Configure Turborepo for efficient monorepo builds with local and remote caching. Use when setting up Turborepo, optimizing build pipelines, or implementing distributed caching.

Implement distributed tracing with Jaeger and Tempo to track requests across microservices and identify performance bottlenecks. Use when debugging microservices, analyzing request flows, or implementing observability for distributed systems.

Python error handling patterns including input validation, exception hierarchies, and partial failure handling. Use when implementing validation logic, designing exception strategies, handling batch processing failures, or building robust APIs.

Python observability patterns including structured logging, metrics, and distributed tracing. Use when adding logging, implementing metrics collection, setting up tracing, or debugging production systems.

Understand anti-reversing, obfuscation, and protection techniques encountered during software analysis. Use this skill when analyzing malware evasion techniques, when implementing anti-debugging protections for CTF challenges, when reverse engineering packed binaries, or when building security research tools that need to detect virtualized environments.

Master Go concurrency with goroutines, channels, sync primitives, and context. Use when building concurrent Go applications, implementing worker pools, or debugging race conditions.

Master Rust async programming with Tokio, async traits, error handling, and concurrent patterns. Use when building async Rust applications, implementing concurrent systems, or debugging async code.

Debug container agent issues. Use when things aren't working, container fails, authentication problems, or to understand how the container system works. Covers logs, environment variables, mounts, and common issues.

Model interpretability and explainability using SHAP (SHapley Additive exPlanations). Use this skill when explaining machine learning model predictions, computing feature importance, generating SHAP plots (waterfall, beeswarm, bar, scatter, force, heatmap), debugging models, analyzing model bias or fairness, comparing models, or implementing explainable AI. Works with tree-based models (XGBoost, LightGBM, Random Forest), deep learning (TensorFlow, PyTorch), linear models, and any black-box model.

Integrates with Atlassian products to manage project tracking and documentation via MCP protocol. Use when querying Jira issues with JQL filters, creating and updating tickets with custom fields, searching or editing Confluence pages with CQL, managing sprints and backlogs, setting up MCP server authentication, syncing documentation, or debugging Atlassian API integrations.

Use when building, debugging, or extending MCP servers or clients that connect AI systems with external tools and data sources. Invoke to implement tool handlers, configure resource providers, set up stdio/HTTP/SSE transport layers, validate schemas with Zod or Pydantic, debug protocol compliance issues, or scaffold complete MCP server/client projects using TypeScript or Python SDKs.

Writes and debugs Apex code, builds Lightning Web Components, optimizes SOQL queries, implements triggers, batch jobs, platform events, and integrations on the Salesforce platform. Use when developing Salesforce applications, customizing CRM workflows, managing governor limits, bulk processing, or setting up Salesforce DX and CI/CD pipelines.

Builds and debugs Shopify themes (.liquid files, theme.json, sections), develops custom Shopify apps (shopify.app.toml, OAuth, webhooks), and implements Storefront API integrations for headless storefronts. Use when building or customizing Shopify themes, creating Hydrogen or custom React storefronts, developing Shopify apps, implementing checkout UI extensions or Shopify Functions, optimizing performance, or integrating third-party services. Invoke for Liquid templating, Storefront API, app development, checkout customization, Shopify Plus features, App Bridge, Polaris, or Shopify CLI workflows.

Expert guidance for fast fine-tuning with Unsloth - 2-5x faster training, 50-80% less memory, LoRA/QLoRA optimization

Visualize training metrics, debug models with histograms, compare experiments, visualize model graphs, and profile performance with TensorBoard - Google's ML visualization toolkit

Open-source AI observability platform for LLM tracing, evaluation, and monitoring. Use when debugging LLM applications with detailed traces, running evaluations on datasets, or monitoring production AI systems with real-time insights.

Fine-tune and serve Physical Intelligence OpenPI models (pi0, pi0-fast, pi0.5) using JAX or PyTorch backends for robot policy inference across ALOHA, DROID, and LIBERO environments. Use when adapting pi0 models to custom datasets, converting JAX checkpoints to PyTorch, running policy inference servers, or debugging norm stats and GPU memory issues.

Fine-tunes and evaluates OpenVLA-OFT and OpenVLA-OFT+ policies for robot action generation with continuous action heads, LoRA adaptation, and FiLM conditioning on LIBERO simulation and ALOHA real-world setups. Use when reproducing OpenVLA-OFT paper results, training custom VLA action heads (L1 or diffusion), deploying server-client inference for ALOHA, or debugging normalization, LoRA merge, and cross-GPU issues.

Research-to-implement pipeline chaining 5 MCP tools with graceful degradation

Show full session token usage, costs, TLDR savings, and hook activity

Triggers the WORK-PIPELINE when a user request starts with a [] tag (e.g., [new-feature], [bugfix], [WORK start]). Use this skill whenever you detect a [] tag at the beginning of a user message.

Use when profiling CPU/memory hot paths, generating flame graphs, or capturing JFR/perf evidence.

AWS Step Functions workflow orchestration with state machines. Use when designing workflows, implementing error handling, configuring parallel execution, integrating with AWS services, or debugging executions.

Manages MongoDB Atlas Stream Processing (ASP) workflows. Handles workspace provisioning, data source/sink connections, processor lifecycle operations, debugging diagnostics, and tier sizing. Supports Kafka, Atlas clusters, S3, HTTPS, and Lambda integrations for streaming data workloads and event processing. NOT for general MongoDB queries or Atlas cluster management. Requires MongoDB MCP Server with Atlas API credentials.

This skill should be used when setting up or managing Polar local development environment with Docker.

Root cause analysis frameworks including log-first investigation, git bisect correlation, and pattern-based diagnosis with confidence scoring.

Urgent issue classification, root cause analysis, and fast-path routing for production hotfixes

Observation capture and retrieval across sessions. Stores decisions, discoveries, and bugfix patterns. Searchable via tags and relevance scoring.

Use when starting any conversation. Establishes how to find and use skills, requiring skill invocation before any response.

LangSmith tracing and debugging setup for LLM applications. Configure observability, capture traces, and enable debugging for LangChain/LangGraph agents.

Arize Phoenix observability platform setup for LLM debugging and evaluation

Generate visual representations of algorithm execution

CAN/CAN-FD bus analysis and development expertise

Deep integration with JTAG/SWD debug probes for hardware-level debugging and flash programming

Serial protocol analysis and debugging for common embedded interfaces (I2C, SPI, UART)

USB device and host stack implementation expertise

On-chip debugging skill with ILA, VIO, and related FPGA debug tools

Unity Profiler skill for performance analysis, frame debugging, memory profiling, and optimization workflows.

Deep integration with React Native ecosystem for cross-platform mobile development

Expert skill for gRPC protocol implementation, debugging, and performance optimization

Expert skill for generating and consuming source maps for debugging compiled code

RViz configuration and custom visualization for robot development and debugging

Expert skill for ROS tf2 coordinate frame management and transforms

Turbopack configuration and Next.js integration.

Guide for integrating Agentica SDK with Claude Code CLI proxy

Agentica server + Claude proxy setup - architecture, startup sequence, debugging

API versioning strategies, breaking change detection, deprecation lifecycle, and migration guides

Braintrust tracing for Claude Code - hook architecture, sub-agent correlation, debugging

Chrome DevTools MCP ile browser debugging. Console, network, performance, DOM analizi.

Gorev tipine gore dusunme modu secimi. 5 mod -- analytical (derin analiz), creative (yaratici cozum), systematic (adim adim), rapid (hizli aksiyon), debug (hata izleme). Her mod farkli prompt stratejisi ve karar agaci kullanir.