monitoring-cpu-usage
This skill enables Claude to monitor and analyze CPU usage patterns within applications. It helps identify CPU hotspots, analyze algorithmic complexity, and detect blocking operations. Use this skill when the user asks to "monitor CPU usage", "optimize CPU performance", "analyze CPU load", or "find CPU bottlenecks". It assists in identifying inefficient loops, regex performance issues, and provides optimization recommendations. This skill is designed for improving application performance by addressing CPU-intensive operations.
find-CBasePlayerPawn_CommitSuicide
Find and identify the CBasePlayerPawn_CommitSuicide function in CS2 binary using IDA Pro MCP. Use this skill when reverse engineering CS2 server.dll or libserver.so to locate the CommitSuicide function by searching for the "bot_kill" command string, tracing to its handler, and identifying the CommitSuicide vfunc call in the kill loop.
Bottom-Up Nervous System Regulation
Use physiological "bottom-up" interventions to rapidly shift your state of mind. Apply this when feeling high-stakes anxiety before a presentation, detecting early signs of burnout (the "feather"), or when you are stuck in a repetitive, anxious thought loop.
using-systems-thinking
Router for systems thinking methodology - patterns, leverage points, archetypes, stocks-flows, causal loops, BOT graphs
ecs-performance-audit
Analyze Entity Component System implementations for performance bottlenecks including entity iteration efficiency, system priority ordering, memory allocation patterns in hot paths (OnUpdate, rendering loops), cache coherency, LINQ allocations, and boxing issues. Use when reviewing ECS code for optimization, debugging slow entity updates, or investigating frame rate drops.
openai-agents
Use this skill when building AI applications with the OpenAI Agents SDK for JavaScript/TypeScript. The skill covers both text-based agents and realtime voice agents (via @openai/agents-realtime), including multi-agent workflows (handoffs), tools defined with Zod schemas, input/output guardrails, structured outputs, streaming, human-in-the-loop patterns, and framework integrations for Cloudflare Workers, Next.js, and React. It prevents 9+ common errors including Zod schema type errors, MCP tracing failures, infinite loops, tool call failures, and schema mismatches. The skill includes comprehensive templates for all agent types, error handling patterns, and debugging strategies. Keywords: OpenAI Agents SDK, @openai/agents, @openai/agents-realtime, openai agents javascript, openai agents typescript, text agents, voice agents, realtime agents, multi-agent workflows, agent handoffs, agent tools, zod schemas agents, structured outputs agents, agent streaming, agent guardrails, input guardrails, output guardrails, human-in-the-loop, cloudflare workers agents, nextjs openai agents, react openai agents, hono agents, agent debugging, Zod schema type error, MCP tracing failure, agent infinite loop, tool call failures, schema mismatch agents
claude-agent-sdk
This skill provides comprehensive knowledge for working with the Anthropic Claude Agent SDK. It should be used when building autonomous AI agents, creating multi-step reasoning workflows, orchestrating specialized subagents, integrating custom tools and MCP servers, or implementing production-ready agentic systems with Claude Code's capabilities. Use when building coding agents, SRE systems, security auditors, incident responders, code review bots, or any autonomous system that requires programmatic interaction with Claude Code CLI, persistent sessions, tool orchestration, and fine-grained permission control. Keywords: claude agent sdk, @anthropic-ai/claude-agent-sdk, query(), createSdkMcpServer, AgentDefinition, tool(), claude subagents, mcp servers, autonomous agents, agentic loops, session management, permissionMode, canUseTool, multi-agent orchestration, settingSources, CLI not found, context length exceeded
add-rcpp-integration
Add Rcpp or RcppArmadillo integration to an R package for high-performance C++ code. Covers setup, writing C++ functions, RcppExports generation, testing compiled code, and debugging. Use when an R function is too slow and profiling confirms a bottleneck, when you need to interface with existing C/C++ libraries, or when implementing algorithms (loops, recursion, linear algebra) that benefit from compiled code.
coordinate-swarm
Apply collective intelligence coordination patterns — stigmergy, local rules, and quorum sensing — to organize distributed systems, teams, or workflows without centralized control. Covers signal design, agent autonomy boundaries, emergent behavior cultivation, and feedback loop tuning. Use when designing distributed systems without a coordination bottleneck, organizing teams that must self-coordinate, building event-driven architectures with shared state communication, or replacing fragile centralized orchestration with resilient emergent coordination.
ideal-react-component
Use when creating React components, structuring component files, organizing component code, debugging React hooks issues, or when asked to "create a React component", "structure this component", "review component structure", "refactor this component", "fix infinite loop", or "useEffect not working". Applies to both TypeScript and JavaScript React components. Includes hooks antipatterns.
coordinate-swarm
Apply collective intelligence coordination patterns — stigmergy, local rules, and quorum sensing — to organize distributed systems, teams, or workflows without centralized control. Covers signal design, agent autonomy boundaries, emergent behavior cultivation, and feedback loop tuning. Use when designing distributed systems without a coordination bottleneck, organizing teams that must self-coordinate, building event-driven architectures with shared state communication, or replacing fragile centralized orchestration with resilient emergent coordination.
add-rcpp-integration
Add Rcpp or RcppArmadillo integration to an R package for high-performance C++ code. Covers setup, writing C++ functions, RcppExports generation, testing compiled code, and debugging. Use when an R function is too slow and profiling confirms a bottleneck, when you need to interface with existing C/C++ libraries, or when implementing algorithms (loops, recursion, linear algebra) that benefit from compiled code.
yt-to-ren
Extract YouTube video transcripts and inject them as market context into a trading AI (Ren/loop-bot). Supports metadata tagging, library management, and keyword search.
loop-instinct-system
Continuous learning instinct engine for trading bots. Manages named instincts with confidence scoring (0.0-1.0) that evolve based on trade outcomes. Integrates with LLM-based trading agents via tag injection.
lint-build-loop
Run `npm run lint && npm run build` in a loop, fixing errors until both succeed. Use when the user asks to iterate on lint/build failures.
Agent System Learning Loop
Evaluate and improve AgentSystem learning quality for memory/self-compound jobs. Use when bots forget, write filler summaries, fail to update learnings, or memory quality regresses over time.