Lumis

plan_system_validation

Generate a computer system validation (CSV/CSA) plan for life sciences systems, including applicable regulations, GAMP classification, deliverables, effort estimates, and gap assessment areas.

Instructions

Plan a computer system validation (CSV/CSA) for a life sciences system.

Returns applicable regulations, methodology recommendation, GAMP classification, deliverables list, effort estimate, gap assessment areas, and decision tree guidance.

This tool supports planning for 21 CFR Part 11, EU Annex 11, GAMP 5, and related regulatory requirements across CRM, clinical, safety, and manufacturing systems.

Args: system_name: Name of the system being validated (e.g. 'Salesforce CRM', 'Veeva Vault', 'SAP QM') system_type: Type of system — 'saas', 'cots', 'configured', 'custom', 'hybrid' platform: Platform vendor if applicable (e.g. 'Salesforce', 'Veeva', 'SAP', 'Oracle') regulatory_geography: Jurisdiction — 'US', 'EU', 'Japan', 'Global', 'WHO' (default 'US') gxp_context: GxP context — 'GMP', 'GCP', 'GLP', 'GPvP', 'GDP', or comma-separated combo modules_in_use: Comma-separated modules (e.g. 'Sample Management, Events, Consent') has_mobile: Whether mobile/offline is in scope (adds validation complexity) has_integrations: Whether system integrations are in scope has_custom_code: Whether custom code (e.g. Apex, custom middleware) exists user_count: Approximate number of users country_count: Number of countries in scope

Input Schema

Name	Required	Default
`platform`	No
`has_mobile`	No
`user_count`	No
`gxp_context`	No
`system_name`	Yes
`system_type`	Yes
`country_count`	No
`modules_in_use`	No
`has_custom_code`	No
`has_integrations`	No
`regulatory_geography`	No	US

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.1Oct 25, 2026

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 must carry the behavioral burden. It discloses that the tool returns regulations, methodology, GAMP classification, deliverables, effort estimate, gap areas, and decision tree guidance, but it does not state whether the operation is read-only, whether it has side effects, or what permissions are required.

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 front-loaded with purpose and return values, followed by regulatory scope and a structured Args section. It is appropriately sized for an 11-parameter tool, though the regulatory-scope sentence is somewhat redundant after the purpose statement.

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's complexity, the description covers purpose, return categories, regulatory domains, and all parameter semantics. It is largely complete for invocation, but it could better address sibling-tool relationships and the read-only nature of a planning operation.

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%, so the description must compensate for all 11 parameters. It lists each argument with useful examples and allowed values, such as system_type values ('saas', 'cots', 'configured', 'custom', 'hybrid') and gxp_context values. Minor gaps remain, such as not restating defaults for booleans or explaining how user_count affects the output.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

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

The description clearly states a specific verb and resource: planning a computer system validation (CSV/CSA) for a life sciences system. It specifies the regulatory context and system domains, but it does not explicitly distinguish itself from sibling tools such as run_validation or traverse_decision_tree.

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?

Usage is implied by the verb 'Plan' and the statement that the tool supports planning for 21 CFR Part 11, EU Annex 11, GAMP 5, and related requirements. However, the description gives no explicit when-to-use guidance, exclusions, or alternatives versus siblings like run_validation.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server