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Found 10,460 Skills
Provides guidance for LLM post-training with RL using slime, a Megatron+SGLang framework. Use when training GLM models, implementing custom data generation workflows, or needing tight Megatron-LM integration for RL scaling.
Generate comprehensive documentation for content authors taking over an AEM Edge Delivery Services project. Analyzes the project structure and produces a complete authoring guide with blocks, templates, configurations, and publishing workflows.
Background knowledge for droid-control workflows -- not invoked directly. Agent-browser driver mechanics for web page and Electron desktop app automation.
Use a local QMD knowledge base through UXC over MCP stdio, with daemon-backed session reuse and typed retrieval flows that avoid repeated model warmup and unnecessary query-expansion latency.
Grafana OnCall and Incident Response Management (IRM) — alert routing, escalation chains, on-call schedules, Jinja2 routing templates, Slack/mobile notifications, integrations (Alertmanager, Grafana Alerting, webhooks, PagerDuty), and incident lifecycle management. Use when setting up on-call rotations, configuring escalation policies, routing alerts to the right team, declaring and managing incidents, integrating with Alertmanager or Grafana Alerting, or configuring Slack-based alert workflows.
Guide for creating effective skills. This command should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations. Use when creating new skills, editing existing skills, or verifying skills work before deployment - applies TDD to process documentation by testing with subagents before writing, iterating until bulletproof against rationalization
This skill guides the use of Jupyter notebooks for data analysis, exploration, and visualization, particularly with BigQuery. It outlines best practices for notebook execution and validation (supporting both cell-by-cell execution and full notebook generation depending on tool availability), library installation, and structuring notebooks for clarity. It also covers specific rules for data cleaning, plotting, and integrating with BigQuery SQL and machine learning workflows. Relevant when any of the following conditions are true: 1. The user request involves a data analysis, data exploration, data visualization, or data insights task that requires multiple steps, queries, or visualizations to answer. 2. The user explicitly requests a notebook (.ipynb). 3. You are creating, editing, or executing cells in a Jupyter notebook. 4. You need to query BigQuery from within a notebook. DO NOT use the Python BigQuery client library; instead, you MUST use the `%%bqsql` magics explained in this skill.
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.
Generate self-contained HTML pages and slide decks (diagrams, comparison tables, architecture overviews, diff reviews, visual recaps) by emitting semantic component JSON. Use whenever a visual artifact communicates better than terminal prose — proactively trigger on 4+ row tables, ASCII flowcharts, multi-stage pipelines, or explicit "make a diagram / slides / recap" requests.
Set up CI/CD pipelines for Adobe App Builder projects. Generates GitHub Actions workflows using adobe/aio-cli-setup-action@3 and adobe/aio-apps-action@3.3.0, plus patterns for Azure DevOps and GitLab CI. Handles OAuth S2S secrets injection, multi-workspace promotion (stage → prod), deploy gating with manifest validation. Use this skill whenever the user mentions CI/CD for App Builder, GitHub Actions for aio deploy, automated deployment pipelines, continuous integration, continuous delivery, deploy automation, multi-environment promotion, aio app add ci, or wants to automate their App Builder build and release process. Also trigger when users mention deploy workflows, release pipelines, or GitHub secrets for App Builder.
Test quality review drawing on twelve classic engineering books — with primary focus on xUnit Test Patterns, The Art of Unit Testing, How Google Tests Software, and Working Effectively with Legacy Code — that diagnoses structural problems in an existing test suite: brittleness, mock abuse, coverage illusions, slow execution, poor readability. Triggers when: user asks about test quality, shares test files for review, or expresses frustration: "tests keep breaking whenever I change anything", "our tests take forever", "I can't understand what this test is doing", "tests pass but bugs still reach production", "we have too many mocks". Do NOT trigger for: writing new tests from scratch (use the regular test-writing workflow) or testing framework/syntax questions — this skill reviews an existing suite for structural quality problems, not individual test authoring.
Record transaction flow in accordance with unified rules. Save records by individual stock in Markdown format, and simultaneously write to SQLite for statistics and quantitative review.