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Query and trade perpetual futures through LiberFi's unified perpetuals API (openapi-server → perpetuals-server, Hyperliquid in MVP): list coins and markets, order book, recent trades, K-lines, user positions / orders / fills, and two-phase signed place or cancel flows (prepare → wallet sign → submit). Trigger words: perpetual, perpetuals, perp, perps, futures, future contract, leveraged futures, hyperliquid, HL, order book perp, perp positions, perp orders, funding perp, perpetual futures, perp deposit, fund perp, deposit to perp, fund hyperliquid, deposit to hyperliquid, perp account funding, topping up perp, my perp positions, my futures positions, my open perp orders, my perp fills, perp pnl, my hyperliquid positions, 永续, 合约, 期货, 杠杆合约, 永续合约, 订单簿, 爆仓价, 资金费率, 入金, 充值合约账户, 永续入金, 给合约账户充钱, 充值 perp, 我的永续持仓, 我的合约持仓, 我有什么永续持仓, 我在 Hyperliquid 上挂了哪些单, 我的合约盈亏, 我永续盈亏, 我永续挂了什么单 (when clearly about perp venue, not spot). 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 perpetuals query about positions, open orders, or fill history — "我有什么永续持仓", "我的合约持仓", "我在 Hyperliquid 上挂了哪些单", "my perp positions", "my open futures orders", "我永续盈亏", "show my fills" — 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`, (4) pass that address DIRECTLY as the positional argument to `lfi perpetuals positions|orders|fills <evmAddress> --json`. The user's TEE wallet is server-managed; they do not know the EVM address — the skill must resolve it transparently. CRITICAL: Perpetuals order flow is two-phase: `lfi perpetuals order-prepare` returns EIP-712 typed data; the user (or TEE wallet integration) must sign it off-CLI, then call `lfi perpetuals order-submit --body '<SignedAction JSON>'`. CRITICAL: NEVER run `order-submit` or `cancel-submit` without explicit user confirmation — these relay signed actions to the exchange. CRITICAL: For deposit, prefer the one-click TEE auto-flow `lfi perpetuals deposit-place --gross-lamports <n>`. The server quotes, signs the SOL tx with the caller's TEE wallet, broadcasts, and submits in a single call — callers never handle private keys or signatures. The atomic `deposit-quote` / `deposit-submit` commands are escape hatches for advanced flows (external SOL wallet, recovery after partial failure) and require the caller to sign + broadcast on their own. See [reference/deposit-flow.md](reference/deposit-flow.md). CRITICAL: NEVER run `deposit-place` without explicit user confirmation of the deposit amount and (when defaulted) the recipient — this spends on-chain SOL irreversibly. Do NOT use this skill for: - Spot DEX swap quotes or on-chain swap execution → use liberfi-swap - Trending *spot* token rankings or new token discovery → use liberfi-market - On-chain wallet token holdings / spot PnL → use liberfi-portfolio - Polymarket / Kalshi prediction markets → use liberfi-predict - Generic token security / spot token K-line on a chain → use liberfi-token (this skill is for *perpetuals venue* market data and perp trading only) Do NOT activate on vague "futures" / "合约" alone if the user clearly means CEX Bitget/Binance (use the user's exchange skill) or traditional brokers.
Construct and run GFQL graph queries in PyGraphistry using chain-list syntax OR Cypher strings. Covers pattern matching, hop constraints, predicates, let/DAG bindings, GRAPH constructors, and remote execution. Use when requests involve subgraph extraction, path-style matching, Cypher queries, or GPU/remote graph query workflows.
Build PyGraphistry visualizations with bindings, encodings, layout controls, static export, and privacy-aware sharing. Use for color/size/icon/badge styling, layout tuning, map/static output, and plot link sharing workflows.
[Hyper] Use when working on TanStack Start projects and the task involves auth, sessions, cookies, CSRF, secrets, env exposure, server functions/routes, headers/CSP, webhooks, or security review/fixes. Triggers on protecting routes, hardening auth flows, preventing secret leaks, securing server boundaries, or reviewing HTTP/security behavior in a TanStack Start app.
Use this skill when building, debugging, or answering questions about Liveblocks. Liveblocks gives you the building blocks and infrastructure to enable people and AI to work together inside your app, powering realtime collaboration. Liveblocks features include collaboration, rooms, organizations, workspaces, comments, composer, threads, notifications, multiplayer, conflict resolution, realtime presence, avatar stacks, AI collaborators, AI agents, text editors, Tiptap, BlockNote, Lexical, React Flow, Chat SDK. Common components include AiChat, Thread, InboxNotification, Composer, Toolbar (for Lexical Tiptap), FloatingToolbar, FloatingComposer, FloatingThreads, AnchoredThreads. Common hooks include useThreads, useStorage, useMutation, useOthers, useInboxNotifications, useAiChats. Common issues are related to authentication (ID tokens vs access tokens), permissions, room limits, connection errors, user info.
Map, analyze, and redesign the systems behind product experiences. Part of the Intent design strategy system. Creates service blueprints, ecosystem maps, process architecture, and dependency diagrams. Understands how services, teams, tools, and data flows connect to produce (or fail to produce) user outcomes. Proposes structural changes to how products and services are organized. Trigger on: service blueprints, system maps, process architecture, actor/role mapping, dependency analysis, cross-functional workflows, operational design, "how does this system work?", "what breaks when X happens?", "map out the service", "where are the dependencies?", or any question about the structural machinery behind a product experience. Use this skill broadly — whenever someone needs to understand or redesign how a system works, not just what a user sees.
Use when user requests diagrams, flowcharts, architecture charts, or visualizations. Also use proactively when explaining systems with 3+ components, complex data flows, or relationships that benefit from visual representation. Generates .excalidraw files and exports to PNG/SVG via Kroki API or locally using excalidraw-brute-export-cli.
Implement the Syncfusion React Toolbar component to create responsive command bars and action toolbars. This skill covers organizing buttons, separators, and input components with various overflow handling modes. Use this when building rich text editors, document editors, or command-driven interfaces in React applications.
Full three-statement financials (IS / BS / CF) for listed companies via Longbridge — income statement, balance sheet, cash flow statement; annual / semi-annual / quarterly periods. Use this skill to fetch raw financial data. For deep analysis (DuPont, accruals, fraud flags) use longbridge-financial-analysis; for health scoring use longbridge-financial-checkup. Triggers: "财务报表", "三张表", "利润表", "资产负债表", "现金流量表", "三表模型", "季报", "年报", "财报数据", "財務報表", "三張表", "利潤表", "資產負債表", "現金流量表", "三表模型", "季報", "年報", "財報數據", "financial statements", "income statement", "balance sheet", "cash flow statement", "three financial statements", "annual report data", "quarterly financials", "TSLA.US financials", "700.HK balance sheet".
Choose and create the right Neon branch type for testing and development. Use when users ask about Neon branching, migration testing with real data, isolated test environments, schema-only branch workflows for sensitive data, or branch creation via Neon CLI or Neon MCP. Triggers include "Neon branch", "test migrations safely", "branch production data", "schema-only branch", "reset branch" and "sensitive data testing".
Extract a validated learning from the current session, store it in the central agent learnings file, and sync the resulting Learnings section into the agent definitions used by the supported CLIs. User-only maintenance workflow for durable agent guidance.
Search and recall relevant memories from past sessions via memsearch. Use when the user's question could benefit from historical context, past decisions, debugging notes, previous conversations, or project knowledge -- especially questions like 'what did I decide about X', 'why did we do Y', or 'have I seen this before'. Also use when you see `[memsearch] Memory available` hints injected via SessionStart or UserPromptSubmit. Typical flow: search for 3-5 chunks, expand the most relevant, optionally deep-drill into original transcripts via the anchor format. Skip when the question is purely about current code state (use Read/Grep), ephemeral (today's task only), or the user has explicitly asked to ignore memory.