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akhileshvj

Research Server

by akhileshvj
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Python
Local

Server Quality Checklist

50%
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  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool has a clearly distinct purpose: one retrieves stored local information by paper ID, the other searches arXiv for papers by topic. No overlap or ambiguity.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun pattern: 'extract_info' and 'search_papers'. No mixed conventions.

    Tool Count3/5

    With only 2 tools, the server feels under-scoped for a 'Research Server'. More tools like list, delete, or update would be expected, but the count is not extreme.

    Completeness3/5

    The surface covers search and retrieval by ID, but lacks essential operations like listing all stored papers, deleting, or updating entries, leaving notable gaps.

  • Average 3.1/5 across 2 of 2 tools scored.

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

    • No community issues in the last 6 months
    • 3 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

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  • 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?

    The description mentions 'store their information', indicating a side effect of persisting data. However, it does not disclose details such as where storage occurs, whether results are returned, authentication needs, rate limits, or any other behavioral traits. With no annotations provided, the description carries full burden and falls short.

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

    Conciseness4/5

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

    The description is a single concise sentence that front-loads the core action. It is efficient but could benefit from additional structure (e.g., listing parameters or side effects).

    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?

    Given two parameters, no annotations, one sibling tool, and an existing output schema (not provided), the description is incomplete. It lacks details on parameter usage (especially max_results), return value (despite output schema existing), side effects of storage, and differentiation from sibling. The description does not adequately compensate for the schema's lack of description.

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

    Parameters2/5

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

    The input schema has 0% description coverage, so the description must compensate. It specifies the 'topic' parameter implicitly ('based on a topic') but does not explain the 'max_results' parameter or any constraints/format for either parameter. The description adds little meaning beyond the schema's bare parameter names and types.

    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?

    The description clearly states 'Search for papers on arXiv based on a topic and store their information', which specifies the verb (search), resource (papers on arXiv), and action (store). However, it does not explicitly distinguish from the sibling tool 'extract_info', though the verb 'search' vs 'extract' provides implicit differentiation.

    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?

    The description provides no guidance on when to use this tool versus alternatives like 'extract_info', nor does it mention prerequisites, limitations, or when not to use it.

    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 are provided, so the description bears full responsibility for behavioral disclosure. It states the tool 'searches stored local information' which implies a read-only operation, but does not detail side effects, limitations, or what exactly 'stored local information' means. It adds modest context beyond the schema, but is not fully 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 extremely concise: two sentences total, with the first stating the purpose and the second describing the parameter. No unnecessary words, and the most important information is front-loaded. Every sentence earns its place.

    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?

    Given the tool has one parameter, an output schema, and a sibling tool, the description is reasonably complete. It explains what the tool does and the input, but does not mention any prerequisites (e.g., that the paper must have been previously stored locally) or what happens if the ID is not found. The output schema likely covers return values, so the description does not need to. A 4 is appropriate for a simple tool.

    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 schema has 0% description coverage, but the description adds meaningful context: it specifies that 'paper_id' is 'The unique short ID of the paper.' This clarifies the format and uniqueness, which goes beyond the schema's title and type. This compensates well for the lack of schema descriptions.

    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?

    The description clearly states the tool searches for stored local information about a specific paper by its ID. It uses a specific verb ('Search') and resource ('information about a paper'), and the sibling tool 'search_papers' likely searches across papers, implying a distinction. However, it does not explicitly differentiate from the sibling, so a 4 is appropriate.

    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?

    The description does not provide any guidance on when to use this tool versus alternatives, nor does it mention prerequisites or scenarios where it should not be used. It only implicitly suggests use when a paper ID is available, but lacks explicit usage context.

    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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