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Found 1,427 Skills
Guide users to manage Alibaba Cloud resources using the Aliyun CLI command-line tool. Covers CLI installation, credential configuration, plugin management, command construction, and error troubleshooting. Use this skill when the user wants to operate Alibaba Cloud services from the terminal — including ECS (云服务器, cloud servers), Function Compute (函数计算, serverless), RDS (云数据库, databases), OSS (对象存储, object storage), SLS (日志服务, log service), VPC (专有网络, networking), ESS (弹性伸缩, auto scaling), and any other Alibaba Cloud product. Also use when the user mentions "aliyun", "阿里云", "阿里云CLI", "命令行", asks about CLI plugin installation, encounters Aliyun CLI errors (InvalidAccessKeyId, SignatureDoesNotMatch, Throttling), or needs help constructing aliyun commands with correct parameter syntax.
Strategic sales leadership guidance for B2B SaaS and enterprise software companies. Covers sales strategy, team building, pipeline management, enterprise selling, discovery calls, demos, proposals, negotiations, and sales operations. Use when building sales teams, designing sales processes, improving win rates, or scaling revenue operations. Use for "sales strategy", "sales process", "pipeline review", "deal strategy", "sales hiring", "quota planning".
Extract business domain knowledge from a codebase and generate an interactive domain flow graph. Works standalone (lightweight scan) or derives from an existing /understand knowledge graph.
codeck entry point. Scans local files for materials, shows pipeline dashboard with diagnostic intelligence, guides user to the next step. Use when the user says "codeck", "new deck", "make a presentation", "make a deck", "new slides", "build a presentation", or wants to start a new presentation project from scratch. Do NOT trigger for specific sub-tasks like designing, reviewing, exporting, or writing speeches — those have dedicated skills.
Use this skill when users want live on-chain market data: token prices, price charts (K-line, OHLC), trade history, swap activity. Also, it covers on-chain signals — smart money, whale, and KOL wallet activity, large trades, and signal-supported chains. For meme tokens: scanning new launches, checking dev wallets, developer reputation, rug pull detection, rug pull history, tokens by same creator, detecting bundles or snipers, bonding curves %, flagging suspicious launches, and meme token safety checks. For token search, market cap, liquidity, trending tokens, or holder distribution, use opentrade-token instead.
Manage the full lifecycle of Alibaba Cloud EMR Serverless StarRocks instances — create, scale, configure, maintain and diagnose. Use this Skill when operations engineers, SREs, or architects need to manage StarRocks instances. Typical scenarios include: "create a StarRocks", "check instance status", "scale up CU", "modify configuration", "restart instance", "diagnose issues", etc. Not applicable for: writing SQL/DDL, data import/export, query tuning, materialized view configuration, or managing non-StarRocks products (EMR clusters, Spark, Milvus, ClickHouse, Doris, RDS, ECS).
Step-by-step playbook for developing a NocoBase plugin, covering scaffolding, server-side code (collections, APIs, ACL, migrations), client-side code (blocks, fields, actions, settings pages, routes, components), i18n, and verification. TRIGGER when: user asks to create, build, implement, or develop a NocoBase plugin, mentions 'NocoBase plugin', or describes a feature to be built as a NocoBase plugin. This skill contains NocoBase-specific conventions and templates that general coding cannot replicate — always invoke it instead of planning from scratch.
Draft or update architecture documents under `easysdd/architecture/` — describe what a subsystem/module looks like currently, how it is divided, and how external interfaces operate, to provide pre-positioning input for subsequent feature-design. Information sources include code + user materials (oral accounts, scattered documents, compound deposits, existing decisions), and the output can be reverse-validated by anchoring to specific `file:line`. Two modes: new (draft a new architecture document from scratch), update (refresh an existing document based on the latest code status and new user materials). Single-target rule — only modify one document at a time. Trigger scenarios: user says "fill in an architecture doc", "draft an architecture document", "update the architecture directory", "write down the structure of this module", or when it is found that "something that should be in the architecture is missing" during the feature-design / feature-acceptance phase.
Find Kalshi prediction markets on DFlow that match a criterion — arbitrage (YES+NO<$1), cheap long-shots, near-certain short-dated plays, biggest movers, widest spreads, highest volume, closing soonest, and series/event-level scans. Use when the user asks "where's the free money?", "any mispriced markets?", "cheap YES with volume", "what moved today?", "markets closing soon", "cheapest YES in this event", "top markets by volume", or "alert me when X happens" (streaming). Do NOT use to place orders (use `dflow-kalshi-trading`), to view a user's own positions (use `dflow-kalshi-portfolio`), or for general live-data plumbing unrelated to a scan (use `dflow-kalshi-market-data`).
The root entry of the CodeStable workflow family — introduces the overall system to users and routes users' specific requests to the correct cs-* sub-skills. Trigger scenarios: users only input `cs` / `/cs`, say "introduce codestable", "do something with codestable", "I want to do X, which skill should I use", "don't know which one to use", or users' described requests are open-ended (e.g., "start working") and haven't converged to a specific sub-skill. This skill itself **does not perform actual tasks** — it doesn't write specs, write code, or read/write content products in the codestable/ directory — it only performs scanning, routing, prompting, and then transfers control to the target sub-skill.
World-class ML engineering skill for productionizing ML models, MLOps, and building scalable ML systems. Expertise in PyTorch, TensorFlow, model deployment, feature stores, model monitoring, and ML infrastructure. Includes LLM integration, fine-tuning, RAG systems, and agentic AI. Use when deploying ML models, building ML platforms, implementing MLOps, or integrating LLMs into production systems.
Strategic product leadership toolkit for Head of Product including OKR cascade generation, market analysis, vision setting, and team scaling. Use for strategic planning, goal alignment, competitive analysis, and organizational design.