Skill UI

An open-source tool based on the CIS Docker Benchmark. It systematically audits critical security aspects of Docker deployments, including host configuration, daemon settings, and container runtime. It generates a detailed compliance report (pass/fail/warn) to ensure best practices and security compliance in production environments.

Perform comprehensive security assessments for Google Cloud Platform environments. This tool audits critical security components—including IAM policies, firewall rules, and storage permissions—against industry benchmarks like the CIS GCP Foundations Benchmark. It helps organizations establish secure baselines and ensure continuous compliance across multiple GCP projects.

A comprehensive security auditing tool designed to assess a Kubernetes cluster's compliance posture against established CIS benchmarks. It performs deep checks on control plane components (API Server, etcd, Controller Manager), worker nodes, and Role-Based Access Control (RBAC). Use it for proactive security assessments, compliance validation, and hardening throughout the CI/CD lifecycle.

Evaluates pitch decks slide by slide, benchmarking against the 11-slide VC template, scoring every section, flagging common killer patterns, and benchmarking versus famous decks for actionable fundraising feedback.

Run NVIDIA Cosmos Policy evaluations on LIBERO and RoboCasa simulations, enabling headless EGL GPU rendering, inference profiling, and benchmark workflows via public eval entrypoints.

Executes a structured VC valuation workflow that ingests SaaS or startup metrics, runs DCF, comparable revenue multiples, and SaaS health models via Python, and synthesizes a defensible valuation, runway, and capital-efficiency narrative for users planning fundraising or benchmarking.

Guides fine-tuning and evaluation of OpenVLA-OFT/OFT+ for robot action generation, covering LoRA adaptation, continuous action heads, FiLM conditioning, and LIBERO/ALOHA benchmarks plus deployment considerations.

A comprehensive 7-stage workflow designed to manage, audit, and optimize GitHub repositories. This tool automates critical tasks including identifying hardcoded secrets, cleaning up junk files, performing deep documentation reviews, benchmarking against competitors, and validating the final state, transforming messy codebases into production-ready assets.

A comprehensive tool for establishing performance baselines across multiple dimensions. It measures Core Web Vitals (LCP, CLS, INP), API latency (p50, p95, p99), and development build efficiency. Essential for detecting performance regressions before merging code, ensuring stability in CI/CD pipelines, and comparing alternative stack implementations.

This skill is designed for performing local, on-premise evaluations and benchmarking of models hosted on the Hugging Face Hub. It facilitates running specialized evaluation frameworks like `inspect-ai` and `lighteval` against local hardware. Users can select optimal inference backends, including `vllm` for high throughput, or fall back to Hugging Face Transformers or `accelerate`, ensuring comprehensive smoke testing and task selection for LLMs. It focuses purely on the local execution process, separate from remote jobs or publishing workflows.

A comprehensive skill for measuring Go application performance. It guides developers through the entire measurement workflow: writing benchmarks, running tests, profiling hot paths with pprof, statistically comparing results, and detecting regressions in CI. This ensures all performance improvements are measurable, robust, and documented.

A comprehensive guide for optimizing Go code performance, covering techniques such as allocation reduction, CPU efficiency, memory layout, GC tuning, and hot-path optimization. It emphasizes profiling first, following an iterative benchmark cycle, and distinguishing between internal code bottlenecks and external I/O latency.