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lexvibe

by io.github.marcosnovo

Generate legal documents

generate_policies
Read-only

Generate the legal documents (privacy policy, terms of service and, if applicable, an AI disclosure) localized and tailored to the target markets (GDPR, UK GDPR, CCPA…). Returns Markdown drafts. Pass check_website's or check_store's suggestedAnswers as answers so the documents disclose the right processing. Anonymous remote generation is template-based and capped at 3 locales; AI-tailored, hosted and auto-updated documents require a LexVibe account (https://golexvibe.com).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
entityNoData controller / legal entity responsible for the app.
answersNoCompliance flags; pass check_website's suggestedAnswers. Recognized keys: usesAnalytics, processesPayments, usesGenerativeAI, collectsEmails, sharesWithThirdParties, platformType.
appNameYesPublic / commercial name of the product.
localesNoDocument languages (max 3 for anonymous callers). Defaults to the languages suggested by the chosen markets.
marketsYesRegions where the app has users; determines the legal frameworks covered.
contactEmailNoContact email for privacy requests and data-subject rights.

TDQS

A4.7/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond the readOnlyHint and destructiveHint annotations, the description discloses the output format (Markdown drafts), the difference between anonymous template-based generation and AI-tailored hosted versions, the locale cap, and the account requirement. This significantly enriches understanding of the tool's behavior and limitations.

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 well-structured and front-loaded with the core purpose. It consists of four sentences, each providing essential information: what is generated, the output format, the integration with check tools, and the anonymous vs. account-based modalities. No redundant or filler content is present.

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?

Despite having no output schema, the description effectively conveys what the tool produces (Markdown drafts) and how the parameters influence the result (e.g., markets and locales). It covers the key operational details for a complex tool with nested objects and six parameters, making it complete enough for an agent to invoke 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 input schema already covers all parameters (100% coverage), so the baseline is 3. The description adds value by explicitly tying the `answers` parameter to check_website/check_store outputs and explaining that locales and markets determine legal frameworks and document languages. This goes beyond the schema's basic field descriptions.

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 function: generating legal documents (privacy policy, terms of service, AI disclosure) localized to target markets. It is specific about the resource and distinguishes it from sibling tools like check_website and check_store, which analyze rather than generate documents.

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 usage context, including how to pass suggestedAnswers from check_website or check_store to tailor documents. It also explains when the anonymous template-based generation applies (up to 3 locales) versus when a LexVibe account is needed. However, it does not explicitly state when not to use this tool or name alternative generation tools, so it stops short of a 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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TDQS

A4.5/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: check_ai_act classifies AI risk, check_store and check_website audit different platform listings, claim_app creates an app, generate_policies drafts legal docs, get_claim_status tracks claim confirmation, and get_install_snippet provides installation code. No two tools overlap in function.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern with snake_case (e.g., check_ai_act, claim_app, generate_policies). The naming is predictable and easy to understand.

Tool Count5/5

Seven tools is a well-scoped set for the server's purpose: three for compliance checks, one for app creation, one for policy generation, one for status tracking, and one for installation snippets. Each tool earns its place without being excessive.

Completeness4/5

The tool surface covers the primary workflows: checking compliance, creating an app, generating policies, and installation. A minor gap is the lack of update/delete tools for apps, but the core lifecycle is covered. Agents can successfully complete the intended tasks.

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