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rocnubie

reactiontimetest-mcp

by rocnubie
OverviewSchemaRelated ServersScoreDiscussions
JavaScript
Hybrid

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool has a distinct purpose: one provides test overview and rules, the other provides official links. There is no overlap or ambiguity between them.

    Naming Consistency5/5

    Both tool names follow a consistent 'get_' prefix followed by a descriptive noun phrase, maintaining a uniform and predictable naming pattern.

    Tool Count4/5

    With only 2 tools, the server is minimal but appropriately scoped for an informational purpose. Slightly low but still reasonable for a focused utility.

    Completeness3/5

    The server covers providing test overview and links, but lacks any interactive or result-related functionality (e.g., running a test), which could be expected from a reaction time test server.

  • Average 3.9/5 across 2 of 2 tools scored.

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

    • No community issues in the last 6 months
    • No commit activity data available
    • No stable releases found
    • 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.

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

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

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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

  • Behavior3/5

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

    With no annotations provided, the description carries full burden. It states the tool 'Return's data, implying a read-only operation, but does not explicitly confirm idempotency, auth requirements, or potential side effects. For a zero-parameter tool, the lack of behavioral details is acceptable but not exemplary.

    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 two sentences, front-loaded with the action, and contains no redundant words. Every part earns its place, providing clear purpose without unnecessary detail.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness4/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    For a tool with no parameters and no output schema, the description adequately explains what it returns. It could mention the format or structure of the catalog, but the context is sufficient given the tool's simplicity and the presence of a sibling.

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

    Parameters4/5

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

    The tool has zero parameters, and the schema is empty with 100% coverage. The description does not need to add parameter information since none exist. According to the rubric, baseline is 4 for zero parameters.

    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 uses a specific verb 'Return' and identifies the resource as 'test catalog and documented measurement or scoring rules', with a parenthetical specification for 'Reaction Time Test'. This clearly distinguishes it from the sibling tool 'get_official_links', which likely returns links rather than test overviews.

    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 provided on when to use this tool versus alternatives. There is no mention of prerequisites, context, or when not to use it. The only sibling is named but no comparison is made.

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

  • Behavior3/5

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

    No annotations provided, so description carries burden. It discloses it returns a canonical list and that links are 'when available', but no details on authentication, rate limits, or response format beyond that.

    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?

    Single sentence, front-loaded with purpose, no wasted words.

    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?

    Simple tool with no parameters and no output schema; description adequately covers what it returns and for which test.

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

    Parameters4/5

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

    No parameters exist, so schema coverage is 100%. Description adds no parameter info, but baseline for 0-param tools is 4.

    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 returns the canonical list of official links for Reaction Time Test, specifying types (website, support, docs). It is specific and distinguishes from the sibling get_test_overview.

    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 explicit guidance on when to use this tool versus the sibling get_test_overview. No when-not-to-use or alternative references. Usage context is only implicit.

    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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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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