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Found 3,730 Skills
Run a structured design critique against the brief and codebase. Checks visual hierarchy, consistency, responsiveness, accessibility, and aesthetic fidelity. Use when user wants a design review, critique, QA pass, polish pass, or mentions "review" after building.
Drives development with tests. Use when implementing any logic, fixing any bug, or changing any behavior. Use when you need to prove that code works, when a bug report arrives, or when you're about to modify existing functionality.
Writing xUnit tests. v3 Fact/Theory, fixtures, parallelism, IAsyncLifetime, v2 compatibility.
XXE playbook. Use when XML, SVG, OOXML, SOAP, or parser-driven imports may resolve external entities, files, or internal network resources.
Network protocol attack playbook. Use when exploiting layer 2/3 protocols including ARP spoofing, LLMNR/NBT-NS/mDNS poisoning, WPAD abuse, DHCPv6 attacks, VLAN hopping, STP manipulation, DNS spoofing, IPv6 attacks, and IDS/IPS evasion.
Reference data for .NET test framework detection patterns, assertion APIs, skip annotations, setup/teardown methods, and common test smell indicators across MSTest, xUnit, NUnit, and TUnit. DO NOT USE directly — loaded by test analysis skills (test-anti-patterns, exp-test-smell-detection, exp-assertion-quality, exp-test-maintainability, exp-test-tagging) when they need framework-specific lookup tables.
Stress-test a plan, design, or architecture through relentless interviewing. Use when user says "grill me", "challenge this", "stress test my design", "review my plan", wants a design interview, or needs to think through decisions before building. Two modes — collaborative interview (default) and devil's advocate.
Run vLLM performance benchmark using synthetic random data to measure throughput, TTFT (Time to First Token), TPOT (Time per Output Token), and other key performance metrics. Use when the user wants to quickly test vLLM serving performance without downloading external datasets.
Create and run orq.ai experiments — compare configurations against datasets using evaluators, analyze results, and generate prioritized action plans. Use when evaluating LLM agents, deployments, conversations, or RAG pipelines end-to-end. Do NOT use without a dataset and evaluators. Do NOT use for cross-framework comparisons with external agents (use compare-agents).
LocalStack integration. Manage data, records, and automate workflows. Use when the user wants to interact with LocalStack data.
Production-grade payment integration for Stripe, Paddle, Adyen, and more. Use when implementing checkout, subscriptions, webhooks, or billing.
TDD: enforce RED-GREEN-REFACTOR, tests before code.