Agent Skills Hub

policyengine-review-patterns

Standardized review patterns, validation checklists, and quality benchmarks for PolicyEngine codebases.

literature-engineer

Evidence-first literature collector for automated research pipelines. Scales paper pools to 1200+ with metadata normalization, provenance tracking, and multi-source ingestion.

create-worktree

Automates the creation of isolated git worktree environments for parallel feature development and environment setup.

customer-feedback-analyzer

A framework for collecting, analyzing, and prioritizing user feedback across multiple channels to drive product strategy and feature development.

training-data-curation

Guidelines for curating high-quality datasets for LLM post-training (SFT/DPO/RLHF), covering data formats, quality filtering, and collection strategies.

kreuzberg

High-performance document intelligence library for extracting text, tables, code, and metadata from 91+ file formats, with OCR and LLM-ready output.

linear-issue-creator

Creates structured Linear issues (main + sub-issues) with automated project linking, title prefixes, labeling, and PRD-aligned content workflows for fullstack developers.

long-running-agent

Framework for building AI agents that persist state across multiple context windows, enabling them to complete complex, multi-day coding tasks without losing progress or context.

ai-llm-patterns

Anthropic Claude integration patterns: streaming, RAG with pgvector, tool use, model selection (Haiku/Sonnet/Opus), prompt caching, and cost management for AI-powered engineering.

frontend-to-backend-requirements

Standardize frontend communication by documenting data requirements and business rules for backend developers, ensuring clear alignment without dictating implementation details.

transcription

Production-ready audio/video transcription using OpenAI Whisper. Features model selection, timing synchronization, speaker diarization, and batch processing for media workflows.

casadi-ipopt-nlp

Nonlinear optimization toolkit using CasADi and IPOPT. Ideal for building complex NLP models, defining symbolic variables, constraints, and solvers, with specialized support for power systems optimization patterns.