AI Client2026
Lightweight cross-platform database client that exposes configured database connections to AI coding agents via an MCP server and includes a built-in AI SQL assistant. Ships as a single ~15MB binary, supports 60+ databases, and runs on desktop or Docker.
AI Model2026
An uncensored, fine-tuned and GGUF-quantized variant of Qwen3.6-27B tailored for long-context, coding, vision and creative-writing use. Offers multiple NEO-CODE Di-Matrix quants (IQ2/IQ4/Q6/Q8), mmproj vision support and recommended inference settings for local servers.
AI Dataset2026
Early-preview (≈1.2k rows) dataset of agentic coding prompts and unedited model responses generated by DeepSeek‑V4‑Pro, covering real-world programming tasks across many languages. Intended for research, filtering, and model evaluation rather than production training without review.
AI Model2026
DavidAU/Qwen3.6-40B-Claude-4.6-Opus-Deckard-Heretic-Uncensored-Thinking-NEO-CODE-Di-IMatrix-MAX-GGUF
A 40B GGUF-quantized Qwen3.6 variant fine-tuned with Claude 4.6 Opus and Deckard/Heretic datasets for multimodal image-text-to-text tasks. Offers 256K context, custom NEO-CODE Di-IMatrix quants for long conversations and coding, optimized for local inference and creative/coding use cases; safety alignment removed.
AI Coding2026
Explains AI coding jargon in plain English, giving concrete engineering meanings for terms like context window, tool call, and attention degradation. Structured as a browsable dictionary with pragmatic examples and guidance for developers building LLM-driven systems.
AI Dataset2026
Collects ML Intern coding-agent session traces as Claude‑Code‑style JSONL event streams for viewing with the Hugging Face Agent Trace Viewer. Each file is one session (messages, tool calls, outputs, timestamps); automated scrubbing is applied but no comprehensive human redaction—treat as potentially sensitive.
AI Model2026
Mixture-of-Experts LLM tuned for mathematical and coding reasoning, with ~760M active / 8.4B total parameters and post-training for improved stepwise reasoning. Optimized for inference efficiency (vLLM/transformers forks) so it can run in computation-constrained or local deployments; Apache-2.0 licensed.
AI Dataset2026
Agentic coding evaluation dataset containing real-world, multi-step developer tasks and raw model responses across 20+ programming languages. Emphasizes challenging, persona-driven prompts for benchmarking and fine-tuning; users should filter and audit outputs before training.
AI Coding2026
Parses local AI coding-assistant session logs and presents a privacy-first dashboard that surfaces practice scores, anti-patterns, code-output metrics, skill discovery, and context-health checks. Runs as a VS Code extension or a GitHub Copilot canvas; requires building/installing the VSIX.
AI Agent2026
Runs coding and long-running research workflows inside a persistent IPython environment with programmatic subagents and a durable 'Continual Harness' for session-level refinements. Key features include recursive subagents (RLM), executable Python skills, background daemon sessions, and evidence-backed local refinements. Best for reproducible, long-horizon coding, experiments, and evaluation pipelines where auditable agent-driven updates matter.
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.