Loading...
Loading...
Found 255 Skills
Automate Acculynx tasks via Rube MCP (Composio). Always search tools first for current schemas.
nginx C module debugging guidelines based on the official nginx development guide. This skill should be used when debugging nginx C module crashes, memory bugs, request flow issues, or production problems. Triggers on tasks involving segfault analysis, coredump debugging, GDB inspection, memory leak detection, request phase tracing, AddressSanitizer setup, or nginx module troubleshooting.
Onnx Converter - Auto-activating skill for ML Deployment. Triggers on: onnx converter, onnx converter Part of the ML Deployment skill category.
nginx C module performance optimization and reliability guidelines based on the official nginx development guide. This skill should be used when optimizing nginx C modules for throughput, latency, memory efficiency, and operational resilience. Triggers on tasks involving buffer optimization, connection tuning, shared memory contention, error recovery, timeout strategy, caching implementation, worker process tuning, or logging performance in nginx C modules.
Nginx Ingress Manager - Auto-activating skill for DevOps Advanced. Triggers on: nginx ingress manager, nginx ingress manager Part of the DevOps Advanced skill category.
nginx C module directive design guidelines for creating admin-friendly configuration interfaces. This skill should be used when designing nginx module directives — deciding what to expose vs hardcode, naming conventions, scope placement, default values, variable design, and validation patterns. Triggers on tasks involving ngx_command_t design, directive naming, configuration API design, nginx module public interface, or directive deprecation.
NGINX integration. Manage data, records, and automate workflows. Use when the user wants to interact with NGINX data.
Save XNXX videos in HD with fast batch downloading
Remap the function_id:pc_index to the original source code position by provided debug info json file.
Implements high-performance local machine learning inference in the browser using ONNX Runtime Web. Use this skill when the user needs privacy-first, low-latency, or offline AI capabilities (e.g., image classification, object detection, or NLP) without server-side processing.
Specializes in analyzing Lynx trace data to diagnose performance issues and provide actionable optimization strategies. Key Scenarios: - Loading Performance: Diagnosing slow startup metrics (FCP, FMP, TTI) and white screen issues. - Smoothness Analysis: Investigating root causes for scroll jank, frame drops, and interaction lag. - Regression Detection: Comparing traces to identify performance degradation or verify optimization gains between versions. - Pipeline Deep Dive: Pinpointing bottlenecks in specific rendering stages like Layout, Paint, JS execution, and background threads. - Native Module Analysis: Investigating performance issues related to native module calls.
Fetch the latest CI pipeline execution for the current branch. Returns the most recent CIPE which may be completed, in progress, or null. Use when you need to review CI status, check failures, or inspect CI state.