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Found 737 Skills
Issue Workflow Stage 1 — Convert the user's problem into a reproducible, traceable {slug}-report.md through conversation. The AI only asks "what you saw, how to reproduce it, what should happen" here, and does not guess the root cause for the user (that's Stage 2's responsibility). Meanwhile, this stage is the only official decision point for choosing between the fast track and standard path: Based on the user's description, first review the relevant code; if the root cause can be identified at a glance and the required changes are minor, directly inform the user to take the fast track. Trigger scenarios: The user says "file an issue", "record this bug", "I found a problem". This is the starting point of the issue workflow with no pre-dependencies.
One-stop skill for the project architecture center — draft new architecture documents, refresh existing ones, or conduct an architecture health check. Automatically determine the mode based on user input: `new` (draft)/ `update` (refresh to latest code status)/ `check` (review without modification, generate issue list). The `check` mode has three sub-objectives: consistency within a single feature design, alignment between design and code, and consistency among multiple documents under `codestable/architecture/`. Single-target rule — only modify one document or check one target at a time. Trigger scenarios: User says "fill in an architecture doc", "draft an architecture document", "refresh the architecture directory", "write down this module structure", "conduct an architecture check", "is the design internally consistent?", "does the plan match the code?", "are there conflicts among several documents in the architecture folder?", or when an architecture action is required before proceeding during the feature-design / feature-acceptance / implement phases.
freeCodeCamp's "Command-line Chic" UI design system and aesthetic guidelines. Apply these rules whenever building, styling, or reviewing any UI that should look and feel like a freeCodeCamp product — web apps, dashboards, landing pages, admin tools, component libraries, or themes. Use this skill when the user mentions freeCodeCamp styling, fCC design, "Command-line Chic", dark theme development for fCC, or asks for a UI that follows freeCodeCamp's visual identity. Also use when working on any freeCodeCamp repository, contributing to freeCodeCamp projects, or building tools and dashboards for freeCodeCamp staff, even if the user doesn't explicitly mention the design system.
Deeply analyze junk files on Drive C, provide intelligent deletion suggestions and migration solutions. It runs in read-only mode and does not modify any files. This skill is triggered when users ask about insufficient Drive C space, want to clean up junk, free up disk space, or move certain data out of Drive C.
Peter Thiel's Monopoly Creation framework applied to a business idea. Spawns a team of specialist agents — Monopoly Anatomist, Secret Hunter, Market Framer, Last Mover Analyst, Girardian — who each apply a distinct lens from Thiel's framework to evaluate whether a venture has genuine monopoly potential. The lead synthesizes into a verdict: does this company have a secret, a 10x advantage, a tiny domination-ready market, and a path to becoming the last mover in its category? Use when the user says "thiel this", "monopoly test", "zero to one analysis", "does this have monopoly potential", or proposes a venture and wants Thiel-style evaluation. Works standalone or after /office-hours and /munger.
Conduct legal research and risk analysis using GoodLegal MCP tools. Use this skill whenever the user asks a legal question, wants to research case law or legislation, needs a legal risk assessment, or asks about French or EU law. Trigger on any mention of jurisprudence, legal research, contract risk, regulatory analysis, legal memo, or references to GoodLegal tools — even if the user just says something like "can you look into whether this clause is enforceable" or "what does the case law say about X".
Build modern data apps, dashboards, and interactive reports using either React + Vite or Streamlit. Includes optional Gemini Data Analytics chat integration for an AI powered "chat with your data" experience. Relevant when any of the following conditions are true: 1. User explicitly requests to build a data dashboard, data application, or visualization UI, and the UI pulls data from a GCP database (defaulting to BigQuery unless otherwise specified). 2. You need to generate a frontend web application to interact with, query, and visualize data from GCP data sources. 3. User wants to build a "chat with your data" experience or integrate the Gemini Data Analytics chat API into a web interface. Do NOT use when any of the following conditions are true: 1. The request is for building backend-only services. 2. The request is for simple CLI scripts or command-line applications. 3. The web application is not data-centric or does not involve visualizing/querying data from GCP sources.
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 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.
Create and manage Neo4j vector indexes, run vector similarity search (ANN/kNN), store embeddings on nodes or relationships, use SEARCH clause (Neo4j 2026.01+, preferred) or db.index.vector.queryNodes() procedure (deprecated 2026.04, still works on 2025.x), configure HNSW and quantization options, pick similarity function and embedding provider dimensions, and batch-update embeddings. Use when tasks involve CREATE VECTOR INDEX, vector.dimensions, cosine/euclidean search, embedding ingestion pipelines, or semantic nearest-neighbor lookup. Does NOT handle GraphRAG retrieval_query graph traversal — use neo4j-graphrag-skill. Does NOT handle fulltext/keyword indexes (FULLTEXT INDEX, db.index.fulltext) — use neo4j-cypher-skill. Does NOT handle GDS graph embeddings (FastRP, Node2Vec) — use neo4j-gds-skill.
Design, review, and refactor Neo4j graph data models. Use when choosing node labels vs relationship types vs properties, migrating relational/document schemas to graph, detecting anti-patterns (generic labels, supernodes, missing constraints), designing intermediate nodes for n-ary relationships, enforcing schema with constraints and indexes, or assessing an existing model against graph modeling best practices. Does NOT handle Cypher query authoring — use neo4j-cypher-skill. Does NOT handle Spring Data Neo4j entity mapping — use neo4j-spring-data-skill. Does NOT handle GraphQL type definitions — use neo4j-graphql-skill. Does NOT handle data import — use neo4j-import-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.