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yehudit-alfa

MCP Weather Assistant

by yehudit-alfa

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool has a distinct role in the workflow: open browser, enter city, select from dropdown, extract data. No overlap in functionality.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern with snake_case and the suffix '_israel', making them predictable.

    Tool Count5/5

    Four tools is appropriate for a focused weather scraping assistant, covering the essential steps without excess.

    Completeness4/5

    Covers the main workflow but lacks error handling or a tool to explicitly submit the search, leaving minor gaps.

  • Average 3.3/5 across 4 of 4 tools scored.

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

    • No community issues in the last 6 months
    • 1 commit 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?

    No annotations provided, so description carries full burden. It does not disclose side effects (e.g., overwriting input, triggering search) or any behavioral traits beyond the basic action.

    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 sentence, no wasted words, and gets the point across efficiently.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness3/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    For a simple one-parameter tool it is minimally adequate, but lacks details on what happens after entering (e.g., submission, navigation) and ignores the existing output schema.

    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?

    Schema coverage is 0%, and the description adds no meaning beyond the parameter name 'city_name'. No format, examples, or constraints are given.

    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 (receives and enters a city name into a search field) and distinguishes this tool from siblings which extract, open, or select weather forecast data.

    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 on when to use this tool versus alternatives, no context or exclusions provided. The description only explains what it does without usage conditions.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior2/5

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

    No annotations are provided, so the description must carry the full burden. It states the tool extracts and cleans text, implying a read operation with no side effects, but it omits behavioral details like whether it requires prior navigation, what happens if no page is loaded, or the output format (though an output schema exists).

    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 a single, clear Hebrew sentence that efficiently conveys the tool's action. It front-loads the verb and is free of unnecessary detail.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness3/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    For a tool with no parameters and an output schema, the description provides a basic understanding but lacks contextual completeness. It does not clarify the workflow (e.g., must be used after opening a forecast page) or error conditions. The sibling tools hint at a sequence, but the description alone is insufficient for an agent to know when invocation is valid.

    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 input schema has zero parameters, so schema coverage is effectively 100%. The rules set a baseline of 4 for zero-parameter tools. The description adds no parameter information, which is acceptable since there are none to describe.

    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 extracts, cleans, and returns forecast text from the current page. It uses verbs like 'extracts' and 'cleans', which distinguish it from sibling tools that 'enter', 'open', or 'select'. However, it could be more explicit about which specific forecast page is being referred to.

    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 on when to use this tool versus its siblings. It does not mention prerequisites, such as needing to have navigated to a forecast page first, or that this should be called after using tools like open_weather_forecast_israel.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior2/5

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

    With no annotations, the description must disclose behavioral traits. It indicates a selection action but does not specify the effect (e.g., state change, return value) or any side effects. The existence of an output schema is noted in context but not explained.

    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 a single sentence with no unnecessary words. It is front-loaded and efficient.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness3/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    For a tool with no parameters and an output schema, the description is minimally adequate. However, it lacks details on prerequisites, return value, or interaction with siblings. It could be more informative.

    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?

    There are no parameters, and schema coverage is 100%. The description adds context that the tool selects the first dropdown item, which is helpful beyond the empty schema.

    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 selects the first location from a dropdown list. It uses a specific verb 'selects' and identifies the resource 'first location from dropdown', which distinguishes it from sibling tools like 'enter' or 'extract'.

    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 its siblings. The description does not mention prerequisites (e.g., dropdown must be open) or scenarios where this selection is appropriate.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior2/5

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

    No annotations are provided. The description only says 'opens browser and navigates', which implies a read-like navigation but does not disclose any behavioral traits such as whether it returns data or requires authentication.

    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 a single clear Hebrew sentence with no wasted words. It is front-loaded with the action.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness3/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    The description lacks detail about the output schema, which exists. It does not explain what the tool returns (e.g., a page object or the weather data). This is a gap given that sibling tools provide more specific actions.

    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?

    There are no parameters, so the schema coverage is 100%. With 0 parameters, baseline is 4, and the description adds no parameter info which is fine.

    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 opens the browser and navigates to the main weather page in Israel, which is a specific verb+resource. It distinguishes from siblings like 'enter_weather_forecast_city_israel' which are more specific.

    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 alternatives (e.g., enter_weather_forecast_city_israel or extract_weather_data_israel). The agent must infer from the name.

    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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