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JerryLiu369

agent-web-search

by JerryLiu369
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

Server Quality Checklist

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

  • Latest release: v0.1.0

  • Disambiguation5/5

    Only one tool exists, so there is no possibility of confusion between tools. The single tool 'web_search' has a clearly defined purpose.

    Naming Consistency5/5

    The single tool name 'web_search' follows a clear verb_noun pattern and is self-explanatory. Consistency is trivially satisfied with one tool.

    Tool Count3/5

    With only one tool, the server is very minimal but appropriate for a focused web search purpose. It borders on thin but is not extreme.

    Completeness4/5

    For a web search server, the single search operation covers the core need. Additional features like image search or advanced filters are absent, but not strictly required for basic functionality.

  • Average 3.6/5 across 1 of 1 tools scored.

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

    • No community issues in the last 6 months
    • 8 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 MIT License.

  • This repository includes a README.md file.

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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

  • Behavior2/5

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

    With no annotations provided, the description carries full responsibility for disclosing behavioral traits. It only says 'Search the web' and lists providers. There is no mention of rate limits, authentication, result formatting, or any side effects. This is a significant gap for a tool that may have varying provider behaviors.

    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 exceptionally concise, consisting of two short sentences that convey all essential information. It is front-loaded with the primary action and includes relevant provider details without verbosity.

    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 simple, well-scoped tool with a comprehensive schema and no siblings or output schema, the description is adequately complete. It could potentially mention that results come from multiple providers and may vary, but the current description sufficiently conveys the tool's functionality.

    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 description coverage is 100%, with each parameter having a description, so the baseline is 3. The tool description adds no additional parameter-level meaning beyond what the schema already provides, matching the baseline without adding value.

    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 'Search the web' with a specific verb and resource, and differentiates itself by listing the enabled providers (Volcengine ARK, DuckDuckGo, Exa). This is precise and unambiguous, even without sibling tools to distinguish from.

    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?

    The description provides no explicit when-to-use or when-not-to-use guidance, nor any alternatives since there are no sibling tools. The instruction to 'Use a complete natural-language question' is about query formatting, not tool selection. Usage is implied by the tool's name and purpose, meeting the 'implied usage' baseline.

    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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