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Server Quality Checklist

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  • Latest release: v0.1.0

  • Disambiguation5/5

    With only one tool, there is no possibility of confusion between tools. The purpose is clearly defined as a deterministic execution guardrail.

    Naming Consistency5/5

    The single tool name 'dros_evaluate' uses a clear verb_noun style. With only one tool, naming consistency is trivially satisfied.

    Tool Count5/5

    The server has a narrowly scoped purpose, acting as a single guardrail evaluation function. One tool fully serves that purpose without unnecessary extras.

    Completeness5/5

    For its stated domain of evaluating actions as a guardrail, the single tool covers the necessary functionality completely. There are no obvious missing operations within this narrow scope.

  • Average 2/5 across 1 of 1 tools scored.

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

    • No community issues in the last 6 months
    • 21 commits in the last 12 weeks
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is passing
  • Add a LICENSE file by following GitHub's guide. Once GitHub recognizes the license, the system will automatically detect it within a few hours.

    If the license does not appear after some time, you can manually trigger a new scan using the MCP server admin interface.

    MCP servers without a LICENSE cannot be installed.

  • 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

  • Behavior2/5

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

    No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'deterministic' and 'sub-microsecond latency', which are useful behavioral traits, but it does not explain side effects, whether the tool blocks/allows execution, return values, or failure modes. The key behavior—what happens with the evaluation result—is left unspecified.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness3/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is a single sentence with no redundancy—it is concise in the sense of being short. However, it under-specifies the tool so severely that the brevity is more a symptom of incompleteness than effective conciseness. It is not bloated, but it doesn't earn its place as a useful summary.

    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?

    For a tool with no output schema and no annotations, the description must carry a heavy burden. It gives only a vague functional hint and a couple of non-functional attributes, but fails to describe inputs, outputs, side effects, or evaluation semantics. The tool is not adequately contextualized for correct invocation.

    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 or even mention the parameters 'capability' or 'parameters'. There is no indication of what values 'capability' accepts or what structure 'parameters' should follow. The description adds no meaning beyond the bare schema, leaving the agent unable to construct a valid invocation.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose2/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description uses vague, jargon-heavy language ('in-band execution guardrail', 'evaluating actions') without clarifying concretely what the tool does. The verb 'evaluating' and resource 'actions' are generic, and the purpose remains ambiguous—it is not obvious what action is evaluated, how, or for what decision.

    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?

    No guidance is given about when to use this tool. With no sibling tools listed, there are no alternatives to contrast against, but the description also lacks any context about the intended invocation scenario or prerequisites. The agent is left to infer usage entirely from the tool name and vague description.

    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.
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  • Evaluate tool definition quality.

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