13114d7868
- Updated .cursor/mcp.json to use local Nix-built Task Master binary - Configured Task Master to use local Ollama models via OpenAI-compatible API - Set up three models: qwen3:4b (main), deepseek-r1:1.5b (research), gemma3:4b-it-qat (fallback) - Created comprehensive integration status documentation - Task Master successfully running as MCP server with 23+ available tools - Ready for VS Code/Cursor AI chat integration
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1.5 KiB
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47 lines
No EOL
1.5 KiB
Text
<context>
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# Overview
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[Provide a high-level overview of your product here. Explain what problem it solves, who it's for, and why it's valuable.]
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# Core Features
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[List and describe the main features of your product. For each feature, include:
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- What it does
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- Why it's important
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- How it works at a high level]
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# User Experience
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[Describe the user journey and experience. Include:
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- User personas
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- Key user flows
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- UI/UX considerations]
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</context>
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<PRD>
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# Technical Architecture
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[Outline the technical implementation details:
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- System components
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- Data models
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- APIs and integrations
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- Infrastructure requirements]
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# Development Roadmap
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[Break down the development process into phases:
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- MVP requirements
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- Future enhancements
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- Do not think about timelines whatsoever -- all that matters is scope and detailing exactly what needs to be build in each phase so it can later be cut up into tasks]
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# Logical Dependency Chain
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[Define the logical order of development:
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- Which features need to be built first (foundation)
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- Getting as quickly as possible to something usable/visible front end that works
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- Properly pacing and scoping each feature so it is atomic but can also be built upon and improved as development approaches]
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# Risks and Mitigations
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[Identify potential risks and how they'll be addressed:
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- Technical challenges
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- Figuring out the MVP that we can build upon
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- Resource constraints]
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# Appendix
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[Include any additional information:
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- Research findings
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- Technical specifications]
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</PRD> |