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.
An AI-agent value-investing research framework for Claude Code/Codex that encodes Buffett/Munger/Duan Yongping/Lilu methodologies into multi-agent skills — enforces decisive buy/sell outputs, multi-source financial rigor, and reproducible research workflows for investment decision-making.
Provides a CLI and skill suite that lets coding assistants scaffold, evaluate, and deploy ADK-based AI agents on Google Cloud. Integrates eval pipelines (generate/grade), deployment infra and CI/CD scaffolds, observability, and Gemini Enterprise publishing workflows.
Defines a machine-readable text format that pairs YAML design tokens with human-readable rationale so coding agents can generate, lint, diff, and export UI systems. Bundles a CLI for validating DESIGN.md files and exporting tokens to Tailwind and W3C-compatible formats.
Provides a local-first web-intelligence layer for AI agents: search, fetch, crawl, extract, cache, find-similar and agent-style research without API keys or per-query billing, running as an MCP server, REST daemon, or SDK.
Connects coding agents to local reverse‑engineering tools so an agent can inspect binaries, apps, and websites and return traced code, evidence, and reconstruction workflows. Supports native (Ghidra/Hopper/IDA), JavaScript/Electron, .NET, APKs, firmware and network captures via an MCP server and CLI.
Turns plain-English system or process descriptions into polished, themeable architecture, workflow, sequence, data-flow and lifecycle diagrams as a self-contained HTML file, with one-click theme toggle, copy-to-clipboard and export to PNG/JPEG/WebP/SVG (native up-to-4× rasterization).
Browser-based agent workspace and sandboxed app platform that lets organizations run AI agents to perform tasks and build shareable 'Gadgets'. Uses Gatekeepers for fine-grained, zero-trust access control and runs on Cloudflare Workers with multi-LLM support.
Turns books, long videos, and podcasts into executable, testable AI agent skills using a structured RIA‑TV++ pipeline. Produces multi-file skill packs (BOOK_OVERVIEW.md, SKILL.md, INDEX.md, DIGEST.md), applies triple verification and pressure tests, and can install skills into Claude Code/Cursor for agent use.
Generates editorial-quality diagrams as self-contained HTML files with inline SVG across 27 visual types; includes brand onboarding, agent-skill integrations (Claude Code, Codex, Pi), draw.io/Mermaid import, and static-first output with optional accessible motion.
Connects an LLM to a real browser over an editable CDP websocket so the agent can drive clicks, navigation, and generate missing helper code during tasks. The harness self-heals by writing reusable helpers, supports local or cloud browsers, and can optionally record sessions for debugging.
Orchestrates multiple LLM-backed agents locally using tmux and per-role git worktrees, converting role prompts into coordinated development workflows. Key features: configurable two-/four-/six-pack workflows, a durable handoff protocol, per-role backend selection and observable terminals.