Agent Skills Hub

sequential-thinking

Structured reasoning tool for complex problem decomposition, step-by-step analysis, consistency verification, and evidence-based synthesis with confidence scoring.

session-logs

Search, analyze, and audit GeminiClaw session logs and memory. Use to investigate past interactions, track token usage, debug tool calls, and monitor agent performance.

debug-cuda-crash

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

dynamic

Fullstack development agent for bkend.ai BaaS. Automates project init, auth/db setup, and API integration for Next.js applications.

scikit-learn

Classical machine learning with scikit-learn. Use for classification, regression, clustering, dimensionality reduction, preprocessing, model evaluation, and building robust ML pipelines in Python.

use-railway

Operate Railway infrastructure: manage projects, services, databases, object storage, deployments, environments, variables, logs, and performance metrics.

go

Autonomous recursive execution engine for indiiOS that manages task completion, state verification, and error handling.

Swarm Orchestration

Orchestrate multi-agent swarms using agentic-flow for parallel task execution, dynamic topology, and intelligent coordination. Ideal for building distributed AI systems and scaling complex development workflows.

service-mesh-observability

Implement production-grade observability for Istio and Linkerd service meshes, including distributed tracing, metric dashboards, and golden signal monitoring.

sage-mcp-protocol

Sage MCP protocol implementation for integrating external tool servers and standardized AI model context.

trading-strategies

Framework for building, testing, and deploying automated trading strategies for prediction markets using Python.

stable-baselines3

Production-ready reinforcement learning using Stable Baselines3. Train agents, design custom environments, implement training callbacks, and optimize workflows with a scikit-learn-style API.