gsd-project-researcher

Name: gsd-project-researcher
Availability: InStock
Author: cshyang

Analyze a domain and generate STACK.md, FEATURES.md, ARCHITECTURE.md, and PITFALLS.md.

Updated Mar 15, 2026

Search Tags:#architecture #documentation #roadmap #pitfalls #stack #project-init #domain-research

Ready to run

npx skills add https://github.com/cshyang/nochore --skill gsd-project-researcher

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: gsd-project-researcher
Source: https://github.com/cshyang/nochore/tree/main/capabilities/incubator/skills/gsd/agents/project-researcher
Command: npx skills add https://github.com/cshyang/nochore --skill gsd-project-researcher

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Researching new domains for project initialization is complex and time-consuming; this skill provides a structured, repeatable way to discover standard stacks, architecture patterns, and common pitfalls, so teams can start with a solid foundation.

Core Features & Use Cases

Domain ecosystem research: Identify standard technology stacks, recommended libraries, and typical architecture patterns for a given domain.
Risk and requirement mapping: Pinpoint table stakes, differentiators, and anti-features, plus potential pitfalls and mitigations.
Documentation deliverables: Produce structured outputs (STACK.md, FEATURES.md, ARCHITECTURE.md, PITFALLS.md) and a consolidated research document for downstream roadmapping.
Use Case: Before launching a greenfield product, run this agent to generate the baseline architecture and feature plan from domain research.

Quick Start

Invoke the /gsd:new-project orchestrator to spawn the four parallel researchers.

Frequently Asked Questions about gsd-project-researcher

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

FAQPage Schema

How do I research a domain ecosystem for project initialization?▼

Researching a domain ecosystem for project initialization requires analyzing standard technology stacks, architecture patterns, and common pitfalls to establish a solid foundation. This produces structured outputs including STACK.md, FEATURES.md, ARCHITECTURE.md, and PITFALLS.md to guide downstream roadmapping.

What is the best way to document architecture and pitfalls for a greenfield product?▼

Documenting architecture and pitfalls for a greenfield product requires generating structured deliverables like ARCHITECTURE.md and PITFALLS.md. This approach identifies table stakes, differentiators, anti-features, and mitigations to provide a repeatable baseline for teams starting a new project.

When do I need to run domain research before launching a greenfield product?▼

You need to run domain research before launching a greenfield product to discover standard stacks, recommended libraries, and typical architecture patterns. It is also applicable during subsequent milestones to guide stack decisions and map potential risks before development begins.

Can I use this to map features and technology stacks for subsequent milestones?▼

Yes, you can use this to map features and technology stacks for subsequent milestones. The process analyzes a domain to produce a consolidated research document and prescriptive templates that guide feature planning, architecture choices, and stack decisions beyond just the initial greenfield phase.

How do I generate a baseline architecture and feature plan from domain research?▼

To generate a baseline architecture and feature plan from domain research, you invoke the orchestrator to spawn parallel researchers. This produces structured outputs including STACK.md, FEATURES.md, ARCHITECTURE.md, and PITFALLS.md for downstream roadmapping.

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spawn-agent

Delegate scoped implementation, research and bug-fix tasks to Gemini or Codex worker agents via DEFINECOMPOSESPAWNREVIEWREPORT protocol scripts/templates/spawn-agent.sh with adjustable timeout, agent type, and approval modes.

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