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BACH-AI-Tools

World Time By Api Ninjas

by BACH-AI-Tools
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

Server Quality Checklist

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

  • Latest release: v1.0.0

  • Disambiguation5/5

    With only one tool, there is no possibility of ambiguity or overlap between tools. The single tool 'v1worldtime' has a clear and distinct purpose: retrieving world time data based on various location parameters.

    Naming Consistency5/5

    A single tool inherently has perfect naming consistency, as there are no other tools to compare it against. The name 'v1worldtime' follows a clear pattern (version prefix + descriptive name) and does not conflict with any other naming conventions.

    Tool Count2/5

    A single tool is generally too few for most server purposes, as it limits functionality and flexibility. While this tool covers world time retrieval comprehensively, the server's scope feels thin with only one operation, which may hinder agent workflows that require more diverse interactions.

    Completeness4/5

    For the domain of world time retrieval, the tool provides robust coverage with support for city/state/country, coordinates, and timezone inputs. However, there are minor gaps, such as lacking tools for timezone conversion, historical time data, or batch queries, which could limit advanced use cases.

  • Average 3.1/5 across 1 of 1 tools scored.

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

    • No community issues in the last 6 months
    • 0 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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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?

    No annotations are provided, so the description carries the full burden. It mentions the tool returns data but doesn't disclose behavioral traits like rate limits, authentication needs, error handling, or response format. The description is minimal and doesn't compensate for the lack of annotations.

    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 appropriately sized and front-loaded, starting with the purpose and followed by parameter combination rules. Every sentence adds necessary information without waste, though it could be slightly more structured for clarity.

    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 the tool's moderate complexity (6 parameters, no output schema, no annotations), the description is incomplete. It lacks details on return values, error cases, or any behavioral context, making it insufficient for an AI agent to fully understand tool invocation and response handling.

    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%, so the schema fully documents all 6 parameters. The description adds value by explaining the required parameter combinations (e.g., lat+lon, city with optional state/country, timezone), which clarifies semantics beyond individual param descriptions, but doesn't provide additional syntax or format details.

    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's purpose: 'Returns the current date and time' with multiple location input methods. It specifies the verb ('Returns') and resource ('current date and time'), but lacks differentiation from siblings since none exist, making it clear but not distinguishing.

    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 implied usage by stating 'One of the following parameter combinations must be set' with examples, which guides when to use certain parameters. However, it lacks explicit when-not scenarios or alternative tool references, and no siblings exist for comparison, so guidance is basic.

    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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