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AINative-Studio

AINative PRD Generator MCP Server

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prd_validate

Validate PRDs against quality rules and AINative architectural constraints to check required sections, completeness, and compliance.

Instructions

Validate a PRD against quality rules and AINative architectural constraints. Checks for required sections, content completeness, AINative service references, and architecture compliance.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
prd_idNoID of a saved PRD to validate
strictNoStrict mode: also check AINative-specific rules (default: true)
contentNoPRD content in Markdown (provide directly or use prd_id)
Behavior2/5

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

With no annotations, the description carries full burden. It fails to clarify whether the tool is read-only, requires permissions, or reports results. The behavioral scope (checks performed) is stated, but side effects, idempotency, or response characteristics are omitted.

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?

Single, front-loaded sentence that efficiently communicates the purpose and key checks. Every part adds value, with no redundant or filler content.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Missing output schema and no description of return format (e.g., pass/fail, issue list). Does not clarify that either prd_id or content must be provided. For a validation tool, these gaps reduce completeness.

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?

Schema covers all parameters with descriptions (100% coverage). The tool's description adds high-level context about validation areas but does not enhance parameter understanding beyond what the schema provides. Baseline 3 is appropriate.

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?

Description clearly states the tool validates a PRD against quality rules and AINative constraints, listing specific checks (sections, completeness, service references, architecture). This verb+resource combination is distinct from siblings like prd_score or prd_check_api_refs, which have different focuses.

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?

No explicit guidance on when to use this tool versus alternatives (e.g., prd_score, prd_check_api_refs). The description does not mention prerequisites, conditions for use, or when not to use it, leaving the agent without decision support.

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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