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matematicsolutions

ch-eli-mcp

by matematicsolutions
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Server Quality Checklist

75%
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  • Latest release: v0.3.3

  • Disambiguation5/5

    Each tool has a clearly distinct purpose: searching act titles, fetching an act by ELI URI, and declaring coverage/gaps. There is no meaningful overlap between them.

    Naming Consistency4/5

    The ch_ prefix is consistent and data operations follow a verb_noun pattern: ch_search_acts and ch_get_act. ch_coverage deviates slightly by being a noun-only name, but the pattern is still readable and predictable.

    Tool Count4/5

    Three tools is lean but reasonable for a narrowly scoped legal retrieval connector. The count is slightly small, but each tool contributes a distinct capability rather than padding the surface.

    Completeness3/5

    The connector covers the essential search-and-fetch workflow for Swiss federal acts, and the explicit coverage tool helps surface gaps. However, the surface is minimal and lacks obvious conveniences such as browsing by family or fetching act versions, so some workflows will still require fallback to external sources.

  • Average 4.2/5 across 3 of 3 tools scored.

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

    • No community issues in the last 6 months
    • 13 commits in the last 12 weeks
    • Last stable release on
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is passing

  • This repository is licensed under Apache 2.0.

  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

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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?

    Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, fully covering safety. The description adds no additional behavioral traits beyond the stated operation.

    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, no wasted words, front-loaded with the essential action. Perfectly concise for a simple search tool.

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

    Completeness5/5

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

    Given the tool's simplicity (read-only search, 3 parameters, output schema exists), the description is complete. It covers the domain and operation sufficiently.

    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 baseline is 3. The description does not add meaning beyond the schema; it only repeats the operation.

    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 'Full-text search over Swiss federal act titles', specifying both the verb (search) and resource (Swiss federal act titles). It distinguishes from the sibling tool ch_get_act, which likely retrieves a single act.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines3/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description implies use for searching act titles but provides no explicit guidance on when to use this tool versus the sibling ch_get_act, nor any exclusions or conditions.

    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?

    Annotations already declare readOnly, openWorld, idempotent, and non-destructive hints. Description adds context about fetching full detail and the source (Fedlex ELI URI). No contradiction; no additional behavioral traits needed beyond what annotations provide.

    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, well-structured sentence with no extraneous words. Every element is purposeful.

    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 simple tool with 2 parameters, rich annotations, and an output schema, the description covers the essential purpose and usage. Could mention output schema existence, but not required.

    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 baseline is 3. Description reinforces 'uri' by mentioning 'by its Fedlex ELI URI', but provides no extra semantic for 'lang'. Minimal added value over 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?

    Description clearly specifies verb 'Fetch', resource 'full detail for one Swiss federal act', and method 'by its Fedlex ELI URI'. It distinguishes from sibling ch_search_acts which presumably searches for acts, while this retrieves a specific one.

    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?

    Description implies usage context: when you have a Fedlex ELI URI and need full details. It does not explicitly state when not to use or mention alternative tools, but the sibling ch_search_acts provides a natural alternative for search scenarios.

    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?

    Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false. The description adds valuable context by explaining the open-world semantics: an empty search result may reflect a connector gap rather than the law, and each gap includes a fallback. This reinforces and operationalizes the annotations without contradicting them.

    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 concise and well-structured: purpose first, usage trigger second, return value last. Every sentence earns its place, with no redundant filler. The critical warning about empty search results is front-loaded and easy to act on.

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

    Completeness5/5

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

    For a zero-parameter, read-only tool with rich annotations and an output schema, the description is fully sufficient. It explains what the tool covers, when to call it, why it matters, and what it returns. Nothing an agent needs to decide to invoke this tool correctly is missing.

    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 tool has zero parameters, so the schema is trivially complete. The baseline for zero-parameter tools is 4, and the description adds no parameter-specific information because none is needed. It appropriately focuses on behavior and return value instead.

    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 opens with a specific declarative statement of what the tool does: 'Declare what this connector covers, how it is sourced, and what it does NOT cover.' It also specifies the return type ('Coverage with families, an as-of note, and a non-empty list of known gaps'), making the tool's role distinct from the sibling ch_search_acts and ch_get_act 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 gives explicit usage triggers: 'Call this before telling a user that the law "does not contain" something, and whenever a search comes back empty.' It explains the rationale and even notes that gaps carry fallbacks. However, it does not name the sibling tools as alternatives or explicitly state when not to use it, so it stops short of a full 5.

    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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