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A comprehensive guide for profiling, analyzing, and optimizing Python code. It addresses identifying performance bottlenecks related to CPU usage, excessive memory consumption, I/O operations, and slow data processing. Use this skill to improve application speed and efficiency in production environments.

Quantizes HuggingFace LLMs to 8-bit or 4-bit with bitsandbytes, cutting memory by up to 75% while keeping accuracy, and supports QLoRA fine-tuning plus 8-bit optimizers for faster, memory-efficient training.

Automate Composio’s Remote Retrieval toolkit via Rube MCP by always discovering tool schemas with `RUBE_SEARCH_TOOLS`, ensuring active `remote_retrieval` connections, and executing discovered workflows through `RUBE_MULTI_EXECUTE_TOOL` while honoring schema and memory requirements.

Provides systematic methods for diagnosing complex, intermittent errors in the Replit environment. This guide covers advanced topics like container lifecycle issues, Nix build failures, memory leaks, and deployment crash loops using sophisticated shell scripting and runtime monitoring techniques. Use when standard troubleshooting steps fail to identify the root cause.

This comprehensive guide provides methods for implementing deep observability for Replit deployments. It covers building detailed health check endpoints (tracking uptime, memory, and DB status), setting up structured JSON logging, detecting cold start events, and configuring external alerting mechanisms (e.g., UptimeRobot, Slack). Use this when building robust, production-grade applications that require continuous performance monitoring and reliability tracking.

A comprehensive guide for optimizing application performance on Replit. Covers critical areas such as reducing cold start times, managing memory consumption, optimizing Nix environment dependencies, accelerating build processes, and ensuring database connection efficiency. Use this guide when facing slow startups, resource limits, or deployment slowdowns.

This skill provides comprehensive guardrails for securing Replit-hosted applications. It covers critical security policies including preventing hardcoded secrets, implementing resource usage limits (CPU/Memory), enforcing endpoint authentication, and ensuring proper deployment configuration. Use this when you need to harden a Replit app for production or audit its security posture.

Automate retail operations via Composio’s Rube MCP by discovering tool schemas, confirming active Retailed connections, and running workflows that respect the latest execution plans, pagination guidance, and memory/session expectations.

Automates Retellai workflows through Composio's Rube MCP toolkit, guiding tool discovery, connection checks, schema-compliant invocation, and memory/session handling via the RUBE search/manage/execute calls.

This skill provides a comprehensive, expert guide to the entire reverse engineering lifecycle. It covers advanced techniques for binary analysis, including static analysis (disassembly, metadata extraction, control flow mapping) and dynamic analysis (API hooking, memory tracing). Mastery includes utilizing industry-leading tools such as IDA Pro, Ghidra, radare2, and specialized frameworks like pwntools and angr. The methodology is structured for secure research, CTF challenges, and vulnerability assessment, emphasizing best practices and ethical use.

Automates Revolt operations through Composio's Rube MCP toolkit, guiding you to search current tool schemas, validate connection status, and run schema-compliant multi-step workflows with memory and session handling.

Streamline Rkvst workflows by letting Composio's Rube MCP discover current tool schemas, manage Rkvst connections, and execute operations while enforcing schema compliance, memory handling, and session best practices.