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Found 13,211 Skills
Implementation guidance for creating individual agents in the Arcanea system with proper structure, capabilities, and integration.
Agent skill for gossip-coordinator - invoke with $agent-gossip-coordinator
Agent skill for collective-intelligence-coordinator - invoke with $agent-collective-intelligence-coordinator
Operates AIR agentic wallets through AIR's `/v2/wallet/agent-sign` HTTP endpoint and ERC-4337 UserOps. Use when an external agent receives an AIR handoff bundle with `userId`, `walletId`, `privyAppId`, `abstractAccountAddress`, and `airApiAgentSignUrl`, and needs to sign messages, typed data, or control the smart account onchain.
Use for Cobo Agentic Wallet operations via the `caw` CLI: wallet onboarding, token transfers (USDC, USDT, ETH, SOL, etc.), smart contract calls, balance queries, and policy denial handling. Covers DeFi execution on EVM (Base, Ethereum, Arbitrum, Optimism, Polygon) and Solana: Uniswap V3 swaps, Aave V3 lending, Jupiter swaps, DCA, grid trading, Polymarket, and Drift perps. Use when: user mentions caw, cobo-agentic-wallet, MPC wallet, TSS node, Cobo Portal, agent wallet, or needs any crypto wallet operation — even without explicit "Cobo" mention. NOT for: fiat payments, bank transfers, or crypto-to-fiat off-ramp.
Agent spawning, lifecycle management, and coordination patterns. Manages 60+ agent types with specialized capabilities. Use when: spawning agents, coordinating multi-agent tasks, managing agent pools. Skip when: single-agent work, no coordination needed.
Create an appropriate git commit from the working tree and session history. Default commit messages are in Japanese unless the repo says otherwise (e.g. AGENTS.md).
Saleor storefront data + UX playbook. Covers GraphQL query design, channel handling, data contracts per surface (PLP/PDP/nav/pricing/availability/media), variant-selection UX, and Saleor-specific correctness rules. Framework-agnostic — agent inspects repo and applies conventions locally.
Execute a single task from a Jira task plan using a structured pipeline of specialist subagents: planning, testing, refactoring, implementation, documentation, code-quality review, architecture review, security audit, and requirements verification. The user must specify which task number to execute. Use when the user says "execute task 3", "work on task 2", "implement task 1", "start task 5 for PROJECT-1234", or "run task N". Also triggered by the orchestrating-jira-workflow skill as Phase 5 of the end-to-end pipeline (called once per task). Requires that the task plan exists at docs/<TICKET_KEY>-tasks.md. Executes ONLY the specified task — never continues to the next one without explicit user approval.
Installs, configures, audits, and operates Agent Package Manager (APM) in repositories. Use when initializing apm.yml, installing or updating packages, validating manifests, managing lockfiles, compiling agent context, browsing MCP servers, setting up runtimes, or packaging resolved context for CI and team distribution. Don't use for writing a single skill by hand, generic package managers like npm or pip, or non-APM agent configuration systems.
Invoke Alibaba Cloud Apsara Data Agent for Analytics via CLI to perform natural language-driven data analysis on enterprise databases. Data Agent for Analytics is an intelligent data analysis agent developed by Alibaba Cloud Database team for enterprise users. It automatically completes requirement analysis, data understanding, analysis insights, and report generation based on natural language descriptions. This tool supports: discovering data resources (instances/databases/tables) managed in DMS, initiating query or deep analysis sessions, real-time progress tracking, and retrieving analysis conclusions and generated reports. Use this Skill when users need to query databases, analyze data trends, generate data reports, ask questions in natural language, or mention "Data Agent", "data analysis", "database query", "SQL analysis", "data insights".
Mandatory protocol for dispatching any built-in and custom agent in this project via the task tool. Use this skill EVERY TIME you are about to call the task tool with a custom agent_type. This skill ensures the agent's intended model (declared in its YAML frontmatter) is respected rather than overridden by a default. Also encodes prompting best practices for subagent context and quality. ALWAYS invoke before any task tool call that targets a custom agent — even if the agent name seems obvious.