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Found 1,312 Skills
Use when writing, refining, or structuring prompts for AI-powered app features — system prompts, user prompt templates, few-shot examples, chain-of-thought, prompt versioning, and defensive prompting
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.
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.
Use when reading from or writing to Neo4j with Apache Spark or Databricks using the Neo4j Connector for Apache Spark (org.neo4j:neo4j-connector-apache-spark). Covers SparkSession setup, DataFrame reads via labels/Cypher/relationship scan, DataFrame writes with SaveMode, node.keys for MERGE, relationship write mapping, partition and batch tuning, PySpark and Scala examples, Databricks cluster config, Databricks secrets for credentials, Delta Lake to Neo4j pipelines. Does NOT handle Cypher authoring — use neo4j-cypher-skill. Does NOT handle the Python bolt driver — use neo4j-driver-python-skill. Does NOT handle GDS algorithms — use neo4j-gds-skill.
Configure and operate the Neo4j Connector for Kafka (sink + source) and the native Neo4j CDC API. Covers Cypher/Pattern/CUD sink strategies, CDC-based and query-based source, exactly-once semantics, DLQ error handling, Confluent Cloud managed connector, schema registry (Avro/JSON), and native db.cdc.query cursor-loop patterns (Neo4j 5.13+ Enterprise/Aura BC/VDC). Use when streaming Kafka events into Neo4j, streaming Neo4j changes to Kafka, or querying Neo4j change events without Kafka. Does NOT handle Cypher query authoring — use neo4j-cypher-skill. Does NOT handle bulk CSV/file import — use neo4j-import-skill. Does NOT handle GDS algorithms — use neo4j-gds-skill.
Guides Validation by Educational Experience (VEE) for North American actuarial credential paths (SOA, CAS)—how VEE fits preliminary requirements, current topic areas (Economics, Accounting & Finance, Mathematical Statistics; subject to society updates), approved-course criteria, candidate workflow and documentation, SOA vs CAS submission timing relative to ASA/ACAS progress, international/transfer considerations, and common pitfalls. Use for VEE, validation by educational experience, VEE credit, actuarial VEE requirements, SOA VEE, CAS VEE, VEE economics, VEE statistics, VEE accounting and finance, college credit for actuarial exams, submit VEE transcript—not deep exam study (pre-actuarial-foundations, advanced-short-term-actuarial-mathematics, advanced-long-term-actuarial-mathematics), workpapers (actuarial-analyst), signing (associate-actuary, appointed-chief-actuary), official transcript qualification rulings, or generic degree planning.
UI/UX design intelligence for web and mobile. Includes 50+ styles, 161 color palettes, 57 font pairings, 161 product types, 99 UX guidelines, and 25 chart types across 10 stacks (React, Next.js, Vue, Svelte, SwiftUI, React Native, Flutter, Tailwind, shadcn/ui, and HTML/CSS). Actions: plan, build, create, design, implement, review, fix, improve, optimize, enhance, refactor, and check UI/UX code. Projects: website, landing page, dashboard, admin panel, e-commerce, SaaS, portfolio, blog, and mobile app. Elements: button, modal, navbar, sidebar, card, table, form, and chart. Styles: glassmorphism, claymorphism, minimalism, brutalism, neumorphism, bento grid, dark mode, responsive, skeuomorphism, and flat design. Topics: color systems, accessibility, animation, layout, typography, font pairing, spacing, interaction states, shadow, and gradient. Integrations: shadcn/ui MCP for component search and examples.
Run Megatron-LM (MLM) and Megatron Bridge training with mock or real data. Covers correlation testing, available recipes, and multi-GPU examples.
Comprehensive geospatial science skill covering remote sensing, GIS, spatial analysis, machine learning for earth observation, and 30+ scientific domains. Supports satellite imagery processing (Sentinel, Landsat, MODIS, SAR, hyperspectral), vector and raster data operations, spatial statistics, point cloud processing, network analysis, cloud-native workflows (STAC, COG, Planetary Computer), and 8 programming languages (Python, R, Julia, JavaScript, C++, Java, Go, Rust) with 500+ code examples. Use for remote sensing workflows, GIS analysis, spatial ML, Earth observation data processing, terrain analysis, hydrological modeling, marine spatial analysis, atmospheric science, and any geospatial computation task.
Discover and run Holoscan Sensor Bridge example applications on a connected devkit. Filters available apps by the user's platform, HSB software version, board type, and sensors. Supports timed execution, failure analysis, code-edit suggestions, and iterative re-runs.
Amazon OpenSearch Service and Serverless across five capabilities — migration (Solr/ES/self-managed OpenSearch into AOS/AOSS, schema/query translation, sizing, cutover); provisioning (domain + AOSS lifecycle, upgrades, storage tiers, FGAC, monitoring); search (vector / semantic / hybrid / RAG with Bedrock connectors); log-analytics (PPL, OSI ingestion, anomaly detection, OpenSearch Dashboards, Splunk/Datadog alternatives); trace-analytics (OTel spans, service maps, Data Prepper). Triggers on OpenSearch, AOS, AOSS, Elasticsearch, ELK, Solr, Lucene, vector / k-NN / semantic / hybrid / neural search, RAG, ELSER, log analytics, observability, Kibana, OSI, OCU, PPL, trace analytics, BM25, eDisMax, schema.xml, ILM, ISM, FAISS, HNSW, Migration Assistant for Amazon OpenSearch Service, Historical Data Migration, Live Traffic Migration, UltraWarm, OR1, Splunk/Datadog alternative, moving off Solr. Picks ONE capability per ask, names instance class + count + shard math, ships query DSL examples.
Delegate a coding task to a separate Claude Code CLI process or another Claude session as an implementer, then review its diff and land it yourself. Use only when the user explicitly asks to delegate implementation to Claude Code, another Claude session, or the `claude` CLI — for example, "have another Claude implement this", "delegate this to Claude Code", or "run this queue through a separate Claude session." Do not trigger merely because the current orchestrator is Claude, and do not use when the user asks the current Claude to implement directly without delegation.