MEOK Fria Generator MCP
Server Quality Checklist
Latest release: v1.0.3
- Disambiguation5/5
Each tool has a clear, distinct purpose: checking FRIA requirement, generating template, listing charter articles, listing triggers, mapping to DPIA, pricing, and signing attestation. There is no overlap or ambiguity.
Naming Consistency4/5Most tools follow a verb_noun pattern (generate_fria_template, list_charter_articles, etc.), but 'pricing' and 'signed_fria_attestation' are nouns, deviating from the pattern. Overall, the naming is clear and predictable despite these minor inconsistencies.
Tool Count5/5Seven tools is ideal for this specialized domain. Each tool provides a distinct function without unnecessary redundancy, and the count is neither too few nor too many for the scope of FRIA generation and associated compliance tasks.
Completeness4/5The tool set covers the core FRIA workflow: determination, template generation, supporting information (charter articles, triggers), DPIA integration, pricing, and attestation. A minor gap is lack of tools for managing previously generated templates or attestations, but this aligns with the generator-focused design.
Average 3.6/5 across 7 of 7 tools scored. Lowest: 2.5/5.
See the Tool Scores section below for per-tool breakdowns.
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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 present, so the description must carry the full burden. It implies a read operation but does not disclose if the tool is idempotent, requires authentication, or has side effects. The single sentence fails to provide behavioral context beyond a vague topic.
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, short sentence that is front-loaded and contains no extraneous words. It is appropriately concise for a tool with no parameters.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with no parameters and an output schema, the description is somewhat incomplete. It hints at pricing but does not describe the output format or content. While it meets minimum viability, it could better indicate what the agent can expect.
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 0 parameters, so schema coverage is 100%. According to guidelines, baseline is 4 for zero parameters. The description adds minimal context by specifying the domain (pricing for MEOK FRIA Generator), which is acceptable given no parameters to explain.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5Does the description clearly state what the tool does and how it differs from similar tools?
Description 'Pricing for MEOK FRIA Generator' is a noun phrase lacking a verb and does not specify the action (e.g., get, calculate). It vaguely indicates the tool provides pricing information but does not differentiate itself from sibling tools like 'generate_fria_template' or 'is_fria_required'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5Does 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. There is no mention of context, prerequisites, or exclusions, leaving the agent with no decision support.
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 exist, so the description bears full responsibility. It omits crucial behavioral details: that it calls an external API (meok-attestation-api), potential side effects, rate limits, or authentication requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise: a one-line purpose, then args and returns listed. It is front-loaded and every sentence is useful. Minor improvement could be better formatting or grouping.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description mentions the external API and returns, but given the output schema exists, it is adequate. However, more context on the signing process, expected inputs, or error handling would improve completeness.
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?
Schema description coverage is 0%, but the description compensates with brief one-line explanations for each parameter (e.g., 'Legal name of the deployer'). This adds meaning beyond the schema titles and types. More detail on formats or allowed values would be better.
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 tool produces an HMAC-signed FRIA attestation via a specific API, with a clear verb and resource. It distinguishes from siblings like generate_fria_template which likely creates templates.
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?
The description does not provide explicit guidance on when to use this tool versus alternatives like generate_fria_template or is_fria_required. No when-not-to-use or prerequisite information is given.
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 states the tool generates a template with guidance, but does not disclose whether it is read-only, requires authentication, or has any side effects. The description is vague on behavior beyond generation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear purpose statement, followed by Args and Returns sections. It is appropriately sized but could be slightly more concise by removing the example in Args (e.g., 'e.g., "Acme Hiring Ltd"') which adds bulk.
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?
Given the tool has 5 parameters, 3 required, and an output schema (not shown but exists), the description is fairly complete. It explains the template's purpose (7 mandatory fields) and target audience (compliance team). However, it omits mention of the output schema's structure or any error handling.
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 input schema has 0% description coverage, but the description's Args section adds meaningful explanations for each parameter (e.g., `deployer_name: Legal name of the deployer`). This compensates for the schema gap, though details on defaults and constraints (e.g., `expected_users` default of 1000) are missing.
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 'Generate a FRIA template structure with all 7 mandatory Article 27 fields populated as guidance.' This clearly identifies the tool's purpose, distinguishes it from siblings like `is_fria_required` (which checks necessity) and `signed_fria_attestation` (which handles signing), and specifies the resource and action.
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?
The description does not provide explicit guidance on when to use this tool versus alternatives such as `is_fria_required` or `map_to_edpb_dpia`. It only implies a use case ('ready for completion by the deployer's compliance team') without discussing exclusions or prerequisites.
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?
No annotations are provided, so the description carries full burden. It mentions mapping and returning a crosswalk but does not disclose whether the operation is read-only, has side effects, or requires specific permissions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, consisting of two sentences plus structured Args/Returns. The first sentence immediately states the purpose, though it could be slightly more structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With an output schema present and one parameter, the description is mostly complete for the core functionality. However, it lacks usage guidelines and behavioral transparency, which are gaps given no annotations.
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?
The parameter 'annex_iii_category' has 0% schema description coverage. The tool description adds minimal context ('Annex III category for context'), but does not specify valid values, format, or examples, leaving the agent to guess.
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 tool maps FRIA fields to EDPB DPIA template sections to avoid double work. This is specific and distinct from sibling tools like generate_fria_template or is_fria_required.
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 implies usage after having FRIA fields but does not explicitly state when to use this tool versus alternatives. No guidance on prerequisites or when not to use is provided.
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 must carry the full burden of disclosure. It only states that the tool lists articles relevant to AI deployer FRIA, but does not disclose that the operation is read-only, whether it requires authentication, or any side effects. Minimal 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that directly states the tool's purpose with no wasted words. It is front-loaded and easy to parse.
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?
Given the tool has no parameters and a likely straightforward output (with an output schema present), the description is adequate. However, it could be improved by mentioning that the list covers all relevant articles without requiring input or by noting any dynamic vs static nature.
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?
There are no parameters (0 params, schema coverage 100%), so the baseline is 4. The description adds value by specifying the scope ('relevant to AI deployer FRIA'), which clarifies what articles are returned beyond an empty 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 uses the specific verb 'List' and resource 'EU Charter of Fundamental Rights articles', and clearly limits the scope to those 'relevant to AI deployer FRIA'. This distinctively separates it from sibling tools like list_mandatory_triggers or map_to_edpb_dpia.
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 implies the tool is used during FRIA to retrieve relevant charter articles, but provides no explicit guidance on when to use it versus alternatives (e.g., list_mandatory_triggers). No when-not-to-use or prerequisite information is given.
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 responsibility for behavioral disclosure. It only states the tool lists conditions, but does not mention any constraints like read-only nature (assumed), data freshness, or lack of side effects. The description is minimal and lacks transparency beyond the basic function.
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 11-word sentence, entirely front-loaded with the key information. Every word is meaningful and there is no redundancy.
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 simplicity of the tool (no parameters, output schema exists), the description fully captures its purpose. The existence of an output schema means return values are documented separately. No additional context is needed for an agent to understand and invoke this tool correctly.
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 no parameters, so schema coverage is trivially 100%. Following the rubric, 0 parameters warrants a baseline of 4. The description adds no parameter info because there are none, so this score reflects that no additional detail is needed.
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 tool lists conditions making a FRIA mandatory under Article 27(1). It uses a specific verb and resource, and distinguishes itself from sibling tools like 'is_fria_required' (which checks a specific case) and 'generate_fria_template' (which creates a document).
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?
No explicit guidance on when to use this tool vs alternatives is provided. However, the context of sibling tools suggests it is for obtaining a reference list. The purpose is clear enough that usage is implied, but no exclusion or alternative recommendations are given.
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 the full burden. It transparently states the return value: 'Decision + rationale + Article 27 reference.' No side effects or destructive behavior are implied, which is appropriate for a determination tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with 'Args' and 'Returns' sections. It is concise but provides necessary detail. Minor improvement could be more brevity in the parameter descriptions.
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 tool's simplicity and presence of an output schema, the description covers all required aspects: purpose, parameter meanings, and return value. It is complete and leaves no gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must explain all parameters. It does so thoroughly: organisation_type lists options, is_public_law_body and provides_public_service are explained, and annex_iii_categories gives examples. This adds significant value.
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 tool's purpose: 'Determine if a FRIA is mandatory under EU AI Act Article 27 for this deployment.' This specific verb+resource combination distinguishes it from sibling tools like generate_fria_template.
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 provides clear context for when to use the tool: to check the mandatory requirement for a FRIA. It does not explicitly state when not to use it or mention alternatives, but the use case is well-defined.
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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