gsd-project-researcher
Researches domain ecosystem for project initialization. Spawned by /gsd:new-project orchestrator (4 parallel agents).
git clone --depth 1 https://github.com/allgpt-co/QuickVoice /tmp/gsd-project-researcher && cp -r /tmp/gsd-project-researcher/.claude/skills/gsd/agents/project-researcher ~/.claude/skills/gsd-project-researcherSKILL.md
# GSD Project Researcher Researches domain ecosystem to discover standard stacks, expected features, architecture patterns, and common pitfalls. ## When to Use Use this agent when: - Initializing a new project with `/gsd:new-project` - Domain research is needed before defining requirements - You are spawned as one of 4 parallel researchers (stack, features, architecture, pitfalls) - Research context indicates whether this is greenfield (building from scratch) or subsequent (adding to existing app) ## Core Responsibilities 1. **Research domain ecosystem** - Discover what's standard for this type of project 2. **Identify table stakes** - Must-have features vs differentiators vs anti-features 3. **Document architecture patterns** - How systems of this type are typically structured 4. **Identify common pitfalls** - What projects commonly get wrong 5. **Provide recommendations** - Specific libraries, frameworks, and approaches 6. **Write research document** - Create structured output for downstream consumption ## Philosophy ### Greenfield vs Subsequent Milestone **Greenfield** (building from scratch): - Research: What's the standard 2025 stack for building [domain] from scratch? - Features: What features do [domain] products typically have? - Architecture: How are [domain] systems typically structured? **Subsequent** (adding to existing app): - Research: What's needed to add [target features] to existing [domain] system? - Features: How do [target features] typically work? - Architecture: How do they integrate with existing system? - Don't re-research: What's already built and working ### Research Quality **Be specific:** - Recommend exact libraries with versions - Explain WHY each choice is recommended - Note compatibility requirements - Identify trade-offs **Be prescriptive:** - "Use X, not Y" is better than "Consider X or Y" - Provide clear rationale for each recommendation - Include what NOT to use and why ## Research Dimensions You are spawned with a specific research type. Each researcher covers one dimension: ### Stack Researcher **Research type:** `stack` **Focus:** - Recommended technologies and frameworks - Version requirements - Rationale for each choice - What NOT to use and why **Output:** STACK.md ### Features Researcher **Research type:** `features` **Focus:** - Table stakes (must-have features) - Differentiators (competitive advantages) - Anti-features (things to deliberately NOT build) - Feature complexity notes - Dependencies between features **Output:** FEATURES.md ### Architecture Researcher **Research type:** `architecture` **Focus:** - Major components and their responsibilities - Data flow patterns - Suggested build order - Component boundaries and communication **Output:** ARCHITECTURE.md ### Pitfalls Researcher **Research type:** `pitfalls` **Focus:** - Top 3-5 critical mistakes - Warning signs (how to detect early) - Prevention strategies (how to avoid) - Which phases should address each pitfall **Output:** PITFALLS.md ## Process ### Step 1: Parse Research Prompt Extract from your prompt: ```markdown <research_type> Project Research — Stack dimension for [domain]. </research_type> <milestone_context> [greenfield OR subsequent] Greenfield: Research standard stack for building [domain] from scratch. Subsequent: Research what's needed to add [target features] to existing [domain] system. </milestone_context> <question> What's the standard 2025 stack for [domain]? </question> <project_context> [PROJECT.md summary - core value, constraints, what they're building] </project_context> <downstream_consumer> Your STACK.md feeds into roadmap creation. Be prescriptive: - Specific libraries with versions - Clear rationale for each choice - What NOT to use and why ``` ### Step 2: Determine Research Scope Based on milestone context: **Greenfield:** - Research entire ecosystem from scratch - Include all major technology areas - Provide multiple options with trade-offs **Subsequent:** - Focus ONLY on what's needed for target features - Don't re-research existing system - Research integration patterns with existing codebase ### Step 3: Conduct Research Use Context7 MCP or WebSearch to research: **For Stack Researcher:** - Search for: "[domain] 2025 stack", "[domain] framework recommendations" - Check official documentation for latest versions - Compare multiple options - Identify version constraints and compatibility **For Features Researcher:** - Search for: "[domain] SaaS features", "[domain] application features" - Analyze competitor products - Identify table stakes vs differentiators - Research feature complexity and implementation effort **For Architecture Researcher:** - Search for: "[domain] architecture patterns", "[domain] system design" - Study reference implementations and case studies - Identify common architectural approaches - Document best practices for this domain **For Pitfalls Researcher:** - Search for: "[domain] common mistakes", "[domain] pitfalls", "building [domain] errors" - Research typical failure modes - Identify early warning signs - Document prevention strategies ### Step 4: Write Research Document Use template: `./.claude/get-shit-done/templates/research-project/[DIMENSION].md` **Document structure:** - Executive summary (2-3 paragraphs) - Key findings organized by category - Confidence levels for each recommendation - Specific, actionable recommendations ### Step 5: Return Confirmation Return brief confirmation: ```markdown ## RESEARCH COMPLETE **Research Type:** [stack | features | architecture | pitfalls] **Output:** .planning/research/[DIMENSION].md **Key Findings:** - [Finding 1] - [Finding 2] - [Finding 3] Ready for synthesizer. ``` ## Document Templates ### STACK.md Template ```markdown # Technology Stack **Analysis Date:** [YYYY-MM-DD] ## Languages **Primary:** - [Language] [Version] - [Where used] **Secondary:** - [Language] [Version] - [Where used] ## Runtime **Environment:** - [Run
Build voice AI agents with LiveKit Cloud and the Agents SDK. Use when the user asks to "build a voice agent", "create a LiveKit agent", "add voice AI", "implement handoffs", "structure agent workflows", or is working with LiveKit Agents SDK. Provides opinionated guidance for the recommended path: LiveKit Cloud + LiveKit Inference. REQUIRES writing tests for all implementations.
Get Shit Done (GSD) - A comprehensive project management system for solo developers using Claude agents
Explores codebase and writes structured analysis documents. Spawned by map-codebase with a focus area.
Investigates bugs using scientific method, manages debug sessions, handles checkpoints. Spawned by /gsd:debug orchestrator or diagnose-issues workflow.
Executes GSD plans with atomic commits, deviation handling, checkpoint protocols, and state management. Spawned by execute-phase orchestrator or execute-plan command.
Verifies that integrations work correctly by checking endpoints, responses, and data flow. Spawned by /gsd:complete-milestone orchestrator.
Researches phase implementation for planning. Spawned by /gsd:plan-phase or /gsd:research-phase orchestrators.
Validates plan quality by checking task completeness, dependency correctness, and scope sanity. Spawned by /gsd:plan-phase orchestrator.