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animaios

anima-use-google

by animaios
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Server Quality Checklist

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

  • Latest release: v0.1.6

  • Disambiguation5/5

    With only one tool, there is no possibility of confusion between tools. The single tool has a clear, distinct purpose.

    Naming Consistency5/5

    Only one tool exists, so naming consistency is not an issue. The name 'search_google_ai' follows a clear verb_noun pattern.

    Tool Count3/5

    At 1 tool, the count is at the lower end of the borderline range. While the tool performs a specific function well, the server feels thin for broader use.

    Completeness5/5

    The tool fully covers the stated purpose of performing a Google AI Mode search. There are no obvious gaps given the server's narrow scope.

  • Average 3.9/5 across 1 of 1 tools scored.

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

    • No community issues in the last 6 months
    • 20 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 The Unlicense.

  • 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

  • Behavior4/5

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

    With no annotations, the description carries full burden. It discloses that the tool uses the user's Firefox session, is free, grounded, and returns AI-synthesized answers with citations. It does not mention rate limits or side effects, but the key behaviors are transparent.

    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-loading the action and resource, then adding a valuable second sentence about the output and benefits. Every word earns its place; no redundancy.

    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 no output schema, the description adequately explains the return value (AI answer with citations and source list). It also mentions the URL format and prerequisite (logged-in Firefox session). For a two-parameter tool, this is complete.

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

    Parameters3/5

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

    Schema coverage is 100% (both query and timeout_ms have schema descriptions). The description does not add additional meaning for the parameters themselves but provides context about the output format (AI-synthesized answer with citations). Baseline 3 is appropriate.

    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?

    Description clearly states it runs a Google AI Mode search and returns AI-synthesized answer with citations and source list. The verb 'Run a search' and resource 'Google AI Mode search' are specific. Though no sibling tools are listed, the description distinguishes it by mentioning 'free, grounded, no API key'.

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

    Usage Guidelines3/5

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

    Description implies the tool requires a logged-in Firefox session and is free and grounded, but does not explicitly state when to use versus alternatives or provide when-not scenarios. The usage context is implied rather than direct.

    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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