Loading...
Loading...
Found 16 Skills
Quét biên giới agent-framework 30 ngày qua và đối chiếu overstack theo 8 trục (frontier-gap-scan runbook) — gọi INSTANT, không phải cron. Chạy 5 WebSearch, chấm Ngang/Chớm/Thua, diff kỳ trước, raise-issue cho gap mới / cập nhật gap đã có, cập nhật report. Trigger: 'frontier scan', 'quét đối thủ', 'scout tuần', 'chúng ta thua gì', '/frontier-scan'.
Python port of Claude Code agent harness — tools, commands, task orchestration, and CLI entrypoint via oh-my-codex
Transform Claude Code into a fully autonomous agent system with persistent memory, scheduled operations, computer use, and task queuing. Replaces standalone agent frameworks (Hermes, AutoGPT) by leveraging Claude Code's native crons, dispatch, MCP tools, and memory. Use when the user wants continuous autonomous operation, scheduled tasks, or a self-directing agent loop.
Comprehensive guide for building production-grade LLM applications using LangChain's chains, agents, memory systems, RAG patterns, and advanced orchestration
Connect an AI agent to Handlebar governance platform
Multi-agent adversarial verification with convergence loop. Two independent review agents must both pass before output ships.
Conducts investigative-grade research with primary source analysis, cross-verification, and trial-level depth. Use when an album needs factual research, source material, or verification of claims.
Look up VoltAgent documentation embedded in node_modules/@voltagent/core/docs for version-matched docs. Use for API signatures, guides, and examples.
Utiliza esta habilidad cuando el usuario quiera crear, modificar o analizar una nueva "Skill" (habilidad) para Antigravity. Proporciona instrucciones sobre estructura de carpetas, YAML y Markdown.
Use this skill when you learn one or more design pattern(s) in the Langroid (multi) agent framework, and want to make a note for future reference for yourself. Use this either autonomously, or when asked by the user to record a new pattern.
Build a project-local Kitaru adapter for an unsupported Python or TypeScript agent framework. Use when a user wants to record or replay framework-native agent runs in Kitaru, needs a custom adapter, has no supported Kitaru integration for their framework, or needs to assess whether public framework hooks and the installed Kitaru SDK can support an adapter.
Builds LLM applications with LangChain including chains, agents, memory, tools, and RAG pipelines. Use when users request "LangChain setup", "LLM chain", "AI workflow", "conversational AI", or "RAG pipeline".