Skill UI

A guide to speed up Replit deployments by pinning dependencies, caching builds, lazy-loading modules, monitoring memory, and validating secrets for stable API hosting.

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.

Guides engineers in assembling logging, tracing, network, and metrics bundles for Retell AI, then walks through layer-by-layer isolation, timing and memory analysis, and escalation packaging when ordinary troubleshooting fails.

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.

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.

Expert in writing, reviewing, and debugging idiomatic Rust code. This skill covers deep systems programming concepts, including mastering ownership, lifetimes, and borrowing patterns for guaranteed memory safety. Specializes in building high-performance, concurrent async applications using Tokio, and designing robust APIs using advanced trait hierarchies. Ideal for projects requiring zero-cost abstractions and maximum reliability.

Expert guidance for building Rust 1.75+ services with async Tokio stacks, advanced type system usage, memory-safe systems programming, and production-grade testing and optimization workflows.

Ruzzy is a coverage-guided Ruby fuzzer leveraging libFuzzer to exercise both pure Ruby code and native C extensions; follow the provided installer, harness patterns, and sanitizer-aware runs to validate Ruby apps or gems for memory safety issues.

RWKV is an RNN+Transformer hybrid architecture with linear-time inference, infinite context, and GPT-style training. It delivers constant-memory, streaming generation on CUDA and CPU, ideal for long-context, memory-constrained deployments.

Orchestrates Sage ERP tasks through Composio’s Sage toolkit via Rube MCP, enforcing tool discovery, connection checks, schema compliance, and structured multi-step execution with remembered sessions.

Automates Screenshot Fyi workflows via the Rube MCP + Composio toolkit by enforcing tool discovery, connection checks, schema-safe execution, memory/session handling, and pagination-aware bulk runs.