Agent Skills Hub

context-optimization

Optimize agent context windows through KV-caching, observation masking, summarization-based compaction, and context partitioning to reduce costs and latency.

training-data-curation

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

generate-image

Generate or edit images using AI models like FLUX and Gemini. Ideal for photos, illustrations, concept art, and visual assets, excluding technical diagrams and schematics.

k8s-troubleshooting

AI-powered Kubernetes and OpenShift troubleshooting. Proactively assess cluster health, debug pod failures, analyze logs, and validate security using Popeye-inspired patterns.

debug-cuda-crash

Tutorial for identifying and resolving CUDA runtime crashes using FlashInfer's API logging framework.

mls

Unified local ML inference server for ASR, TTS, Translation, Image Generation, and Vision on Apple Silicon, powered by MLX.

self-improve

Self-maintaining skill for OpenCode agents to update documentation, capture learnings, and extend tool/agent capabilities dynamically.

cost-optimization

Systematic cloud cost optimization for AWS, Azure, GCP, and OCI through resource rightsizing, automated governance, pricing model analysis, and architectural best practices.

context-engineering-collection

A structured repository of Agent Skills for context engineering, multi-agent architectures, and production-grade agent system optimization.

memory-systems

Guides agent memory system implementation, compares frameworks (Mem0, Zep, Letta, LangMem, Cognee), and designs persistence architectures for cross-session knowledge retention.

database-testing

Database schema validation, data integrity testing, migration validation, transaction isolation, and query performance testing. Ensure ACID compliance and referential integrity for data-driven applications.

prompt-rewriter

Advanced prompt rewriting and optimization service. Analyzes prompts for clarity, specificity, and structure, providing actionable improvements, variations for testing, and prompt engineering best practices.