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Found 9,785 Skills
How to read paid media dashboards without fooling yourself. Attribution models, platform reporting quirks, multi-platform reconciliation, ROAS vs LTV horizon traps, statistical noise in performance metrics, incrementality testing, and the failure modes that produce expensive lessons. Triggers on read paid media dashboard, attribution analysis, ROAS vs LTV, multi-platform reconciliation, ad incrementality, geo holdout, conversion lift study, ghost bidding, paid media reporting, board-deck paid media metrics, blended CAC, MMM, MTA, last-click attribution. Also triggers when a marketer is about to scale, kill, or rebudget a campaign based on platform metrics, or when reconciling platform reports against warehouse revenue.
Screen US equities for parabolic exhaustion patterns and generate conditional pre-market short plans, then evaluate intraday trigger fires from live 5-min bars. Phase 1 daily 5-factor scorer (MA extension / acceleration / volume climax / range expansion / liquidity), Phase 2 per-candidate plans for ORL break / first-red 5-min / VWAP fail with explicit borrow / SSR / manual-confirmation gating, Phase 3 one-shot intraday FSM that detects trigger fires and resolves concrete share counts. Covers Phase 1 + Phase 2 + Phase 3.
This skill should be used when the user wants to refactor TypeScript code to functional patterns or write new code following functional doctrine. Common triggers include "make this functional", "remove the class", "use Result instead of throw", "stop mutating this", and "refactor to factory function". Bakes in factory functions over classes, Result<T,E> over exceptions, immutable state via spread/map/filter, and pure functions composed in pipelines. Skip when the user wants general TS hygiene (use ts-best-practices), the class wraps a stateful SDK (PrismaClient, Octokit, WebSocket), or a framework requires a class.
Pull data from a web page. First call on a new intent prototypes the flow via $B primitives and returns JSON. Subsequent calls on a matching intent route to a codified browser-skill and return in ~200ms. Read-only — for mutating flows (form fills, clicks, submissions), use /automate. Use when asked to "scrape", "get data from", "pull", "extract from", or "what's on" a page. (gstack)
Query Allium APIs for wallet PnL (current + historical, by-wallet and by-token), holdings timeseries history, Hyperliquid HyperCore trading data (info, fills, orders, orderbook), and custom SQL analytics across 70+ chains. NOT for token prices, token metadata, current wallet balance snapshots, transaction transfer history, or NFT metadata — for those use `alchemy-cli` (live work), `alchemy-mcp`, `alchemy-api` (app code), or `agentic-gateway` (no API key). Requires Allium credentials at `~/.allium/credentials`.
Pushes live updates to connected WebSocket clients via streams. Use when building real-time dashboards, live feeds, or collaborative features.
Revisar um contrato contra o playbook de negociação da organização — sinalizar desvios, gerar redlines e fornecer análise de impacto de negócios. Use ao revisar acordos com fornecedores ou clientes, ao precisar de análise cláusula por cláusula contra posições padrão, ou ao preparar estratégia de negociação com redlines priorizadas e posições de fallback.
Competitor Blogger Daily Monitoring + One-Click Video Script Parsing — Monitor the latest videos of competitor bloggers (Douyin/Kuaishou/WeChat Channels), AI scores the viral potential; one-click script parsing for selected viral videos (yt-dlp + faster-whisper + DOUBAO multimodal 5 dimensions: shots/lines/visuals/sound/rhythm). Trigger when users say "monitor bloggers", "check competitor bloggers", "what did peers post", "parse this video", "secondary creation script".
Guides actuarial work for insurance and reinsurance—pricing and rate adequacy, reserving and IBNR, loss development and triangles, mortality/morbidity and lapse assumptions, experience studies and credibility, capital and risk metrics at overview level, product design tradeoffs (life, health, P&C, annuity), and regulatory reporting concepts (NAIC, IFRS 17, Solvency II overview—not legal advice). Use when the user mentions actuary, actuarial, IBNR, loss development, reserve analysis, mortality table, pricing insurance, experience study, IFRS 17, loss ratio, combined ratio, credibility, or asks for assumption documentation and model governance for insurance products—not generic FP&A (financial-analyst), investment banking valuation (comps-analysis, dcf-model), legal policy interpretation (commercial-counsel), clinical trials, software-only implementation (senior-software-engineer), or broad GRC without actuarial models (compliance-engineer).
Guides senior front-end software engineering—TypeScript/React/Next.js architecture, component design, client and server rendering, state and data fetching, styling and design systems, accessibility (WCAG), performance (Core Web Vitals), testing, and senior-level UI code review. Use when building or refactoring complex UIs, designing component APIs, optimizing LCP/INP/CLS, implementing accessible interactions, integrating design tokens, or reviewing front-end PRs—not for backend APIs or databases (fullstack-software-engineer, senior-fullstack-developer), design-only critiques without implementation, CI/CD (devops), or cross-service system RFCs (senior-software-engineer). For implementing screens from design specs, component states, and visual QA, use ui-software-engineer. Deep perf investigations and load/RUM analysis: performance-engineer.
Generates a self-contained Python experiment client that uses the ddtrace.llmobs SDK. Emits either a runnable .py script or a Jupyter .ipynb notebook matching the canonical DataDog reference notebook style. Use when the user says "generate Python experiment", "write an SDK experiment", "create a ddtrace experiment", "Python notebook experiment", "use the LLM Obs SDK", or has `ddtrace` installed and wants idiomatic SDK code.
Use when the user has a long-form video (interview / lecture / podcast / conversation) and a transcript SRT, and wants to extract 3–6 stand-alone topical short clips from it. This skill ONLY cuts and crops — it produces raw clips + per-clip SRTs as a hand-off package for downstream post-production (`/wjs-overlaying-video`). Triggers — "切成几段", "分主题", "拆成短视频", "切片", "topic segments", "split into clips".