Provides a reliability layer for self-hosted LLM tool-calling and multi-step agent workflows. Adds guardrails — rescue parsing, response validation, retry nudges, and a synthetic respond tool — and ships a Drop-in OpenAI-compatible proxy plus a WorkflowRunner for structured loops.
Browser-based visual editor and learning hub for RDF/OWL ontologies (targeted at Microsoft Fabric IQ): interactive graph exploration, a searchable catalogue, an embeddable viewer, RDF/XML import/export, and a natural-language→ontology preview — all as a zero-backend static site.
Optimizes websites for AI-first search by providing GEO-focused SEO audits: citation-readiness scoring, AI-crawler access checks, schema generation, platform-specific recommendations, and client-ready PDF reports — delivered as a Claude Code skill with CLI commands.
Desktop-first personal agent that compresses your connected accounts into a local memory tree and runs agentic workflows. Key features include 118+ one‑click integrations, TokenJuice token compression into an Obsidian‑style vault, model routing with optional local models (Ollama).
Provides portable agent 'skills' that steer code-generating agents toward higher-quality UI: stronger layout, typography, spacing and image-reference boards. Ships adjustable dials for design variance, motion and density and image→code pipelines for agent-led frontends.
Desktop app that orchestrates teams of AI agents: agents autonomously create, assign, and complete tasks while messaging and reviewing each other on a Kanban board. Includes local/no-auth models, provider runtime auto-detection, per-task logs, and hunk-level code review.
Provides named agents, reusable skills, and MCP data connectors for common financial‑services workflows (investment banking, equity research, private equity, wealth). Available as Claude Cowork plugins or deployable Claude Managed Agents templates—designed as enterprise-ready templates, not turnkey investment advice.
One-command installer that gives AI agents the ability to read and search the web and social platforms (web pages, Twitter/X, Reddit, YouTube, GitHub, Bilibili, XiaohongShu) by installing and wiring upstream CLIs and MCP connectors while keeping credentials local.
Provides a deployable personal AI assistant that runs locally or in the cloud, supports multi-channel chat, extensible Skills/Plugins, and local-model runtimes. Key features include three-layer memory, kernel-level sandboxing and tool/file guards, and bundled QwenPaw-Flash local models for zero-API deployments.
Converts scene intent into production-ready Seedance 2.0 prompts, reference-role mappings, and IP-safe rewrites for multimodal (text/image/audio/video) video generation. Ships as a modular agent-skill OS with multilingual examples, troubleshooting tools, and pro filmmaker handoff artifacts.
Provides a set of task-focused agent “skills” — small folders of instructions that teach agents how to perform common Flutter development workflows (integration tests, widget previews, routing, localization). Maintained by the Flutter team to reduce mistakes and make repeatable dev tasks reliable.