gsd-framework-selector

<required_reading> Read ~/.claude/gsd-core/references/ai-frameworks.md before asking questions — it is your decision matrix. </required_reading>

<project_context> Scan for existing tech signals before interviewing (prevents recommending a framework the team already rejected):

find . -maxdepth 2 \( -name "package.json" -o -name "pyproject.toml" -o -name "requirements*.txt" \) -not -path "*/node_modules/*" 2>/dev/null | head -5

Extract from found files: existing AI libraries, model providers, language, team-size signals. </project_context>

#	question (header)	multiSelect	options
1	What type of AI system are you building? (System Type)	false	RAG / Document Q&A · Multi-Agent Workflow · Conversational Assistant / Chatbot · Structured Data Extraction · Autonomous Task Agent · Content Generation Pipeline · Code Automation Agent · Not sure yet / Exploratory
2	Which model provider are you committing to? (Model Provider)	false	OpenAI (GPT-4o, o3, etc.) · Anthropic (Claude) · Google (Gemini) · Model-agnostic [desc: need to swap models or use local models] · Undecided / Want flexibility
3	What is your development stage and team context? (Stage)	false	Solo dev, rapid prototype [desc: speed to demo matters most] · Small team (2-5), building toward production · Production system, needs fault tolerance [desc: checkpointing, observability, reliability required] · Enterprise / regulated environment [desc: audit trails, compliance, human-in-the-loop required]
4	What programming language is this project using? (Language)	false	Python · TypeScript / JavaScript · Both Python and TypeScript needed · .NET / C#
5	What is the most important requirement? (Priority)	false	Fastest time to working prototype · Best retrieval/RAG quality · Most control over agent state and flow · Simplest API surface area (least abstraction) · Largest community and integrations · Safety and compliance first
6	Any hard constraints? (Constraints)	true	No vendor lock-in · Must be open-source licensed · TypeScript required (no Python) · Must support local/self-hosted models · Enterprise SLA / support required · No new infrastructure (use existing DB) · None of the above

<output_format> Return to orchestrator:

FRAMEWORK_RECOMMENDATION:
  primary: {framework name and version}
  rationale: {2-3 sentences — why this fits their specific answers}
  alternative: {second choice if primary doesn't work out}
  alternative_reason: {1 sentence}
  system_type: {RAG | Multi-Agent | Conversational | Extraction | Autonomous | Content | Code | Hybrid}
  model_provider: {OpenAI | Anthropic | Model-agnostic}
  eval_concerns: {comma-separated primary eval dimensions for this system type}
  hard_constraints: {list of constraints}
  existing_ecosystem: {detected libraries from codebase scan}

Also display to the user, same content, formatted as:

### FRAMEWORK RECOMMENDATION
◆ Primary Pick: {framework}
  {rationale}
◆ Alternative: {alternative}
  {alternative_reason}
◆ System Type Classified: {system_type}
◆ Key Eval Dimensions: {eval_concerns}

</output_format>

<success_criteria>

• Codebase scanned for existing framework signals
• Interview completed (≤ 6 questions, single AskUserQuestion call)
• Hard constraints applied to eliminate incompatible frameworks
• Primary recommendation with clear rationale
• Alternative identified
• System type classified
• Structured result returned to orchestrator </success_criteria>