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amoljagtap17

users

by amoljagtap17
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Server Quality Checklist

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

  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools are clearly distinguished by their lookup parameter: email vs. name. Descriptions explicitly state each input, so an agent can confidently select the appropriate tool without ambiguity.

    Naming Consistency5/5

    Both tools follow the same verb_noun_by_attribute pattern (get_user_by_...). This is consistent and predictable, making it easy to infer behavior from the name.

    Tool Count3/5

    With only 2 tools, the server feels thin, but the scope may be intentionally limited to user lookup. It is not as extreme as having a single trivial tool, so it sits at the borderline.

    Completeness2/5

    The server only provides read operations for users. There are no create, update, delete, or list endpoints, which are essential for a 'users' domain. This is a significant functional gap that will hinder agents needing full user lifecycle management.

  • Average 3.7/5 across 2 of 2 tools scored.

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

    • No community issues in the last 6 months
    • 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 status not available

  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

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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?

    Annotations already declare readOnlyHint=true and destructiveHint=false, covering the safety profile. The description adds that the result includes id, name, and email, which is useful behavioral information. It does not mention not-found behavior or case sensitivity, but the annotations lower the burden.

    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 concise sentences, front-loaded with the action verb. Every word earns its place, with no redundancy or filler.

    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 single-parameter read tool with rich annotations and an output schema, the description covers the essential purpose and return shape. It lacks usage guidance, but that is captured under dimension 2. Slightly minimal but sufficient.

    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?

    The schema has 100% description coverage with a clear description for the 'email' parameter, so the description does not need to add much. The description does not go beyond the schema's format/pattern details. Baseline of 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?

    The description clearly states 'Get user information by email', specifying the verb, resource, and lookup method, and lists the returned fields. However, it does not explicitly distinguish this tool from the sibling 'get_user_by_name', so it falls short of a 5.

    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 the sibling 'get_user_by_name'. The description does not mention alternatives or exclusions, leaving the agent without context for choosing between the two lookup methods.

    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?

    Annotations already declare readOnly, openWorld, and idempotent behavior. The description adds that it returns id, name, and email, but since an output schema exists, this is redundant. No additional behavioral context like not-found behavior is provided.

    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?

    Two short sentences, front-loaded with the main purpose. No wasted words; 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?

    For a simple read tool with good annotations and an output schema, the description is adequate. It could be more complete by mentioning when to use this over get_user_by_email or handling edge cases, but the core is clear.

    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?

    The input schema already provides 100% coverage with a description for the 'name' parameter. The tool description repeats the parameter's role without adding syntax or formatting details, so it adds minimal value beyond the schema.

    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 'Get' and resource 'user information' with a clear lookup key 'by name', which distinguishes it from the sibling tool get_user_by_email. The return fields are stated, making the purpose unmistakable.

    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 implies usage when you have a name to look up, but it doesn't explicitly contrast with get_user_by_email or state when not to use this tool. No alternatives are mentioned, so usage guidance is only implied.

    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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