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nihalpatel99

flight

by nihalpatel99
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.1.0

  • Disambiguation5/5

    With only a single tool, there is no ambiguity whatsoever. The tool's purpose is clearly distinct by virtue of being the only one.

    Naming Consistency5/5

    The single tool name 'search_flights' follows a clear verb_noun convention, and consistency is trivially satisfied with just one name.

    Tool Count2/5

    Having only one tool for a flight-related server is too few. While the search functionality is useful, a typical flight service would expect additional operations like booking, cancellation, or flight status, making this feel extremely minimal for the apparent domain.

    Completeness2/5

    The tool surface is severely incomplete for the flight domain—it only covers searching. There are no tools for selecting, booking, modifying, or canceling flights, which are obvious core operations, leading to significant gaps that would cause agent failures in real workflows.

  • Average 4.3/5 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 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

  • Behavior3/5

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

    With no annotations, the description is the sole source of behavioral context. It conveys that the tool uses Google Flights via SerpApi, implying a remote read-only search operation. However, it doesn't disclose potential rate limits, result format expectations, or edge cases such as airport code validation, so some behavior is left implied.

    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 compact and front-loaded with the core intent, followed by a precise argument list. No filler or redundancy; each line contributes necessary semantic value. The structure makes it easy for an agent to quickly parse and use.

    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 5-parameter flight search tool, the description is highly complete: all parameter constraints and defaults are covered, and an output schema is present to cover return values. It misses only minor non-critical details such as potential downstream API limitations, but not enough to significantly confuse an agent.

    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?

    Schema description coverage is 0%, so the description must fully clarify parameters. It does so well: lists each argument with format examples and defaults, clarifies that return_date being omitted means one-way, and explains currency defaults to USD. This is far more helpful than the raw 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 clearly states the action ('Search for flights') and names the resource (Google Flights via SerpApi). Although there are no sibling tools to differentiate, the verb+resource+integration context makes the purpose 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 implies when to use the tool: whenever flight search is needed. It provides clear context through operational details like omit return_date for one-way trips, but does not explicitly mention alternatives or exclusions. With no siblings, this is acceptable.

    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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