Loading...
Loading...
Found 6,714 Skills
Use when writing automation tests, functional tests, or any test in Unreal Engine. Also use when the user asks about "UE_LOG", logging, log categories, assertion, check, ensure, verify, DrawDebug, debug draw, console command, profiling, Unreal Insights, stat commands, or debugging techniques. See ue-module-build-system for test module setup, and ue-cpp-foundations for general C++ logging patterns.
DeepEval evaluation workflow for AI agents and LLM applications. TRIGGER when the user wants to evaluate or improve an AI agent, tool-using workflow, multi-turn chatbot, RAG pipeline, or LLM app; add evals; generate datasets or goldens; use deepeval generate; use deepeval test run; add tracing or @observe; send results to Confident AI; monitor production; run online evals; inspect traces; or iterate on prompts, tools, retrieval, or agent behavior from eval failures. AI agents are the primary use case. Covers Python SDK, pytest eval suites, CLI generation, tracing, Confident AI reporting, and agent-driven improvement loops. DO NOT TRIGGER for unrelated generic pytest, non-AI test setup, or non-DeepEval observability work unless the user asks to compare or migrate to DeepEval.
Workday integration. Manage Organizations, Deals, Leads, Projects, Pipelines, Goals and more. Use when the user wants to interact with Workday data.
Creates and manages isolated cloud sandboxes (secure code execution environments with dedicated runtimes) on the Daytona platform. Use when a task needs an isolated runtime, sandbox, secure compute, or Daytona SDK/API/CLI operations. Covers Python, TypeScript, Go, and Ruby SDKs.
Analyzes unit economics by product or service using PayPal merchant insights and QuickBooks cost data, benchmarks against inflation and cost changes, and shows pricing-scenario data (e.g. "a 5% increase historically correlates with ~3% volume drop"). Surfaces analysis only — does not recommend a price. Use when the user asks about raising prices, pricing, margin analysis, what to charge, whether costs are eating into profit, or how a price change might affect their business. Trigger even if the user doesn't say "margin" explicitly — phrases like "am I making enough?", "should I charge more?", or "my costs are going up" all call for this skill.
Book Teardown. Calm, concise, sharp, and straightforward. Explain five key points clearly: What question is the author answering? What unproven assumptions does the author base their argument on? What framework do they use to analyze the topic? What conclusions do they reach? Finally, a few sentences of God's-eye view compression of the entire book. Use this when the user says '拆书', '拆这本', '分析这本书', '这本书在讲什么', '上帝之眼看这本书', '压缩一本书', 'book', or shares a book name requesting structural analysis. DO NOT use for chapter summaries (use Fabric extract_wisdom), papers (use ljg-paper), deep dives into a single viewpoint (use ljg-think), or ranking within a field (use ljg-rank).
Adversarial robustness engineering for ML/AI—evasion, poisoning, extraction, membership-inference threat models; robust training, sanitization, detectors; ASR/certified evals; lab model attacks; data-pipeline integrity; production I/O guardrails (classical ML and LLM/multimodal). Use for adversarial examples, robustness suites, poison audits, deploy guardrails—not LLM app red team (ai-redteam), governance (ai-risk-governance), safety classifier R&D (ml-research-engineer-safeguards), safeguard serving (ml-infrastructure-engineer-safeguards), privacy research (privacy-research-engineer-safeguards), AppSec pentest (penetration-tester).
[QwenCloud] Manage account auth and query usage/billing. Use for: login, logout, check usage, view billing, free tier quota, coding plan status, pay-as-you-go costs. Skip for: model browsing, non-account tasks.
Translate approved GDDs + architecture into epics — one epic per architectural module. Defines scope, governing ADRs, engine risk, and untraced requirements. Does NOT break into stories — run /create-stories [epic-slug] after each epic is created.
Database performance optimization, schema design, query analysis, and connection management across PostgreSQL, MySQL, MongoDB, and SQLite with ORM integration. Use this skill for queries, indexes, connection pooling, transactions, and database architecture decisions.
Challenge an outbound campaign copy by benchmarking it against the user's existing campaigns — what worked, what didn't, what the winners do differently — and return a concrete verdict plus prioritized fixes. Use whenever the user wants to know if a campaign or sequence is good, compare a draft to past campaigns, audit campaign copy against real performance, pressure-test a sequence before launch, validate a sequence before going live, or asks 'is this campaign as good as my best ones'. Triggers on: 'challenge this campaign', 'benchmark this sequence', 'is this campaign good', 'audit my copy', 'pressure-test before launch', 'compare to my best campaigns', 'should I launch this'. Pulls existing campaign performance from the La Growth Machine MCP when connected; otherwise works from stats and copy the user pastes; falls back to a best-practice baseline when there is no campaign history. For SDR, RevOps, Growth, Head of Sales/Marketing, founders launching outbound. Maintained by La Growth Machine.
Plan and optimize Amazon Sponsored Display campaigns. Covers product targeting, audience targeting, retargeting views and purchases, and creative choices, and matches each tactic to a funnel goal. Use when a user asks about Sponsored Display, SD campaigns, product targeting, audience targeting, retargeting on Amazon, defending a listing, or attacking a competitor ASIN with ads. Trigger phrases: "sponsored display", "SD ads", "display ads", "product targeting", "audience targeting", "retargeting", "competitor targeting". Works with zero tools. the user describes the product and goal.