Loading...
Loading...
Found 13,634 Skills
Protocolo de Inteligência Pré-Tarefa — ativa TODOS os agentes relevantes do ecossistema ANTES de executar qualquer tarefa solicitada pelo usuário. Enriquece o contexto com análise paralela...
Load top-performing Shinka programs into agent context using `shinka.utils.load_programs_to_df`, and emit a compact Markdown bundle for iteration planning.
Multi-agent management workflow — task delegation, progress monitoring, quality verification with regression testing, feedback delivery, and cross-review orchestration. Use this skill when coordinating multiple agents on a shared task, monitoring delegated work, ensuring quality across agent outputs, or implementing a multi-phase plan (3+ phases or 10+ file changes).
Real-time sports & events data for AI agents via Shipp. Use when the user wants live scores, schedules, or game events for NBA, NFL, NCAA Football, MLB, or Soccer — especially to power prediction market trading strategies on Polymarket or Kalshi using a MoonPay wallet.
Documentation reference for writing Python code using the browser-use open-source library. Use this skill whenever the user needs help with Agent, Browser, or Tools configuration, is writing code that imports from browser_use, asks about @sandbox deployment, supported LLM models, Actor API, custom tools, lifecycle hooks, MCP server setup, or monitoring/observability with Laminar or OpenLIT. Also trigger for questions about browser-use installation, prompting strategies, or sensitive data handling. Do NOT use this for Cloud API/SDK usage or pricing — use the cloud skill instead. Do NOT use this for directly automating a browser via CLI commands — use the browser-use skill instead.
Interactive guide to repository workflow system: agents, skills, routing, and execution patterns. Use when user asks how the system works, what commands are available, or how to use brainstorm/plan/execute phases. Use for "how does this work", "what can you do", "explain workflow", "help me understand", or "show me the process". Do NOT use for actually executing workflows (use workflow-orchestrator) or debugging (use systematic-debugging).
Operate `superise market-sustain` for SupeRISE Market self-supervision. Use when the user asks the agent to keep itself alive, monitor balance or runway, inspect market pricing, top up a market account, retry pending top-up orders, clear market auth state, or change sustain guardrails and config.
Multi-agent swarm coordination for complex tasks. Uses hierarchical topology with specialized agents to break down and execute complex work across multiple files and modules. Use when: 3+ files need changes, new feature implementation, cross-module refactoring, API changes with tests, security-related changes, performance optimization across codebase, database schema changes. Skip when: single file edits, simple bug fixes (1-2 lines), documentation updates, configuration changes, quick exploration.
Overview The Messari Tracker Agent serves as a direct bridge to Messari’s institutional-grade data sources, allowing users to extract BTC and ETH data without manual searching or fragmented data sourc
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".
Sharpen, refine, and optimize AI agent skills through real usage — learn from mistakes, review quality, and improve over time. Observes skill execution in the current conversation, analyzes three sources (conversation history, file diffs, user feedback), and proposes concrete improvements to the target skill's SKILL.md. Works with Claude Code and any SKILL.md-based agent framework. Use after executing any skill: `/skill-sharpen [name]` for a specific skill, or `/skill-sharpen` to auto-detect the last used. Three modes: interactive (propose one by one), observe-only (dump to LESSONS.md), review (process pending lessons).
Use this skill to prevent destructive operations when working on production systems or running agents autonomously.