobenyang-com
OverviewSchemaRelated ServersScoreDiscussions
TypeScript
Remote

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    With only one tool, there is no possibility of confusion or overlap between tools, as there are no other tools to compare it against. The tool's purpose is singular and clearly defined, eliminating any ambiguity in tool selection.

    Naming Consistency5/5

    Since there is only one tool, it inherently maintains perfect consistency with itself. The tool name follows a clear verb-object pattern (markdown-to-notion), which is straightforward and descriptive for its function.

    Tool Count2/5

    A single tool is generally too few for a server's scope, as it limits functionality and suggests an incomplete or overly narrow implementation. While the tool's purpose is clear, one tool often indicates a minimal surface that may not cover related operations or workflows effectively.

    Completeness2/5

    The server's domain appears to involve converting markdown to Notion content, but with only a conversion tool, there are significant gaps. Missing operations might include retrieving markdown, updating Notion pages, handling errors, or managing conversions in bulk, which could lead to agent failures in broader tasks.

  • Average 2.6/5 across 1 of 1 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 Apache 2.0.

  • This repository includes a README.md file.

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

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

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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

  • Behavior1/5

    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 only states the conversion function without mentioning any behavioral traits: no information about error handling, performance characteristics, rate limits, authentication needs, or what happens to invalid markdown. This leaves the agent with significant uncertainty about how the tool behaves in practice.

    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 - a single sentence that directly states the tool's function with zero wasted words. It's perfectly front-loaded with the essential information. This is an excellent example of efficiency in description writing.

    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?

    Given the tool's purpose (format conversion), absence of annotations, no output schema, and 0% schema coverage, the description is insufficiently complete. It doesn't address what the output looks like (beyond 'notion json page content'), error conditions, or practical usage considerations. For a conversion tool with no structured documentation support, more context is needed.

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

    Parameters2/5

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

    Schema description coverage is 0% (no parameter descriptions in schema), and the tool has 1 parameter. The description mentions 'markdown content' but provides no additional semantic context about the parameter: no format requirements, size limits, supported markdown features, or examples. It doesn't compensate for the complete lack of schema documentation.

    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 tool's purpose: 'Convert markdown content to notion json page content' - a specific verb ('convert') and resources ('markdown content' to 'notion json page content'). It's unambiguous about what transformation it performs. However, with no sibling tools mentioned, there's no explicit differentiation from alternatives, preventing a perfect score.

    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. It doesn't mention prerequisites, constraints, or typical use cases. While the purpose is clear, there's complete absence of contextual usage instructions.

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

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