tendercoconut174
Community@tendercoconut174
tendercoconut174 provides code-generation skills for building a multi-agent platform spanning LangGraph orchestration, FastAPI services, PostgreSQL persistence, security, and observability.
Agent Skills by tendercoconut174
Showing 14 vetted skills indexed across 1 GitHub repositories.
tendercoconut174agent-skill
Generate CrewAI agents, system prompts, and agent registry entries for LangGraph workflows.
tendercoconut174tool-skill
Generate MCP tools, LangChain wrappers, and agent-tool bindings for AI agents.
tendercoconut174workflow-skill
Generate LangGraph supervisor nodes, execution plans, and workflow orchestration logic.
tendercoconut174error-handling-skill
Generates retry logic, circuit breakers, dead-letter queues, and graceful degradation patterns for Python services.
tendercoconut174architectural-skill
Generate services, agents, workflows, and orchestration logic for a LangGraph multi-agent platform.
tendercoconut174documentation-skill
Generate README files, API documentation, docstrings, and developer guides for codebases.
tendercoconut174coding-skill
Generates Python code, FastAPI services, agents, and workflows following platform coding standards.
tendercoconut174devops-skill
Runs and deploys an AI agent platform locally or with Docker Compose and PostgreSQL.
tendercoconut174security-skill
Generates authentication, authorization, input validation, and rate limiting patterns for APIs.
tendercoconut174change-docs-skill
Updates README, docs, and Cursor skills after every code change.
tendercoconut174observability-skill
Generate structured logging, metrics, and distributed tracing code for Python services.
tendercoconut174database-skill
Generates SQLAlchemy models, Alembic migrations, and PostgreSQL queries for database persistence.
tendercoconut174testing-skill
Generate pytest unit, integration, workflow, agent, tool, and API endpoint tests.
tendercoconut174memory-skill
Generates session memory, vector memory, and RAG patterns for AI agent platforms.
Frequently Asked Questions About tendercoconut174
FAQPage SchemaWhat tasks can I accomplish using tendercoconut174's skills?▼
You can generate agents, system prompts, MCP and LangChain bindings, LangGraph supervisor graphs, FastAPI services, Pydantic data models, SQLAlchemy migrations, authentication layers, retry and circuit-breaker logic, structured logging, RAG memory, pytest suites, and project documentation for an agent platform.
Who is the target audience for these skills?▼
Backend and platform engineers building a multi-agent system on Python, FastAPI, LangGraph, and PostgreSQL. It suits developers implementing supervisor orchestration, session memory, endpoint security, observability, and test coverage rather than end users or non-technical teams.
How do I run and deploy projects built with these skills?▼
The devops-skill covers running the project locally or with Docker, managing PostgreSQL, building images, and using docker-compose for local development. It guides starting, testing, and deploying the application stack including the database service.
What prerequisites and dependencies do these skills assume?▼
The stack assumes Python with FastAPI, Pydantic, LangGraph, LangChain, and SQLAlchemy, plus PostgreSQL for persistence and Docker with docker-compose for local runs. Testing relies on pytest, and memory features assume embeddings and vector stores for retrieval.
How do the skills keep documentation and quality in sync?▼
The change-docs-skill enforces updating README.md, docs, and Cursor skills after every feature, refactor, or bugfix. The testing-skill generates unit, integration, and endpoint tests, while the observability-skill adds logging, metrics, and tracing for production debugging.