A curated collection of Korea-focused AI agent skills that enable agents to perform local tasks — ticket booking, public-data lookups, e-commerce and messaging integrations — via prebuilt connectors and an optional hosted proxy for API keys and fallbacks.
Bridges an LLM assistant to your locally running TradingView Desktop via Chrome DevTools Protocol for AI-assisted chart analysis, Pine Script development, and UI automation. Key features: Claude Code MCP integration, a JSON/CLI 'tv' toolset, local-only operation and streamable chart data.
Integrates Codex into Claude Code so you can run read-only code reviews, steerable adversarial reviews, and delegate long-running tasks to a local Codex instance via slash commands. Uses the local Codex CLI/app server and Node.js; designed for developers who want seamless handoff between Claude Code and Codex.
Provides reusable 'Agent Skills'—modular skill packages for integrating Gemini, Managed Agents, and Google Cloud services into installable agent components. Focuses on ready-made connectors and recipes for common Google product workflows, speeding up building and extending agents on Google's Agent Platform.
Runs and manages persistent teams of coding agents (Claude Code, Codex, Pi) locally — boots named seats from a YAML topology and provides a daemon, CLI and TUI to monitor, snapshot, evolve and coordinate agent workspaces and terminals.
Provides a native desktop interface to install, configure, and chat with Hermes Agent—handling local or remote backends, provider setup, sessions, memory, and tools. Ships a guided installer, streaming SSE chat UI with token tracking, persona/profile management, messaging gateways, and cron scheduling.
Provides a cloud-backed shared memory and skill-propagation layer for coding agents: captures session traces, mines recurring patterns into reusable SKILL.md, and shares capabilities across agents in real time. Features hybrid semantic+lexical search, BYOC storage, and a VFS for traces — built for team workflows and agent orchestration.
Compresses LLM/agent replies into a terse “caveman” style to cut output tokens (~65–75%) while preserving technical accuracy. Offers per-agent skills, intensity modes, memory-compression and middleware to lower token cost and extend usable context.
Automates scanning and evaluating job listings with LLM-driven agents, then generates ATS-optimized, per-role PDFs and a unified tracker. Supports batch processing and terminal-first workflows with structured A–F scoring and portal scanners.
Provides fully local long-term and symbolic short-term memory for AI agents via a 4-tier layered pipeline and Mermaid canvases, with zero external API dependencies. Key features: lossless drill-down from personas to raw traces, hybrid retrieval, and ready integrations for OpenClaw and Hermes.
A local-first web and desktop dashboard for Hermes Agent that runs multi-agent LLM chats, manages profiles/providers/models, schedules automated jobs, and connects platform channels (Telegram/Discord/Slack/etc.) with built-in TTS, file browser, and usage analytics.
A local-first web and desktop dashboard for Hermes Agent that runs streamed agent chats, manages profiles/providers/models/credentials, schedules cron jobs, and inspects files and terminals across local, Docker, SSH and Singularity backends.