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ChenchaoZhao

paper-search

by ChenchaoZhao
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 or overlap with other tools. The tool's purpose is clearly defined as searching academic literature.

    Naming Consistency4/5

    With a single tool, naming consistency is trivially maintained. The name 'search_papers' follows a clear verb_noun pattern, which is a good convention.

    Tool Count2/5

    A single tool for a paper search server is extremely thin. While the tool is comprehensive in its search capabilities, the server lacks any other functionality such as fetching paper details, managing libraries, or retrieving citations, making the count feel insufficient for a full-featured server.

    Completeness2/5

    The server only provides search functionality, which is a core feature but leaves obvious gaps. For a paper search server, one would expect at least a tool to fetch details of a specific paper, and possibly tools for saving or managing papers. The current surface is incomplete for a comprehensive academic literature tool.

  • Average 4.6/5 across 1 of 1 tools scored.

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

    • No community issues in the last 6 months
    • 5 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

  • 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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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?

    No annotations are provided, so the description carries full responsibility for behavioral disclosure. It mentions 'deduplicated and ranked results', 'JSON' output, and the concept of keyless sources, which hints at API key requirements. It does not explicitly mention error handling or latency, but for a search tool, this is adequate. The behavior is sufficiently described.

    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 concise and well-structured: an opening one-sentence overview followed by a clean Args section. Each parameter is given a clear explanation. There is no extraneous information, and it is front-loaded with the key purpose.

    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?

    With 5 parametersaren and an output schema present, the description fully explains what the tool does, what each parameter means (including defaults and examples), and the output format (JSON, deduplicated, ranked). It covers behavioral aspects like source selection and default behavior. Given the output schema exists, no further details on return structure are needed.

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

    Parameters5/5

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

    The schema provides only names and types (0% coverage). The description compensates fully by explaining each parameter: query (with example), sources (with list of allowed values), max_results_per_source, year_from, and year_to. It adds meaning beyond the schema, including defaults and examples, making it highly instructive for the agent.

    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's purpose: 'Search academic literature across multiple sources, returning deduplicated and ranked results as JSON.' It specifies the action (search), the resource (academic literature), and the output format (JSON). Since there are no sibling tools, it doesn't need to differentiate, but it is specific and unambiguous.

    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 provides usage context by explaining defaults (e.g., 'Defaults to all keyless free sources') and listing sources, which helps the agent decide when to call this tool. However, it lacks explicit when-not-to-use guidance or exclusion criteria, which would elevate it to 5. Still, it clearly implies the intended use case.

    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 there are no obvious security issues.
  • Evaluate tool definition quality.

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