trigger-dev-tasks
Expert assistant for designing and optimizing production-grade Trigger.dev background jobs, AI workflows, and resilient asynchronous task architectures in TypeScript.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
164 skills found
Expert assistant for designing and optimizing production-grade Trigger.dev background jobs, AI workflows, and resilient asynchronous task architectures in TypeScript.
A structured PRD generator for vibe-coding MVPs. It guides you through defining product requirements, target audiences, and success metrics, ensuring a clear foundation for your development workflow.
AI-driven GitHub Actions automation featuring swarm-based workflow orchestration, intelligent CI/CD pipeline management, and autonomous repository maintenance.
Extract tacit engineering knowledge through guided interviews and generate structured steerings for consistent project standards and conventions.
Meta-skill for generating publication-ready scientific figures, multi-panel layouts, and journal-compliant visualizations using Python's matplotlib, seaborn, and plotly libraries.
Bayesian modeling and probabilistic programming with PyMC. Build hierarchical models, perform MCMC sampling (NUTS), variational inference, and conduct rigorous model comparison using LOO and WAIC.
Create professional data visualizations with Python using matplotlib, seaborn, and plotly. Includes chart selection guidance, design principles, accessibility standards, and code patterns for publication-quality figures.
Comprehensive biosignal processing toolkit for ECG, EEG, EDA, RSP, PPG, EMG, and EOG signal analysis, enabling psychophysiology research and multi-modal integration.
Build production-grade AI agents using LangGraph, Anthropic/OpenAI/vLLM, and structured outputs. Features streaming, A2A protocol, Pydantic validation, vector memory, and guardrails for resilient, multi-agent workflows.
Applies cognitive science frameworks for creative thinking to generate genuinely novel research directions in computer science and AI.
A project-specific architectural template for Next.js 15, FastAPI, and Supabase applications, including structured AI integration patterns.
Prevents AI hallucination and ensures evidence-based, verifiable outputs when analyzing code, reviewing technical documents, or providing recommendations.