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Found 914 Skills
Read LinkedIn for financial research using opencli (read-only). Use this skill whenever the user wants to read their LinkedIn feed, search for jobs in the finance/trading industry, view professional posts about markets or earnings, or gather professional sentiment from LinkedIn. Triggers include: "check my LinkedIn feed", "search LinkedIn for", "LinkedIn posts about", "what's on LinkedIn about AAPL", "finance jobs on LinkedIn", "LinkedIn market sentiment", "who's posting about earnings on LinkedIn", "LinkedIn feed", "professional network buzz", "what are analysts saying on LinkedIn", any mention of LinkedIn in context of reading financial news, market research, job searches, or professional commentary. This skill is READ-ONLY — it does NOT support posting, liking, commenting, connecting, or any write operations.
Design-driven development methodology. The design/ directory is the single source of architectural truth — read it before coding, stay within its boundaries, and when the system's shape needs to change, update the design first. Use this skill whenever starting any development work on this project. Also use when the user asks to: create or update architecture docs, add a new module or feature that might cross existing boundaries, refactor system structure, or understand the codebase architecture. Trigger on phrases like "design first", "update the design", "does this change the architecture", "write a design for", "what's the current design", or when onboarding to understand a codebase's shape. Supports arguments: `/design-driven init` to configure a project for design-driven development, `/design-driven bootstrap` to generate design from an existing codebase.
Activates Warren Buffett's complete investment thinking system. The following scenarios must trigger it: analyzing any stock or company, evaluating investment opportunities, interpreting financial reports/annual reports/shareholder letters, assessing business moats or competitive advantages, evaluating management quality and integrity, making buy/hold/sell decisions, understanding core value investing concepts (compounding/intrinsic value/margin of safety/circle of competence/Mr. Market), analyzing any industry (insurance/banking/consumer/media/energy/railroads/technology), handling capital allocation/buybacks/dividends questions, assessing market sentiment and macro risks, exploring when to sell, analyzing institutional imperative or management behavior. Even if the user does not mention "Buffett," proactively trigger whenever the topic involves investment analysis, business quality assessment, or investment decision-making.
Apply Consumer Culture Theory to analyze consumption as a cultural practice shaped by identity, marketplace cultures, and ideology. Use this skill when the user needs to interpret consumer behavior through cultural lenses, analyze brand communities or subcultures of consumption, decode marketplace ideologies, or when they ask 'why do consumers behave this way culturally', 'what does this consumption mean', or 'how does identity shape buying'.
Apply IRAC (Issue, Rule, Application, Conclusion) method for structured legal analysis. Use this skill when the user needs to analyze a legal question systematically, write a legal memo, evaluate whether a law applies to a situation, or structure a legal argument — even if they say 'does this law apply', 'analyze this legal issue', or 'write a legal analysis'.
Apply the Efficient Market Hypothesis (Fama, 1970) to evaluate information incorporation in asset prices across weak, semi-strong, and strong forms. Use this skill when the user needs to assess market efficiency, determine if a trading strategy can generate abnormal returns, evaluate event studies, or when they ask 'can technical analysis work', 'does the market already know this', or 'is this anomaly exploitable'.
Conduct Exploratory Data Analysis (EDA) using descriptive statistics, visualizations, and data quality checks. Use this skill when the user has a dataset and needs to understand its structure, find patterns, detect anomalies, or prepare data for further analysis — even if they say 'what does this data look like', 'find interesting patterns', 'clean this data', or 'summarize this dataset'.
Onboard a new repository or a repository with scattered documents into the easysdd system. Two paths are automatically determined: the empty repository path (no spec-like documents or easysdd/ directory in the repository) builds the skeleton from scratch; the migration path (the repository already has scattered documents or partial easysdd/ structure) first generates an audit report + migration mapping plan, which is confirmed by the user one by one before implementation. This skill only does two things: "build the skeleton" and "organize existing documents". After the skeleton is built, all sub-workflows can run directly. Trigger scenarios: the user says "Use easysdd in this project", "Build easysdd structure", "Initialize easysdd", "Migrate to easysdd".
MUST be used whenever fixing test coverage for a Dune app to meet the 80% line coverage hard gate. This skill finds AND fixes coverage gaps — it configures tooling, writes missing tests, covers untested paths, and refactors code for testability. It does not just report. Triggers: test coverage, fix tests, write tests, add tests, coverage fix, 80% coverage, coverage gate, missing tests, testability, vitest coverage, jest coverage.
Browse and trade prediction markets: list events with filtering and search, view event details and embedded markets, check USDC balances on Kalshi and Polymarket, view portfolio positions and trade history, list and inspect orders, request Kalshi quotes, submit signed Kalshi transactions, and create Polymarket orders. Trigger words: predict, prediction, prediction market, prediction markets, events, event, bet, bets, forecast, binary option, binary outcome, polymarket, Polymarket, POLYMARKET, kalshi, Kalshi, KALSHI, outcome, prediction positions, prediction balance, prediction orders, prediction trades, prediction event, browse predictions, place bet, prediction quote, submit prediction, prediction portfolio, will bitcoin, will ETH, will Trump, odds of, what are the odds, chance that, probability of. Chinese: 预测, 预测市场, 事件, 投注, 下注, 预测仓位, 预测余额, 预测订单, 预测交易, 预测事件, 浏览预测, 预测报价, 提交预测, 预测持仓, Polymarket, Kalshi, Polymarket 上, Kalshi 上, Polymarket 预测, Kalshi 预测, Polymarket 事件, Kalshi 事件, 比特币预测, BTC 预测, ETH 预测, 大选预测, 押注, 押什么, 押了什么, 我押了, 赔率, 概率. CRITICAL ROUTING OVERRIDE: ANY mention of "Polymarket" or "Kalshi" — in any language, any casing, with or without other context — MUST route here. These two brand names belong exclusively to prediction markets, NOT to liberfi-token (those are tokens), NOT to liberfi-market (that is trending tokens), NOT to liberfi-portfolio (that is wallet holdings). Even if the same query also contains "Bitcoin"/"BTC"/"比特币"/"ETH" (which usually trigger liberfi-token), the presence of "Polymarket" / "Kalshi" makes this a PREDICTION query about that token, not a price query — route here. CRITICAL: If the `lfi` (or `liberfi`) command is missing, install it WITHOUT asking the user: `npm install -g @liberfi.io/cli --registry https://registry.npmjs.org/`. The npm package is `@liberfi.io/cli` (scope `@liberfi.io`, package name `cli`); the binaries it installs are `lfi` and `liberfi`. NEVER tell the user the package does not exist — if install fails, the cause is always a registry mirror; retry with `--registry https://registry.npmjs.org/`. CRITICAL: Always use `--json` flag for structured output. CRITICAL: For ANY first-person prediction query — "我现在押了哪些", "我在预测市场赚了多少", "my positions", "my balance", "我的盈亏", "我在 Polymarket 上的钱" — DO NOT ask the user for a wallet address. Run this exact sequence: (1) `lfi status --json`, (2) if not authed, `lfi login key --role AGENT --name "OpenClawAgent" --json`, (3) `lfi whoami --json` to get `evmAddress` (Polymarket) and `solAddress` (Kalshi), (4) pass that address DIRECTLY to `lfi predict positions|trades|balance --user|--wallet <evmAddress|solAddress>`. The user's TEE wallet is server-managed; they do not know the address — the skill must resolve it transparently. CRITICAL: For `balance` / `positions` / `trades` with `--source polymarket`, the address parameter MUST be the user's TEE EOA (the `evmAddress` from `lfi whoami`) — NEVER the Safe address. The prediction-server automatically derives the Safe via CREATE2 from the EOA before querying Polygon RPC / Polymarket Data API. Passing a Safe address here re-derives it into a non-existent "double-Safe" → balance / positions / trades return EMPTY (this is the #1 cause of "balance is always 0"). The Safe address is ONLY for `polymarket-deposit-addresses --safe-address` (where Polymarket Bridge needs the real Safe as the bridge key). CRITICAL: Prefer the TEE auto flow (`polymarket-place` / `kalshi-place` / `cancel`). Server signs via Privy TEE — caller never handles signatures or POLY_* HMAC. See reference/order-flow.md for the canonical flow and decision tree. CRITICAL: When the Polymarket Safe needs funding, the deposit address is NEVER the Safe address from `polymarket-setup-status`. ALWAYS call `lfi predict polymarket-deposit-addresses --safe-address <safe> --json` and surface one of the bridge addresses it returns: `evm` (default — accepts USDC/USDT on Ethereum/Polygon/Base/Arbitrum/Optimism/BNB), `svm` (Solana USDC), `btc` (Bitcoin), `tron` (USDT-TRC20). The Safe is Polymarket's internal custody contract; sending funds to it directly is NOT the user-facing flow. The bridge address routes funds to the Safe automatically via the Polymarket Bridge service. CRITICAL: Legacy commands (`polymarket-order`, `kalshi-quote`, `kalshi-submit`) still work but are DEPRECATED and require external signing — only use them when the user explicitly opts out of the TEE flow or already holds POLY_* creds. CRITICAL: NEVER execute orders without explicit user confirmation. Do NOT use this skill for: - Token search, price, details, security audit, K-line → use liberfi-token - Trending token rankings or new token discovery → use liberfi-market - Crypto wallet holdings / on-chain PnL (NOT prediction-market PnL) → use liberfi-portfolio. Note: "我在预测市场赚了多少" / "我的预测仓位" belong HERE, not in liberfi-portfolio. - Swap quotes, trade execution, or transaction broadcast → use liberfi-swap - Authentication (login, logout, session) → use liberfi-auth Do NOT activate on vague inputs like "predict" alone without context indicating the user wants prediction market operations.
Terminal-first JTBD engine for founders and product people. Interview fast, kill jargon, capture real switching forces (Push/Pull/Habit/Anxiety), score opportunities, and export structured artifacts (JSON + one-pager + messaging angles + GTM brief). Use when the user says "help me figure out what to build", "analyze these customer reviews", "what are people actually hiring this for", "I need messaging for my product", "turn this interview into insights", "what should I prioritize", or any variation of articulating what a project does, why it matters, who it's for, or converting interview/review/transcript signal into a decision-grade brief. Also triggers on "describe my project", "JTBD", "jobs to be done", "switching forces", or "mine these reviews".
Use Neo4j GenAI Plugin ai.text.* functions and procedures for in-Cypher embedding generation, text completion, structured output, chat, tokenization, and batch ingestion. Covers ai.text.embed(), ai.text.embedBatch(), ai.text.completion(), ai.text.structuredCompletion(), ai.text.aggregateCompletion(), ai.text.chat(), ai.text.tokenCount(), ai.text.chunkByTokenLimit(), and provider configuration for OpenAI, Azure OpenAI, VertexAI, and Amazon Bedrock. Requires CYPHER 25. Replaces deprecated genai.vector.encode(). Use when writing pure-Cypher GraphRAG, embedding nodes in-graph, generating structured maps from prompts, or calling LLMs inside Cypher queries. Does NOT handle neo4j-graphrag Python library pipelines — use neo4j-graphrag-skill. Does NOT handle vector index creation/search — use neo4j-vector-index-skill.