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Found 411 Skills
Use this skill for ANY task involving jj or jujutsu version control. ALWAYS trigger when the user mentions jj, jujutsu, revsets, change IDs, bookmarks, or oplog. Also trigger when the user wants to squash, split, or reorder commits in a stack, write a revset query, absorb fixup changes, undo or restore a previous operation, resolve conflicts after rebasing, recover from force-pushes, rewrite protected/immutable commits, view change evolution (evolog), or try parallel approaches. Trigger even if "jj" is not explicitly said — "changes" instead of "commits", "stack" instead of "branch", "absorb", "squash into the right commit", "undo my last operation", "conflict after rebase", or "compare approaches in parallel" are strong jj signals. This skill contains critical non-obvious rules (like always using -m flags) that prevent broken workflows.
Multi-framework frontend development. Frameworks: React 18+ (Suspense, hooks, TanStack), Vue 3 (Composition API, Pinia, Nuxt), Svelte 5 (Runes, SvelteKit), Angular (Signals, standalone). Common: TypeScript, state management, routing, data fetching, performance optimization, component patterns. Actions: create, build, implement, style, optimize, refactor components/pages/features. Keywords: React, Vue, Svelte, Angular, component, TypeScript, hooks, Composition API, runes, signals, useSuspenseQuery, Pinia, stores, state management, routing, lazy loading, Suspense, performance, bundle size, code splitting, reactivity, props, events. Use when: creating components in any framework, building pages, fetching data, implementing routing, state management, optimizing performance, organizing frontend code, choosing between frameworks.
Spawn a single autonomous AI agent with a specific task, personality, and CLI backend (Claude, Gemini, OpenCode, Copilot). Agent accepts task from docs/todo/pending/, selects personality based on task type, and works autonomously with CLI tools. Integrates with docs-first workflow via task signals and progress tracking.
What are crypto funds and VCs holding right now? Cross-chain fund portfolios and net accumulation signals.
Detect buying signals across TAM companies and watchlist personas. Three-phase architecture: (1) free diff-based signals from existing data (headcount growth, tech stack changes, funding rounds), (2) Apify-powered signals (job postings, LinkedIn content analysis, profile changes), and (3) post-processing with dedup, scoring, and lead status updates. Writes signals to Supabase signals table for downstream activation.
Enrich contacts and companies with verified emails, phones, and firmographic data. Also covers CRM data hygiene, deduplication, and bulk enrichment. Use when enriching leads, finding email addresses, cleaning CRM data, doing bulk enrichment, optimizing enrichment credits, setting up auto-enrichment, or fixing stale contact data. Do NOT use for building new prospect lists from scratch (use /sales-prospect-list), interpreting buying signals (use /sales-intent), or general Apollo platform help (use /sales-apollo).
Diagnose why a listing is losing the Amazon Buy Box (Featured Offer) and build a plan to win it back. Covers seller-health signals, pricing relative to the competing offer, fulfillment method, stock, and account metrics. Use when a user asks why they lost the Buy Box, how to win the Featured Offer, why a reseller is beating them, or why their own listing shows another seller's offer. Trigger phrases: "buy box", "featured offer", "lost the buy box", "win the buy box", "buy box percentage", "another seller has my listing". Works with zero tools. the user describes the offer and account state.
Backtest crypto and traditional trading strategies against historical data. Calculates performance metrics (Sharpe, Sortino, max drawdown), generates equity curves, and optimizes strategy parameters. Use when user wants to test a trading strategy, validate signals, or compare approaches. Trigger with phrases like "backtest strategy", "test trading strategy", "historical performance", "simulate trades", "optimize parameters", or "validate signals".
Healthcare Enterprise Funding Monitoring System. Real-time monitoring of industrial and commercial changes of healthcare enterprises, identification of funding signals, and automatic alert pushing. Supports data collection from Tianyancha/Qichacha, AI funding judgment, and multi-channel pushing.
Design a product-led sales motion from usage signals to sales handoff and conversion.
Quick backtest a strategy on a symbol. Creates a complete .py script with data fetch, signals, backtest, stats, and plots.
Summarize a customer interview transcript into a structured template with JTBD, satisfaction signals, and action items. Use when processing interview recordings or transcripts, synthesizing discovery interviews, or creating interview summaries.