grey-haven-context-management

More from greyhaven-ai/claude-code-config

• grey-haven-prompt-engineering

  Master 26 documented prompt engineering principles for crafting effective LLM prompts with 400%+ quality improvement. Includes templates, anti-patterns, and quality checklists for technical, learning, creative, and research tasks. Use when writing prompts for LLMs, improving AI response quality, training on prompting, designing agent instructions, or when user mentions 'prompt engineering', 'better prompts', 'LLM quality', 'prompt templates', 'AI prompts', 'prompt principles', or 'prompt optimization'.

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• grey-haven-ontological-documentation

  Create comprehensive ontological documentation for Grey Haven systems - extract domain concepts from TanStack Start and FastAPI codebases, model semantic relationships, generate visual representations of system architecture, and document business domains. Use when onboarding, documenting architecture, or analyzing legacy systems.

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• grey-haven-api-design

  Design RESTful APIs following Grey Haven standards - FastAPI routes, Pydantic schemas, HTTP status codes, pagination, filtering, error responses, OpenAPI docs, and multi-tenant patterns. Use when creating API endpoints, designing REST resources, implementing server functions, configuring FastAPI, writing Pydantic schemas, setting up error handling, implementing pagination, or when user mentions 'API', 'endpoint', 'REST', 'FastAPI', 'Pydantic', 'server function', 'OpenAPI', 'pagination', 'validation', 'error handling', 'rate limiting', 'CORS', or 'authentication'.

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• grey-haven-llm-project-development

  Build LLM-powered applications and pipelines using proven methodology - task-model fit analysis, pipeline architecture, structured outputs, file-based state, and cost estimation. Use when building AI features, data processing pipelines, agents, or any LLM-integrated system. Inspired by Karpathy's methodology and production case studies.

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• grey-haven-tdd-python

  Python Test-Driven Development expertise with pytest, strict red-green-refactor methodology, FastAPI testing patterns, and Pydantic model testing. Use when implementing Python features with TDD, writing pytest tests, testing FastAPI endpoints, developing with test-first approach, or when user mentions 'Python TDD', 'pytest', 'FastAPI testing', 'red-green-refactor', 'Python unit tests', 'test-driven Python', or 'Python test coverage'.

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• grey-haven-smart-debugging

  AI-powered intelligent debugging with stack trace analysis, error pattern recognition, and automated fix suggestions. Use when debugging complex errors, analyzing stack traces, or performing root cause analysis. Triggers: 'debug', 'error analysis', 'stack trace', 'root cause', 'troubleshooting'.

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