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Found 1,463 Skills
Interactive workflow for creating, configuring, connecting, and publishing AI agents on Agents.Hot using the agent-mesh CLI. Also covers CLI command reference, flags, skill publishing, and troubleshooting. Trigger words: create agent, manage agent, publish agent, agent description, agent setup, list agents, delete agent, connect agent, agent-mesh command, CLI help, agent-mesh flags, connect options, agent-mesh troubleshooting, TUI dashboard, publish skill, skill init, skill pack, skill version, skills list, unpublish skill, install skill, update skill, remove skill, installed skills.
Browser automation CLI for AI agents - create, test, and deploy web automations
Learn how to manage conversation context in AMCP to avoid LLM API errors from exceeding context windows. This skill covers SmartCompactor strategies, token estimation, configuration, and best practices.
Operate long-lived agent workloads with observability, security boundaries, and lifecycle management.
Semantic search skill for retrieving code and documentation from the ChromaDB vector store. Use when you need concept-based search across the repository (Phase 2 of the 3-phase search protocol). V2 includes L4/L5 retrieval constraints.
Build and deploy agentic finance applications on the Alva platform. Access 250+ financial data sources (crypto, equities, macro, on-chain, social), run cloud-side analytics, backtest trading strategies, and release interactive playbooks -- all from your AI agents.
Headless browser automation CLI for AI agents using native Rust binary with Chrome DevTools Protocol
Implementation guidance for creating individual agents in the Arcanea system with proper structure, capabilities, and integration.
A valid skill that uses $ARGUMENTS placeholder
Delegate tasks to AI agents via Box0. Use when the user asks to review code, check security, run tests, compare tools, get multiple perspectives, research a topic, analyze data, write docs, or any task that could benefit from specialized or parallel execution. Also use when the user mentions agent names or says "ask", "delegate", "get opinions from", or "have someone".
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.
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.