gpu-debugger
Debug failed GPU CLI runs. Analyze error messages, diagnose OOM errors, fix sync issues, troubleshoot connectivity, and resolve common problems. Turn cryptic errors into actionable fixes.
aws-agentic-ai
AWS Bedrock AgentCore comprehensive expert for deploying and managing all AgentCore services. Use when working with Gateway, Runtime, Memory, Identity, or any AgentCore component. Covers MCP target deployment, credential management, schema optimization, runtime configuration, memory management, and identity services.
threejs-graphics-optimizer
Performance optimization rules for THREE.js and graphics programming. Covers mobile-first optimization, fallback patterns, memory management, render loop efficiency, and general graphics best practices for smooth 60fps experiences across devices.
get-available-resources
This skill should be used at the start of any computationally intensive scientific task to detect and report available system resources (CPU cores, GPUs, memory, disk space). It creates a JSON file with resource information and strategic recommendations that inform computational approach decisions such as whether to use parallel processing (joblib, multiprocessing), out-of-core computing (Dask, Zarr), GPU acceleration (PyTorch, JAX), or memory-efficient strategies. Use this skill before running analyses, training models, processing large datasets, or any task where resource constraints matter.
memory-location
Configure chitta memory storage location for optimal I/O performance. Use when memory is slow, setting up fast storage, or moving the soul database.
memory-consolidation
Background process that proactively maintains memory hygiene. Scans for obsolescence to prune irrelevant data and synthesizes scattered information into higher-order patterns.
python-performance-optimization
Python performance optimization patterns using profiling, algorithmic improvements, and acceleration techniques. Use when optimizing slow Python code, reducing memory usage, or improving application throughput and latency.
go-performance
Go performance optimization - profiling, benchmarks, memory management
ios-fundamentals
Master iOS development foundations - Architecture, lifecycle, memory, concurrency
Python Performance
Master Python optimization techniques, profiling, memory management, and high-performance computing
ownership-borrowing
Master Rust's ownership, borrowing, and lifetime system
memory-management
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custom-plugin-flutter-skill-performance
1600+ lines of performance optimization mastery - profiling, rendering, memory, network, battery, APK size with production-ready code examples.
streams
Master Node.js streams for memory-efficient processing of large datasets, real-time data handling, and building data pipelines
creating-handoffs
Creates comprehensive handoff documents for seamless AI agent session transfers. Triggered when: (1) user requests handoff/memory/context save, (2) context window approaches capacity, (3) major task milestone completed, (4) work session ending, (5) user says 'save state', 'create handoff', 'I need to pause', 'context is getting full', (6) resuming work with 'load handoff', 'resume from', 'continue where we left off'. Proactively suggests handoffs after substantial work (multiple file edits, complex debugging, architecture decisions). Solves long-running agent context exhaustion by enabling fresh agents to continue with zero ambiguity.
session-memory-bootstrap
Session start bootstrap. Use this skill at the beginning of EVERY new session, before answering anything else. Purpose: load persistent user memory from the repo-root memories.md file (create it if missing), then apply it to the rest of the session. If this is not a new session, only use this skill when memory is relevant or when the user asks to remember or forget something.
particles-lifecycle
Particle lifecycle management—emission/spawning, death conditions, object pooling, trails, fade-in/out, and state transitions. Use when particles need birth/death cycles, continuous emission, trail effects, or memory-efficient recycling.
debugging-memory
This skill should be used when the user asks to "debug this", "fix this bug", "why is this failing", "investigate error", "getting an error", "exception thrown", "crash", "not working", "what's causing this", "root cause", "diagnose this issue", or describes any software bug or error. Also activates when spawning subagents for debugging tasks, using Task tool for bug investigation, or coordinating multiple agents on a debugging problem. Provides memory-first debugging workflow that checks past incidents before investigating.
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