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Server Quality Checklist

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  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool has a distinct function: search, get details, reviews, profile, and prompt generation. No overlap in purposes.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern using snake_case, e.g., search_businesses, get_business, get_reviews.

    Tool Count5/5

    5 tools is ideal for the domain, covering the core workflow without being excessive or insufficient.

    Completeness4/5

    The tool set covers the essential workflow for lead generation, though a tool to save or manage prospects could be a minor addition.

  • Average 3.9/5 across 5 of 5 tools scored. Lowest: 3.1/5.

    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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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 must disclose behavioral traits. It indicates a read operation (get) but does not mention mutability, permissions, error behavior, or side effects. For a simple retrieval, more could be said about invariants.

    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?

    Single sentence that efficiently conveys the tool's function and the data returned. No unnecessary words, front-loaded with the main 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?

    For a simple get-by-ID tool with no output schema, the description covers the main purpose and returned data. However, it lacks information on what happens when a place_id is invalid or not found, and whether the output is a single object. Adequate but not fully complete.

    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 coverage is 100% with descriptions for both parameters. The description adds context that place_id is the key identifier and implies language is optional. However, it does not explain the language parameter beyond what the schema already states.

    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 verb 'gets', resource 'complete profile of a business', and identifier 'place_id'. It lists specific data fields (contact, website, rating, categories, location). However, it does not differentiate from the sibling 'get_business_profile', which might be similar.

    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 like search_businesses or get_business_profile. The description only explains what it does, not when it's 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?

    With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions using 'datos reales' and 'mejores reviews' but does not explain whether the tool fetches external data, has side effects, or requires authentication. The description is insufficient for an agent to understand the tool's operational behavior.

    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 sentences with no wasted words. Every sentence adds value: the first states the core function, the second clarifies the intended use case. 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 4 parameters and no output schema, the description provides enough context to understand the purpose but does not explain the return format (a prompt string) or how the tool integrates with the data sources. It is minimally adequate but leaves gaps in a complete mental model.

    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 coverage is 100% and all parameters have descriptions in the schema. The tool description does not add additional meaning beyond the schema, except for implying that 'max_reviews' relates to 'mejores reviews'. Baseline 3 is appropriate since the schema already documents the parameters adequately.

    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 verb (Genera), the resource (prompt para Claude Code que construye una landing page), and the target (venderle al negocio). It is distinct from sibling tools, which are search and retrieval tools, not generation tools.

    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 explicitly says the tool is 'Pensado para venderle la página al negocio', implying when to use it. However, it does not explicitly contrast with siblings or state when not to use it. The context is clear enough for an agent to differentiate from data retrieval tools.

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

  • Behavior4/5

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

    No annotations are provided, so the description carries full burden. It clearly states what the tool returns: profile, reviews, and social networks. It implies a read operation without side effects. Though it does not detail rate limits or authorization, the behavior is straightforward and well-described.

    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 consists of two concise sentences. The first sentence states the core functionality, and the second adds a usage hint. Every word is valuable, with no redundancy or unnecessary detail.

    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?

    Without an output schema, the description provides essential context about the return content (ficha, reviews, social networks). While it lacks detailed structure, the level of detail is sufficient for an agent to understand the tool's output. The sibling tools complement, but this description is self-contained enough.

    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 coverage is 100% with all three parameters (language, place_id, max_reviews) having descriptions. The tool description does not add extra meaning beyond the schema, except noting that social networks are detected from the website. Since parameter descriptions are already clear, a baseline score of 3 is appropriate.

    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 returns the full business profile including listing, reviews, and social networks detected from the website. The verb 'Devuelve' (returns) and the specific components distinguish it from sibling tools like get_business (likely returns only listing) and get_reviews (only reviews). The phrase 'insumo ideal antes de generar el prompt de la página web' provides purpose context.

    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 explicitly mentions this tool is ideal before generating a webpage prompt, indicating a primary use case. However, it does not provide guidance on when not to use it or mention alternative tools. The sibling list includes get_business and get_reviews, but no comparative usage notes.

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

  • Behavior4/5

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

    No annotations provided, but the description discloses the key behavioral distinction: full paginated list with SERPAPI_KEY vs up to 5 reviews without. Mentions the 'complete' field in output. Could add more about read-only nature, but sufficient.

    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 sentences, no wasted words. Action and key distinction front-loaded. Efficient and easy to scan.

    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 3 parameters and no output schema, the description covers the main behavior and output indicator ('complete'). Could mention language filtering, but not critical. Adequate for the tool's complexity.

    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 coverage is 100% with descriptions for all parameters. The description adds the default value for max_reviews (100) not in schema, but otherwise adds little beyond schema. Baseline 3 is appropriate.

    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 it extracts reviews by place_id, with a specific verb 'Extrae' and resource 'reviews de un negocio'. It distinguishes from siblings as none of them deal with reviews.

    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 explains when to use (to get reviews) and provides context about two modes based on SERPAPI_KEY configuration. It lacks explicit when-not-to-use, but the context is clear.

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

  • Behavior4/5

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

    With no annotations, the description explains it returns specific fields (name, address, phone, web, rating, place_id) and mentions default and max results. No destructive behavior implied, but doesn't explicitly state read-only nature.

    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 sentences, no filler. First sentence introduces main action with an example, second sentence summarizes filters and output. Every part is essential.

    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?

    Covers the main purpose, filters, and return data. Missing details on pagination or error handling, but given the complexity (6 params, no output schema), it is mostly complete.

    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?

    Adds value beyond schema by providing example queries and explaining the purpose of the website_filter parameter. Schema already has 100% coverage, so baseline is 3; the description justifies +1.

    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 it searches businesses on Google Maps using free text, and explicitly differentiates from siblings like get_business or get_reviews by focusing on search and filtering.

    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?

    Provides an explicit use case ('ideal para prospectar clientes') but does not mention when to avoid using this tool or alternatives beyond the implied sibling distinction.

    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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Glama performs regular codebase and documentation scans to:

  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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