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thedaviddias

MCP LLMS.txt Explorer

by thedaviddias
OverviewSchemaRelated ServersScoreDiscussions
JavaScript
Remote

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 have clearly distinct purposes: check_website verifies the presence of llms.txt files on a specific website, while list_websites retrieves a list of known websites that already have such files. There is no overlap in functionality, making it easy for an agent to select the appropriate tool based on the task.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun pattern (check_website and list_websites), using snake_case and clear action verbs. This uniformity makes the tool set predictable and easy to understand, with no deviations in naming conventions.

    Tool Count2/5

    With only two tools, the server feels under-scoped for exploring llms.txt files. While the tools cover basic checking and listing, there are likely missing operations such as fetching file contents, updating lists, or analyzing data, which limits the server's utility for comprehensive exploration.

    Completeness2/5

    The tool set is severely incomplete for an 'Explorer' server. It lacks essential operations like retrieving the actual llms.txt content, validating file structure, searching within files, or managing the list of websites. This creates significant gaps that will hinder agents from performing meaningful exploration tasks.

  • Average 3/5 across 2 of 2 tools scored.

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

    • 0 of 2 community issues answered or closed 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 status not available

  • 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 of behavioral disclosure. It states the tool checks for 'llms.txt files,' implying a read-only operation, but doesn't specify what 'check' entails (e.g., HTTP request details, error handling, or output format). For a tool with no annotations, this is a significant gap in transparency.

    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 sentence with no wasted words. It's front-loaded with the core purpose and efficiently conveys the tool's function without unnecessary elaboration, making it highly concise and well-structured.

    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 lack of annotations and output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., boolean result, file details, or error messages) or any behavioral aspects like rate limits or authentication needs. For a tool with no structured support, the description should provide more context to be fully helpful.

    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 has 100% description coverage, with the 'url' parameter fully documented. The description doesn't add any semantic details beyond the schema, such as URL format requirements or examples. Given the high schema coverage, the baseline score of 3 is appropriate, as the schema handles the parameter documentation adequately.

    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: 'Check if a website has llms.txt files.' It specifies the verb ('check') and resource ('website'), making the action explicit. However, it doesn't differentiate from the sibling tool 'list_websites,' which likely serves a different function (listing vs. checking), so it doesn't reach the highest score.

    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?

    The description provides no guidance on when to use this tool versus alternatives. It doesn't mention the sibling tool 'list_websites' or any other context for usage, such as prerequisites or scenarios. This leaves the agent without direction on tool selection.

    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 full burden for behavioral disclosure. It mentions that the tool lists websites 'with llms.txt files' but doesn't describe what 'known websites' means, whether this is a read-only operation, what format the output takes, or any limitations (like pagination or rate limits). The description is minimal and lacks important behavioral context.

    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 extremely concise - a single sentence that directly states the tool's purpose. There's zero waste or unnecessary elaboration. It's appropriately sized for a simple listing tool with well-documented parameters.

    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 listing tool with 100% schema coverage but no annotations and no output schema, the description is adequate but has clear gaps. It explains what the tool does but doesn't provide context about what constitutes 'known websites' or what the output format will be. The description meets minimum viability but could be more 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 description coverage is 100%, so the schema already documents both parameters (filter_llms_txt and filter_llms_full_txt) with clear descriptions. The description doesn't add any parameter semantics beyond what's in the schema - it doesn't explain how these filters work together or their default behavior. Baseline 3 is appropriate when schema does the heavy lifting.

    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: 'List known websites with llms.txt files' specifies both the action (list) and resource (websites with llms.txt files). However, it doesn't explicitly differentiate from the sibling tool 'check_website', which likely serves a different purpose (possibly checking individual websites rather than listing them).

    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?

    The description provides no guidance on when to use this tool versus alternatives. There's no mention of the sibling tool 'check_website' or any context about when listing websites is appropriate versus checking individual ones. The description simply states what the tool does without usage context.

    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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