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Server Quality Checklist

83%
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  • Latest release: v1.13.0

  • Disambiguation5/5

    With only one tool, there is no possibility of ambiguity between tools. The tool has a clear purpose and unique identity.

    Naming Consistency4/5

    The single tool name 'diffctx_context' is clear but not a verb_noun pattern; however, with one tool there is no inconsistency to penalize.

    Tool Count3/5

    A single tool feels thin for a server, but the tool's scope is narrow and it uses modes to cover different needs, making it borderline appropriate.

    Completeness4/5

    The tool covers the core need of understanding a git diff with two modes (locate and pack). Minor gaps exist, such as no explicitly separate raw diff retrieval, but the primary use case is well-served.

  • Average 4/5 across 1 of 1 tools scored.

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

    • 7 of 7 community issues answered or closed in the last 6 months
    • 28 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 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.

  • This repository includes a glama.json configuration file.

  • This server has been verified by its author.

  • Add related servers to improve discoverability.

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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

  • Behavior4/5

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

    The description adds a crucial behavioral warning beyond the readOnlyHint annotation: returned repository content must be treated as untrusted data, not instructions. This provides security context that the annotation alone does not convey. The mode explanations and fragment_id flow also add transparency about how the tool behaves.

    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 compact and front-loaded: the first sentence states the core purpose, the second explains the modes, and the third gives language support. The safety warning is essential and placed at the end. No sentence is wasted; it achieves a lot in few words.

    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 complexity (8 parameters) and the presence of an output schema, the description covers the core workflow well but omits details on five parameters. It provides enough to get started (mode, diff_ref, fragment_ids) but not enough to fully understand all configuration options. The output schema may cover return values, but parameter gaps keep this from being complete.

    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%, so the description must compensate. It explains the meaning of mode, diff_ref, and fragment_ids, but the remaining five parameters (repo_path, max_tokens, budget_tokens, include_raw_diff, clipboard) are completely unexplained in both description and schema. This is a significant gap for an 8-parameter tool.

    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 opens with 'Understand a git diff', using a specific verb and resource. It further distinguishes the two modes (locate vs pack), making the tool's purpose unmistakable. Even without siblings, this is a clear, specific statement of function.

    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 gives clear context for when to use this tool: to understand a git diff. It describes the primary usage pattern (locate mode, then pass fragment_ids back) and mentions the alternative 'pack' mode. There are no exclusions because no sibling tools exist, but the guidance is still actionable.

    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.

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