AI Coding2026
Applies an "ADHD-friendly" output style to coding assistants so answers lead with the next action, present numbered steps, and avoid burying results. Packaged as a reusable skill/plugin for coding-agent workflows (examples: Claude Code, Codex) and guided by a 10-rule style set.
AI Agent2026
Routes code-based AI agents through repeatable reverse-engineering and pentesting workflows and orchestrates local and remote tools (jadx, Frida, IDA, BurpSuite) so agents can triage APKs, binaries, JS, firmware, and CTFs without guessing the toolchain. Includes master routing rules, tool-index detection, MCP integration, and a field-journal for reusable lessons.
AI Agent2026
An A‑share–specialized fork of TradingAgents that runs a seven‑analyst multi‑agent investment research pipeline for China stocks, integrating free A‑share data connectors and LLM providers. Key features: mootdx/東財 data integrations, A‑share trading rules (T+1, limits), Streamlit UI, and Apache‑2.0 license.
AI Dataset2026
Pairs natural-language instructions with executable setup artifacts and Python reward functions to create verifiable computer-use agent tasks. Provides a Parquet task table for fast filtering plus a compressed archive of runnable task bundles; several web task endpoints are placeholders that require a local CUA-Gym-Hub deployment.
AI Dataset2026
25,000 chat-formatted synthetic SFT examples distilled to emulate the reasoning style and agentic behavior of Anthropic's Claude Mythos, focused on cybersecurity, advanced coding, mathematical reasoning, and long-horizon agent tasks. Includes metadata for targeted curriculum fine-tuning and is Apache-2.0 licensed.
AI Model2026
A trillion-parameter reasoning model aimed at long-horizon, multi-step agent workflows and tool collaboration. Offers adjustable Reasoning Effort modes (high, xhigh), async RL training (IcePop), and very long context (128K→256K) for complex production scenarios.
AI Model2026
Multimodal 35B scientific foundation model for image+text-to-text reasoning and conversational workflows. Uses task-scaling and full-chain training (pretraining → RL) to boost domain scientific abilities while keeping general multimodal reasoning and agent skills.
AI Model2026
A GGUF-format 9B model derived from Qwen3.5, fine-tuned for agentic coding, tool-calling, reasoning and vision-capable multimodal prompts. Optimized for local 8‑bit inference on 16GB-class machines; community experimental release for research use.
AI Dataset2026
Provides 40 public Kubernetes incident scenarios (SRE subset) with ground-truth root-cause entities and offline cluster snapshots in JSONL format; designed to evaluate agentic root-cause diagnosis on alerts, events, traces and topology.
AI Model2026
Reasoning-enhanced 27B dense LLM fine-tuned from Qwen3.6-27B and released in GGUF format for image-text-to-text and long-context reasoning. Augmented with Trace Inversion reconstructed chains, three-stage SFT curriculum and MTP/vision support; community research release.
AI Image2026
Node-based infinite-canvas web workstation for iterative visual creation — integrates image/video generation, reference editing, prompt library, multi-agent assistants, and asset management. Runs in-browser with configurable OpenAI-compatible endpoints; suited for local/personal deployment (AGPL-3.0).
AI Agent2026
Runs shared, self-hosted AI agents in isolated Kubernetes sandboxes accessible from Slack or an API. Provides durable workflows, reusable tool plugins, and network-edge credential injection (iron-proxy) so agents can execute real work securely and audibly for teams.