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open-claw

Run structured deep-dive research and package validated implementations with architecture diagrams.

Updated Jul 5, 2025
Search Tags:#documentation#validation#implementation#web search#architecture diagrams#deep research#demo repo
One-click install
npx skills add https://github.com/nsuberi/ai-prototype-hub --skill open-claw
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: open-claw
Source: https://github.com/nsuberi/ai-prototype-hub/tree/main/apps/research-workspace/vault-seed/.claude/skills/open-claw
Command: npx skills add https://github.com/nsuberi/ai-prototype-hub --skill open-claw

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It solves the problem of vague or incomplete answers by guiding an AI to perform structured deep-dive research, validate the approach, implement working code, and produce architecture documentation in one cohesive workflow.

Core Features & Use Cases

  • Research-to-implementation loop: Runs a multi-phase process from findings to validated execution and final deliverables.
  • Working demo packaging: Produces a standalone repo artifact with a README and a runnable package configuration.
  • Architecture documentation: Generates Mermaid-based system diagrams that explain how the solution is put together.

Use Case Example: You ask for a deep dive on “how to implement a retrieval-augmented generation pipeline with embeddings and evaluation,” and the skill outputs researched findings, a validation report, an implementation with tests, architecture diagrams, and a packaged demo repo.

Quick Start

Ask the AI: "OpenClaw, deep dive on {{TOPIC}} and produce a standalone demo repo with research, validation, implementation, architecture diagrams, and packaging."

Frequently Asked Questions about open-claw

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

FAQPage Schema
How do I package AI research findings into a standalone demo repo with architecture diagrams?▼

To package deep-dive research into a standalone demo repo, you need a structured workflow that outputs research findings, validation reports, implementation code, Mermaid architecture diagrams, and a packaged directory driven by a YAML state file.

What is the best way to validate implementation patterns before writing code for a complex technology deep dive?▼

Validating implementation patterns during a technology deep dive requires a multi-phase process that researches findings, tests the approach, and generates a validation report before moving to actual code execution and architecture documentation.

How do I generate Mermaid architecture diagrams from researched technology approaches?▼

Generating Mermaid architecture diagrams from researched approaches involves running a structured research-to-implementation loop that processes findings, validates the execution path, and automatically outputs system diagrams explaining the solution structure.

Can I turn complex technology questions into working code and documentation in one workflow?▼

You can turn complex technology questions into working code and documentation by applying a phased workflow that handles research, validation, implementation, architecture generation, and final packaging into an output directory.

Does deep research packaging require a YAML state file to manage the output directory?▼

Deep research packaging requires a YAML state file to drive the final output directory, ensuring the standalone repo artifact correctly organizes the README, runnable package configuration, and generated architecture documentation.

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