An AI coding agent skill that transforms rough business requests, screenshots, or existing documents into highly structured, actionable product requirement artifacts.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install requirement-analysis-assistant
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install requirement-analysis-assistant using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Requirement Analysis Assistant?
The Requirement Analysis Assistant is a technical skill designed for Openclaw Skills environments to bridge the gap between abstract business ideas and structured technical execution. It enables AI agents to work as collaborative product analysis assistants, generating high-quality drafts, highlighting explicit assumptions, exposing missing inputs, and flagging implementation risks.
By acting as a supportive co-pilot for product managers, developers, and QA teams, this skill ensures that requirements for web campaigns, recharge hubs, SDK integrations, and admin modules are robust and clear. It handles everything from requirement review to active feature breakdown, keeping engineering teams aligned before a single line of production code is written.
Requirement Analysis Assistant Use Cases
- Drafting PRDs from Scratch: Turning a brief feature idea or rough bullet points into a fully structured, multi-section Product Requirement Document.
- Visual-to-Spec Engineering: Analyzing an uploaded user interface screenshot, sketch, or competitor mockup to break down visible modules and infer functional rules.
- Interactive Prototyping: Generating low-fidelity, self-contained HTML/CSS/JS demo pages to align stakeholders on interactions and UI states.
- PRD Audits & Quality Control: Reviewing an existing requirements document to group gaps and risks by severity before handoff to engineering.
- Scenario-Specific Planning: Structuring specialized workflows for platform-centric use cases like game-publishing operations, user acquisition pipelines, and back-office configuration panels.
How Requirement Analysis Assistant Works
- Input Identification: The skill detects the source material type, whether it is an image, an existing markdown file, or a loose conversational prompt.
- Context Extraction: It systematically extracts business goals, target user personas, entry channels, visual states, data tracking demands, and platform constraints.
- Scenario Classification: The agent maps the request to a specific functional category, such as an SDK integration, recharge center, or admin configuration.
- Reference Loading: Based on the context, it loads matching reference frameworks (e.g., standard templates, quality checklists, or visual prototyping guidelines).
- Artifact Generation: The assistant structures the final output into dedicated modules like edge cases, acceptance criteria, or wireframe field models.
- Self-Check Assessment: Before delivering results, it runs an automated validation pass to guarantee that visible facts are separated from assumptions and that high-risk unknowns are clearly exposed.
Requirement Analysis Assistant Setup
Integrate this skill into your agent workspace by installing the skill definition bundle and placing the essential structural templates into your reference directory.
# Create the references directory within your agent workspace
mkdir -p references/
# Populate standard validation reference files
touch references/prd-template.md \
references/publishing-scenarios.md \
references/visual-prototype.md \
references/quality-checklist.md
Configure your configuration framework to point to the skill file, enabling the agent to load the reference contexts when triggered by requirement analysis tasks.
Requirement Analysis Assistant Data Schema & Taxonomy
The skill standardizes unstructured inputs into organized taxonomies. Below is the file metadata and documentation schema used for visual and textual data organization:
| Output Category | Data Modules Included | Core Focus |
|---|---|---|
| Standard PRD Draft | Objectives, Scope, Functional Breakdown, Interaction Rules, Edge Cases, Acceptance Criteria | Comprehensive technical alignment |
| Visual Analysis | Visible Content Facts, Inferred Functional Rules, Open Questions | Separating visual evidence from assumptions |
| Prototype Outline | Page List, Component Hierarchy, State Matrix (Empty/Loading/Success/Error) | Interaction architecture and form schema |
| HTML Demo File | Self-contained HTML/CSS/JS layout, UI State Toggles, Placeholder labels | Rapid feedback loops and visual alignment |
Requirement Analysis Assistant Advanced Features
- Structured Reference Ingestion: Automatically pulls custom organizational templates, writing rules, or compliance policies dynamically if provided in the active workspace.
- Multi-State UI Blueprinting: Generates HTML wireframes pre-mapped to state-specific markers (e.g., ongoing, reserved, claimed, ended, loading, error).
- Risk Isolation Framework: Automatically isolates high-risk payment, identity verification, privacy, and SDK version rules under explicitly tagged "To Confirm" sections.
- Severity-Graded QA Handouts: Groups requirement review findings into structured severity blocks: "Must fix before review", "Should clarify before development", and "Optional improvements" to assist project managers with prioritization.
SKILL.md
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