dk-eli-mcp
Server Quality Checklist
Latest release: v0.3.3
- Disambiguation5/5
Each tool has a clearly distinct purpose: metadata retrieval, full-text retrieval, coverage declaration, and change listing. No two tools overlap in what they return, making misselection unlikely.
Naming Consistency4/5All tools share the dk_ prefix, and most follow a verb_noun pattern (dk_get_act, dk_get_text). dk_coverage and dk_recent_changes deviate slightly by using nouns rather than verbs, but the pattern remains readable and predictable.
Tool Count4/5With four tools, the set is compact but sufficient for its narrow scope. It could benefit from a search tool, but the count is reasonable and each tool earns its place.
Completeness4/5The core needs are covered: fetch metadata, fetch full text, list recent changes, and explicitly declare coverage gaps. Minor gaps exist—such as no search-by-keyword or version-history tool—but the dk_coverage tool mitigates uncertainty and provides fallbacks.
Average 4.1/5 across 4 of 4 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 16 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
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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 indicate read-only, idempotent, non-destructive behavior. The description adds format detail (LexDania XML) but no additional behavioral traits like permissions or error handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence of 12 words, highly concise with no wasted words. Perfectly front-loaded with key information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple fetch tool with optional parameters and an output schema, the description covers the essential aspects (what it returns, origin). Could mention that it returns XML or document retrieval, but sufficient given the output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the input schema already provides sufficient descriptions for all three parameters (year, number, accession). The description adds no new semantic meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Fetch'), resource ('full LexDania XML of a Danish document'), and quality ('verbatim official text'), making it highly specific and distinguishable from siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus the siblings (dk_get_act, dk_recent_changes). No explicit conditions or alternatives mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so the safety profile is clear. The description adds that it fetches 'metadata', implying no side effects. However, it does not disclose potential missing data behavior or authentication requirements. Given annotation coverage, a 3 is appropriate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence with no extraneous information. It efficiently communicates the core purpose and method.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With a complete schema (100% coverage), annotations, output schema presence, and only three siblings, the description covers the tool's purpose and usage adequately. The output schema will explain return values, so no further description is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with each parameter having a description. The description adds overall context (by ELI coordinate or accession) but does not provide additional parameter-specific details beyond the schema. Baseline 3 is correct.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Fetch'), the resource ('Danish act / order metadata'), and the query method ('by ELI coordinate or accession'). It distinguishes from siblings: dk_get_text fetches full text, dk_recent_changes fetches changes, so this tool is specifically for metadata lookup.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains when to use the tool (to get metadata given an ELI coordinate or accession) but does not explicitly mention when not to use it or suggest alternatives (e.g., when full text is needed, use dk_get_text). The guidance is clear but incomplete.
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 true, and destructiveHint false. The description adds that the harvest API is available 03:00-23:45 Danish time and that an empty list is a valid response, which is useful beyond annotations. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that efficiently communicates the tool's purpose and source. No unnecessary words, front-loaded with the key action and resource.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema, high schema coverage, and detailed annotations, the description is complete enough. The purpose, parameter constraints, and behavioral traits are all covered.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the date parameter already having a detailed description including format, example, and availability caveats. The tool description adds minimal extra value ('harvest API' is already in the schema). Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('List'), resource ('Danish documents'), condition ('changed on a given date'), and source ('harvest API'). This distinguishes it from sibling tools like dk_get_act and dk_get_text, which likely retrieve specific documents rather than lists of changes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for listing changes on a specific date, but does not explicitly state when to use it or when to prefer siblings. The context is clear given sibling names, but no exclusion criteria are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations (readOnlyHint, openWorldHint, idempotentHint), the description adds important behavioral context: absence might be a connector gap rather than a gap in the law, and every known gap includes a fallback for where to look instead. This meaningfully informs the agent's interpretation of empty results.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and well-structured: it states the core purpose first, follows with concrete invocation conditions, and closes with the return type. Every sentence earns its place without repetition or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter metadata tool, the description fully covers what the tool does, when to use it, and what it returns. The output schema handles the detailed return structure, and the annotations cover safety and idempotence, so nothing essential is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters and the schema is an empty object with 100% coverage, so there is nothing for the description to add about parameters. The baseline of 4 applies because parameter semantics are not applicable.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource: it declares what the connector covers, how it is sourced, and what it does NOT cover. This clearly distinguishes it from sibling tools like dk_get_act and dk_get_text, which retrieve specific content rather than coverage metadata.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives explicit when-to-use guidance: call it before telling a user the law 'does not contain' something, and whenever a search returns empty. It does not explicitly name excluded scenarios or alternatives, but the conditions are clear and actionable.
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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