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Server Quality Checklist

83%
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  • Latest release: v0.3.8

  • Disambiguation5/5

    Only one tool exists, so there is no risk of confusion or overlap with other tools.

    Naming Consistency5/5

    The single tool name 'load_ditto_profile' follows a clear verb_noun pattern, which is consistent and predictable.

    Tool Count4/5

    With exactly one tool, the server is narrowly scoped to profile loading; while minimal, it is appropriate for a focused utility.

    Completeness3/5

    The tool covers loading a profile but lacks supporting operations like creating, updating, or deleting profiles, which are notable gaps for profile management.

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

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

    • 2 of 2 community issues answered or closed in the last 6 months
    • 328 commits in the last 12 weeks
    • Last stable release on
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is passing
  • This repository is licensed under MIT License.

  • 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.

  • This repository includes a glama.json configuration file.

  • This server has been verified by its author.

  • Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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

  • Behavior5/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    Despite no annotations, the description fully discloses behavior: it loads a profile to make the agent act like the user, returns profile text or a recovery instruction, and explains domain semantics. No hidden side effects or contradictions.

    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?

    Two sentences with no filler. The first sentence covers purpose and timing, the second covers domain definitions and return value. Efficiently communicates all necessary information.

    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?

    Given the simple input schema and no output schema, the description covers purpose, usage guidance, parameter semantics, and return value. No gaps remain for effective agent invocation.

    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 single parameter 'domain' has 100% schema coverage with an enum and description. The description adds rich meaning by explaining what each domain represents (execution, debugging, UI/UX, writing voice), far exceeding the schema's minimal description.

    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 loads the user's Ditto profile to mimic them, specifies when to call it, and explains the domains with concrete examples. It distinctly identifies the tool's purpose and resource.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines5/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    Explicitly instructs to 'Call this before working on their task', and details the three domains and their coverage (work, design, write). This provides clear guidance on when and how to use the tool.

    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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