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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.
Use when OpenSpec artifacts have been generated by /opsx:propose and need review before implementation begins — validates proposal scope, spec completeness, design decisions, and task executability
AIMarket Financial Capability Discoverer. Trigger this skill to list available platform capabilities and provide installation commands when users ask questions related to financial data/analysis/tools and the AI is unsure which specific skill to use.
Estimate the ATS score of a resume file (DOCX or text). Returns per-category scores (parsability, headings, quantification, verb variety, active voice, vague filler, length) and a weighted overall 0-100. Triggers on: score my resume, ATS score, how good is my resume, rate my resume, /resume score.
Decode benchmark videos, contact sheets, frames, or rough ideas into reusable prompt structure. Use this when you need to extract hook essence, viewer question, must-copy visual grammar, and forbidden drift before writing storyboard or generation prompts.
Detects and prevents code injection attacks targeting serverless functions (AWS Lambda, Azure Functions, Google Cloud Functions) through event source poisoning, malicious layer injection, runtime command execution, and IAM privilege escalation via function modification. The analyst combines static analysis of function code, CloudTrail event correlation, runtime behavior monitoring, and IAM policy auditing to identify injection vectors across the expanded serverless attack surface including API Gateway, S3, SQS, DynamoDB Streams, and CloudWatch event triggers. Activates for requests involving Lambda security assessment, serverless injection detection, function event poisoning analysis, or serverless privilege escalation investigation.
You are **Infrastructure Maintainer**, an expert infrastructure specialist who ensures system reliability, performance, and security across all technical operations. You specialize in cloud archite...
Find dead code and cleanup candidates such as unused exports, unreachable branches, orphaned files, stale feature flags, dead registrations, and compatibility layers with no live callers. Use when auditing refactors, bundle-size cleanup, architecture simplification, pre-release cleanup, reviewing requests to find unused code or decide what can be deleted, or when deciding whether code can be safely removed or auto-fixed.
Resolves experiment references from natural language to concrete experiment IDs. Handles name lookups, fuzzy descriptions ('the signup experiment', 'my latest experiment'), status filtering, and disambiguation when multiple experiments match. TRIGGER when: user refers to an experiment by name, description, or relative reference ('latest', 'most recent', 'the one I created yesterday') and you don't already have the experiment ID. DO NOT TRIGGER when: user provides an experiment ID directly, or you already resolved the experiment earlier in the conversation.
macOS menu bar app that identifies USB-C cable capabilities and charging diagnostics using IOKit
Scan project dependencies for known vulnerabilities and CVEs
Use when assessing AI/ML systems for prompt injection, jailbreak vulnerabilities, model inversion risk, data poisoning exposure, or agent tool abuse. Covers MITRE ATLAS technique mapping, injection signature detection, and adversarial robustness scoring.