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self-tech-labs

Entscheidsuche MCP Server

by self-tech-labs
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JavaScript

Server Quality Checklist

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

  • Latest release: v1.0.0

  • Disambiguation5/5

    Each tool has a clearly distinct purpose: get_document retrieves specific document content, list_courts provides metadata about courts, and search_case_law performs searches across the database. There is no overlap in functionality, making tool selection straightforward for an agent.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern (get_document, list_courts, search_case_law) with clear, descriptive verbs. There are no deviations in naming conventions, making the set predictable and easy to understand.

    Tool Count3/5

    With only 3 tools, the server feels somewhat thin for a legal document search domain. While the tools cover core operations (retrieve, list, search), more comprehensive coverage might include tools for filtering, advanced search, or document metadata management, suggesting a borderline appropriateness.

    Completeness3/5

    The tools provide basic CRUD-like operations (get, list, search) for legal documents and courts, but there are notable gaps. For example, there is no tool for updating or deleting documents, managing user queries, or handling advanced search parameters, which could limit agent effectiveness in complex workflows.

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

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

  • This repository is archived. Archived repositories automatically receive an F maintenance tier.

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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?

    With no annotations provided, the description carries full burden for behavioral disclosure. While 'Retrieve' implies a read operation, it doesn't disclose important behavioral aspects like authentication requirements, rate limits, error conditions, response format, or whether this is a simple fetch versus a complex operation. The description is minimal and lacks operational 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 no wasted language, repetition, or unnecessary elaboration. It's front-loaded with the core functionality.

    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?

    For a tool with 3 parameters, no annotations, and no output schema, the description is insufficiently complete. It doesn't explain what constitutes a valid document signature, how the retrieved content is structured, error handling, or operational constraints. The minimal description leaves too many questions unanswered for effective tool usage.

    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?

    With 100% schema description coverage, the schema already documents all three parameters thoroughly. The description adds no parameter-specific information beyond what's in the schema - it doesn't explain the relationship between signature and spider parameters, provide examples of valid signatures, or clarify the format parameter's implications.

    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 action ('Retrieve') and resource ('full content of a specific legal document'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'search_case_law' or 'list_courts' - it doesn't explain that this retrieves a single document by signature rather than searching or listing.

    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 about when to use this tool versus alternatives. There's no mention of prerequisites, when this tool is appropriate versus 'search_case_law', or any context about what constitutes a 'specific legal document' that can be retrieved.

    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 carries full burden but only states the basic function. It lacks details on behavioral traits such as rate limits, authentication needs, error handling, or what the search returns (e.g., result format, metadata). This is inadequate for a search tool with no output schema.

    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, efficient sentence that directly states the tool's purpose without redundancy. It's front-loaded and wastes no words, making it easy to parse quickly.

    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 complexity of a search tool with no annotations or output schema, the description is insufficient. It doesn't explain what the search returns, how results are structured, or any limitations, leaving gaps for the agent to understand the tool's behavior fully.

    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 parameters like 'query' for search terms and 'from/size' for pagination. The description adds no additional meaning beyond implying a legal context, meeting the baseline for high schema coverage.

    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 action ('Search') and target resource ('Swiss court decisions') with the specific database ('Entscheidsuche'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'get_document' or 'list_courts', which might also retrieve legal information.

    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. The description doesn't mention scenarios for searching case law compared to getting specific documents or listing courts, leaving the agent to infer usage from tool names alone.

    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 carries the full burden. It mentions 'Get information' but doesn't disclose behavioral traits such as whether this is a read-only operation, potential rate limits, authentication needs, or what format the information is returned in. The description is minimal and lacks essential context for safe invocation.

    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, efficient sentence that directly states the tool's purpose without any fluff or unnecessary details. It is front-loaded and appropriately sized for a simple tool with no parameters.

    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 'information' includes (e.g., court names, IDs, document counts), how results are structured, or any limitations. For a tool that returns data, more context is needed to guide the agent effectively.

    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 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, and since there are none, it meets the baseline of 4 for not introducing confusion or redundancy.

    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 'Get' and the resource 'information about available courts and their document counts', which is specific and actionable. However, it doesn't explicitly differentiate from sibling tools like 'search_case_law', which might also involve court information but with different functionality.

    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 like 'search_case_law'. It lacks context about use cases, prerequisites, or exclusions, leaving the agent to infer usage based on the tool name and description alone.

    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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