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Found 364 Skills
AI-first coding guidelines for projects maintained by LLMs. Use when creating new code, refactoring, or reviewing code to optimize for model reasoning, regenerability, and debugging; applies to layout, architecture, functions, naming, logging, platform use, and tests.
Dollar Cost Averaging (DCA) for Stacks DeFi — automate recurring buys or sells of any Bitflow token pair via direct swaps. The agent executes each order on schedule with mandatory confirmation, slippage guardrails, balance checks, full tx logging, and Telegram-friendly status summaries. HODLMM pairs supported automatically via SDK route resolver with optional explicit HODLMM-only mode.
Troubleshoots and debugs AWS Clean Rooms collaboration issues related to IAM roles, S3 bucket policies, KMS keys, Lake Formation permissions, and CloudWatch logging for custom ML model training and inference jobs. Use when a customer reports permission failures, access errors, or log publishing issues in Clean Rooms.
How to debug tursodb using Bytecode comparison, logging, ThreadSanitizer, deterministic simulation, and corruption analysis tools
Track and visualize ML training experiments with Trackio. Use when logging metrics during training (Python API) or retrieving/analyzing logged metrics (CLI). Supports real-time dashboard visualization, HF Space syncing, and JSON output for automation.
You are an error tracking and observability expert specializing in implementing comprehensive error monitoring solutions. Set up error tracking systems, configure alerts, implement structured logging,
Structured logging with proper levels, context, PII handling, centralized aggregation. Use for application logging, log management integration, distributed tracing, or encountering log bloat, PII exposure, missing context errors.
Build complete, production-ready Arduino projects (environmental monitors, robot controllers, IoT devices, automation systems). Assembles multi-component systems combining sensors, actuators, communication protocols, state machines, data logging, and power management. Supports Arduino UNO, ESP32, and Raspberry Pi Pico with board-specific optimizations. Use this skill when users request complete Arduino applications, not just code snippets.
This skill should be used when adding error tracking and performance monitoring with Sentry and OpenTelemetry tracing to Next.js applications. Apply when setting up error monitoring, configuring tracing for Server Actions and routes, implementing logging wrappers, adding performance instrumentation, or establishing observability for debugging production issues.
Know when your AI breaks in production. Use when you need to monitor AI quality, track accuracy over time, detect model degradation, set up alerts for AI failures, log predictions, measure production quality, catch when a model provider changes behavior, build an AI monitoring dashboard, or prove your AI is still working for compliance. Covers DSPy evaluation for ongoing monitoring, prediction logging, drift detection, and alerting.
Implement middleware for authentication, logging, CORS, and request processing. Use for cross-cutting concerns and request/response modification.
Use when storing credentials in OCI Vault, troubleshooting secret retrieval failures, implementing secret rotation, or setting up application authentication to Vault. Covers vault hierarchy confusion, IAM permission gotchas, cost optimization, temp file security, and audit logging.