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MEOK Fria Generator MCP

meok-fria-generator-mcp MCP 服务器 MCP 注册表 PyPI

meok-fria-generator-mcp MCP 服务器

meok-fria-generator-mcp

PyPI 许可证: MIT MCP

欧盟《人工智能法案》第 27 条基本权利影响评估 (FRIA) 生成器。包含 EDPB DPIA 交叉参考、欧盟基本权利宪章映射以及 HMAC 签名的合规性证明。

MEOK AI Labs 开发 · MIT 许可 · 可作为 MCP 服务器 在 Claude Code、Cursor、Cline、Windsurf 等工具中运行。


存在意义

欧盟《人工智能法案》条例 (EU) 2024/1689 第 27 条规定,提供公共服务的公法机构和私营运营商必须在部署高风险 AI 系统之前完成基本权利影响评估 (FRIA)。

欧盟人工智能办公室的官方 FRIA 模板尚未发布(截至 2026 年 4 月)。现有的免费工具(ALIGNER、AIActStack、kla.digital)仅为模板生成器——它们均不支持 MCP 调用,也不提供已签名的证明。

该 MCP 为合规团队提供了一个结构化、可调用且已签名的 FRIA 工作流,并对照 EDPB 统一的 DPIA 模板(2026 年 4 月 14 日)进行了映射,从而使同一套证据包能够同时满足《人工智能法案》和 GDPR 审计的要求。

Related MCP server: Encoder AI MCP

工具

工具

用途

is_fria_required

判断特定部署是否根据第 27(1) 条强制要求进行 FRIA

generate_fria_template

生成包含所有 7 个强制性第 27 条字段的结构化 FRIA 模板

map_to_edpb_dpia

交叉参考 FRIA 字段与 EDPB DPIA 部分以共享证据

signed_fria_attestation

通过 meok-attestation-api 对已完成的 FRIA 进行 HMAC 签名

list_charter_articles

与 AI 部署者 FRIA 相关的《欧盟基本权利宪章》条款

list_mandatory_triggers

触发第 27(1) 条 FRIA 义务的条件

pricing

定价层级(免费 / 79 英镑专业版 / 1,499 英镑企业版 / 5,000 英镑起定制版)

安装

pip install meok-fria-generator-mcp

然后在你的 Claude Code / Cursor MCP 配置中:

{
  "mcpServers": {
    "meok-fria-generator": {
      "command": "python",
      "args": ["-m", "meok_fria_generator"]
    }
  }
}

使用示例

“如果我们是一家在欧盟市场部署简历筛选 AI 的英国公共部门招聘服务提供商,是否强制要求进行 FRIA?附件 III 类别:就业与劳动力。”

Claude 调用 is_fria_required(...) 并返回结构化的决策:是,强制要求,因为 (a) 提供公共服务 且 (b) 属于附件 III 高风险类别。返回理由、监管依据以及截止日期(首次部署前)。

“为 Acme Public Services Ltd 的简历筛选 AI 生成 FRIA 模板。预计每年 50,000 名候选人,在德国、法国、爱尔兰部署。”

Claude 返回一个结构化模板,包含所有 7 个第 27 条字段、《欧盟基本权利宪章》条款引用、EDPB DPIA 交叉参考以及审查触发时间表。

第 27 条强制触发条件

在以下情况下,FRIA 是强制性的:

  1. 部署者是公法机构(成员国或欧盟机构)

  2. 部署者是提供公共服务的私营运营商(公共部门招聘、教育、医疗保健等)

  3. 部署的是高风险附件 III 系统

  4. 始终强制的类别(无论组织类型如何):

    • 信用评分(附件 III §5(b))

    • 人寿/健康保险定价(附件 III §5(c))

合规立场

  • 欧盟《人工智能法案》条例 (EU) 2024/1689 第 27 条(FRIA — 公共部门 + 附件 III 部署者强制要求)

  • 《欧盟基本权利宪章》(交叉引用以进行风险识别)

  • EDPB 统一 DPIA 模板(2026 年 4 月 14 日 — 用于 GDPR 第 35 条重叠部分)

  • 第 14 条(纳入 FRIA (e) 部分的人工监督要求)

定价

  • 免费 — 全套工具,公共证明 API

  • 79 英镑/月 专业版 — 你自己的 HMAC 签名密钥 + 自定义验证域名 + FRIA 版本控制

  • 1,499 英镑/月 企业版 — 多部署 FRIA 管理 + SLA + 经销商白标

  • 5,000 英镑起 定制版 — 自托管证明 + GRC 集成 + 现场研讨会

购买:https://meok.ai/pricing · 联系:nicholas@csoai.org

许可证

MIT。© 2026 Nicholas Templeman / CSOAI LTD (英国公司注册处 16939677)。

另请参阅

Available Tools

7 tools
generate_fria_templateA

Generate a FRIA template structure with all 7 mandatory Article 27 fields populated as guidance.

Args: deployer_name: Legal name of the deployer (e.g., "Acme Hiring Ltd"). ai_system_name: Name of the AI system being deployed. annex_iii_category: Annex III category (e.g., "employment-and-workforce"). expected_users: Estimated count of natural persons whose data will be processed. geographic_scope: List of country codes (e.g., ["DE", "FR", "IE"]).

Returns: Structured FRIA template ready for completion by the deployer's compliance team.

ParametersJSON Schema
NameRequiredDescriptionDefault
deployer_nameYes
ai_system_nameYes
annex_iii_categoryYes
expected_usersNo
geographic_scopeNo

Output Schema

ParametersJSON Schema
NameRequiredDescription

No output parameters

TDQS

A3.5/5.0
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.

Conciseness4/5

Is 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.

Completeness4/5

Given 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.

Parameters4/5

Does 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.

Purpose5/5

Does 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 Guidelines2/5

Does 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.

is_fria_requiredA

Determine if a FRIA is mandatory under EU AI Act Article 27 for this deployment.

Args: organisation_type: One of public-authority / private-operator / SaaS-vendor / individual. is_public_law_body: True if the organisation is a body governed by Member State or EU public law. provides_public_service: True if the organisation provides services in a public-service context (recruitment for public sector, education, healthcare, social services, etc.). annex_iii_categories: List of Annex III high-risk categories the system falls under. E.g., ["employment-and-workforce", "education-and-vocational-training", "credit-scoring"].

Returns: Decision + rationale + Article 27 reference.

ParametersJSON Schema
NameRequiredDescriptionDefault
organisation_typeYes
is_public_law_bodyNo
provides_public_serviceNo
annex_iii_categoriesNo

Output Schema

ParametersJSON Schema
NameRequiredDescription

No output parameters

TDQS

A4.5/5.0
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.

Conciseness4/5

Is 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.

Completeness5/5

Given 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.

Parameters5/5

Does 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.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: '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 Guidelines4/5

Does 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.

list_charter_articlesA

List EU Charter of Fundamental Rights articles relevant to AI deployer FRIA.

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

Output Schema

ParametersJSON Schema
NameRequiredDescription

No output parameters

TDQS

A3.8/5.0
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.

Conciseness5/5

Is 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.

Completeness4/5

Given 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.

Parameters4/5

Does 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.

Purpose5/5

Does 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 Guidelines3/5

Does 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.

list_mandatory_triggersA

List the conditions that make a FRIA mandatory under Article 27(1).

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

Output Schema

ParametersJSON Schema
NameRequiredDescription

No output parameters

TDQS

A3.9/5.0
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.

Conciseness5/5

Is 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.

Completeness5/5

Given 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.

Parameters4/5

Does 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.

Purpose5/5

Does 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 Guidelines3/5

Does 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.

map_to_edpb_dpiaA

Map FRIA fields to EDPB harmonised DPIA template (14 April 2026) sections to avoid double work.

Args: annex_iii_category: Annex III category for context.

Returns: Crosswalk showing which FRIA fields satisfy which DPIA sections.

ParametersJSON Schema
NameRequiredDescriptionDefault
annex_iii_categoryYes

Output Schema

ParametersJSON Schema
NameRequiredDescription

No output parameters

TDQS

A3.6/5.0
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.

Conciseness4/5

Is 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.

Completeness3/5

Given 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.

Parameters3/5

Does 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.

Purpose5/5

Does 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 Guidelines3/5

Does 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.

pricingC

Pricing for MEOK FRIA Generator.

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

Output Schema

ParametersJSON Schema
NameRequiredDescription

No output parameters

TDQS

C2.5/5.0
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.

Conciseness5/5

Is 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.

Completeness3/5

Given 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.

Parameters4/5

Does 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.

Purpose2/5

Does 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 Guidelines1/5

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. 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.

signed_fria_attestationB

Produce an HMAC-signed FRIA attestation via the public meok-attestation-api.

Args: deployer_name: Legal name of the deployer. ai_system_name: Name of the AI system. annex_iii_category: Annex III category. completed_sections: List of FRIA section IDs that have been completed (e.g., ["a_deployer_processes", "b_period_frequency_use"]). sign_off_role: Role of the signer.

Returns: Signed attestation with verification URL.

ParametersJSON Schema
NameRequiredDescriptionDefault
deployer_nameYes
ai_system_nameYes
annex_iii_categoryYes
completed_sectionsYes
sign_off_roleNocompliance-lead

Output Schema

ParametersJSON Schema
NameRequiredDescription

No output parameters

TDQS

B3.4/5.0
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.

Conciseness4/5

Is 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.

Completeness3/5

Given 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.

Parameters4/5

Does 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.

Purpose5/5

Does 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 Guidelines2/5

Does 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.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. 7 tool updatesv1.0.3
    • First observedgenerate_fria_template
    • First observedis_fria_required
    • First observedlist_charter_articles
    • First observedlist_mandatory_triggers
    • First observedmap_to_edpb_dpia
    • First observedpricing
    • First observedsigned_fria_attestation

TDQS

A3.6/5.0
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 Consistency4/5

Most 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 Count5/5

Seven 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.

Completeness4/5

The 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.

Maintenance

ActivityInactive
ResponsivenessNo issues

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