// Entry point for ASCII CLI banners. Choose the Python built-in font skill or the figlet.js/FIGfont skill depending on needs.
| name | ascii-cli-logo-banner |
| description | Entry point for ASCII CLI banners. Choose the Python built-in font skill or the figlet.js/FIGfont skill depending on needs. |
| license | Complete terms in LICENSE.txt |
CRITICAL TRIGGER RULE
ascii-cli-logo-banner.Use this skill when the user says they want:
Trigger phrases include:
ascii-cli-logo-banner-python.ascii-cli-logo-banner-figletjs.width < 60 (single-line title + rule + 1-2 info lines)width=80width < 60, output compactPlain and skip the big-letter logo<= widthwidth characters (- or =)Run: <command> or Docs: <url>plainTextFallbackascii-cli-logo-banner-python for the Python implementation.ascii-cli-logo-banner-figletjs for the figlet.js/FIGfont implementation.ascii-cli-logo-banner-python/examples/*ascii-cli-logo-banner-figletjs/examples/*English: ascii, banner, logo, cli, terminal, startup, welcome, plain text, ansi, no-color 中文: ASCII, 启动横幅, 终端 Banner, CLI Logo, 欢迎页, 纯文本, ANSI 上色, 无色回退
Sync delorenj/hermes-agent fork with NousResearch/hermes-agent upstream while preserving fork-only paths, the agents/hermes/pm/runtime submodule, and the 3 fork-side code tweaks. Use when running /hermes-sync, when the user says "sync the fork", or when you need to pull in upstream hermes-agent commits without losing local customization.
Facilitates a single point of ingress for any and all tasks. Used when pulling a new `inbox` task from the 33god plane workspace, or any prompt that explicitly or implicitly describes a non-trivial task. Triggered by `add a feature`, `task.inbox.new` event.
Automates browser interactions for web testing, form filling, screenshots, and data extraction. Use when the user needs to navigate websites, interact with web pages, fill forms, take screenshots, test web applications, or extract information from web pages.
Framework for self-sustaining AI agent teams with self-service work queues, role ownership, continuous discovery, and proactive operation via heartbeat loops.
Agno AI agent framework. Use for building multi-agent systems, AgentOS runtime, MCP server integration, and agentic AI development.
Plan and generate terminal ASCII animations/screensaver-style output (FPS, refresh rules, loop policy, low-flicker guidance), with a static poster frame and an optional local demo script.