requirement-analyzer

Parses natural language requirements into structured product requirement models covering pages, entities, APIs, and AI capabilities.

Updated Jun 5, 2026
One-click install
npx skills add https://github.com/fen-zx/NovelToScript --skill requirement-analyzer-fen-zx
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: requirement-analyzer
Source: https://github.com/fen-zx/NovelToScript/tree/main/.agents/skills/requirement-analyzer
Command: npx skills add https://github.com/fen-zx/NovelToScript --skill requirement-analyzer-fen-zx

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Turning unstructured ideas, PRDs, or user stories into a complete, consistent requirement model is slow and error-prone. This Skill converts free-form requirement text into a structured specification covering pages, modules, features, entities, business rules, permissions, API needs, AI capabilities, and async tasks, serving as the entry point of an AI-driven development workflow. ## Core Features & Use Cases - Full Requirement Modeling: Generates 15 structured sections including page models, module models, entity relationships, business rules, permission models, and risk analysis. - API and AI Capability Derivation: Infers requirement-level REST endpoints, AI capabilities, and asynchronous job definitions directly from the requirement text. - Risk and Question Discovery: Automatically produces a risk analysis with mitigation suggestions and a mandatory open-questions list, marking unknowns as [待确认] instead of fabricating details. - Use Case: Paste a paragraph like "users upload novels and AI generates scripts asynchronously with export to PDF" and receive a complete requirement model with entities (User, Script, Version), API endpoints, a GenerateScriptJob async task, and clarifying questions. ## Quick Start Ask the AI to analyze your requirement text or PRD with the requirement-analyzer skill, for example by pasting a user story and requesting a full structured requirement model in Markdown or JSON.

Frequently Asked Questions about requirement-analyzer

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I convert a user story into a structured requirement model?▼

Provide the user story or PRD text as input, either as plain natural language or as JSON with a raw_requirement field. The skill outputs a Markdown or JSON model covering pages, modules, features, entities, rules, permissions, APIs, AI capabilities, and async tasks.

What does a requirement analysis output include for API design?▼

The output includes a requirement-level API section listing endpoints such as POST /scripts or GET /scripts/:id derived from the described features. It intentionally does not design request parameters, keeping the output at the requirements stage.

Can requirement analysis identify async tasks and AI capabilities?▼

Yes. The skill detects long-running operations and defines them as async jobs with input, output, and states like Pending, Processing, Completed, and Failed. It also identifies AI capabilities with their input and output types, such as novel parsing or script generation.

What input formats does the requirement analyzer accept?▼

It accepts natural language text describing the requirement, or a JSON object containing a raw_requirement string. Output defaults to Markdown but can be returned as structured JSON when requested.

What happens when requirement details are missing or ambiguous?▼

Unknown content is marked as [待确认] (to be confirmed) rather than invented, and a mandatory question list is generated to surface ambiguities such as collaboration support, export formats, or retry policies.