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marcosnovo

@lexvibe/mcp

by marcosnovo
OverviewSchemaRelated ServersScoreDiscussions
JavaScript
Hybrid

generate_policies

Read-only

Generate localized legal documents including privacy policy, terms of service, and AI disclosure, tailored to target markets' frameworks like GDPR and CCPA. Returns Markdown documents.

Instructions

Generate the legal documents (privacy policy, terms of service and, if applicable, an AI disclosure) localized and tailored to the target markets' frameworks (GDPR, UK GDPR, CCPA/CPRA, PIPEDA, LGPD…). Returns {documents: [{docType, locale, content, source}]} where content is Markdown and source is 'ai' or 'template' (template ⇒ not yet personalized — tell the user). Documents are returned only, never written to disk (make_compliant writes them to /legal) and nothing is persisted server-side. Run scan_project first and pass its suggestedAnswers as answers so the documents disclose the right processing; requires network access to the LexVibe API.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
entityNoData controller / legal entity (person or company legally responsible), e.g. 'Acme Labs S.L.'. If omitted, the documents keep a [to complete] placeholder.
answersNoCompliance flags; pass scan_project's suggestedAnswers. Recognized keys: usesAnalytics, processesPayments, usesGenerativeAI, collectsEmails, sharesWithThirdParties, platformType.
appNameYesApp / business name shown in the documents, e.g. 'Acme Notes'.
localesNoLanguages to generate the documents in (ISO 639-1). Defaults to the markets' main languages; anonymous calls are capped at 3 locales. Pass scan_project's `locales` to match the languages the app actually ships.
marketsYesRegions where the app has users (at least one). Each market pack cites its own frameworks: eu → GDPR/ePrivacy, uk → UK GDPR/PECR, us → CCPA/CPRA, ca → PIPEDA, latam → LGPD…; 'global' is NOT a union of the others — it only cites generic OECD international privacy best practices, for users outside every listed market. To cover several specific frameworks, list each market explicitly, e.g. ['eu', 'us', 'latam'].
contactEmailNoPrivacy contact email published in the documents. If omitted, a [to complete] placeholder is left.

Tool Definition Quality

A5/5.0
Behavior5/5

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

Annotations already mark readOnlyHint=true and destructiveHint=false. The description adds key details: documents are returned only, never persisted server-side, and template source means not yet personalized. No contradiction with annotations.

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 focused paragraph front-loaded with purpose. Every sentence adds value: purpose, prerequisite, behavior, return format, and distinction from sibling. No wasted words.

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 has 6 parameters, nested objects, and no output schema, the description covers all critical aspects: return structure (documents array with fields), special values (template source), prerequisite (scan_project), and network requirement. It compensates fully for the missing output schema.

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 100%, each parameter has a description. The description adds contextual meaning: explains relationship between 'answers' and 'scan_project', clarifies 'global' market is not a union, and describes the return format. This adds significant value beyond the 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 clearly states the tool generates legal documents (privacy policy, terms of service, AI disclosure) with localization and market-specific frameworks. It distinguishes from siblings like 'make_compliant' and 'scan_project', providing a specific verb and resource.

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

Usage Guidelines5/5

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

The description explicitly says to 'Run scan_project first and pass its suggestedAnswers as `answers`', indicates the tool requires network access to an API, and clarifies that persistence is handled by another tool ('make_compliant'). This provides clear when-to-use and when-not-to-use guidance.

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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