A curated collection of production-ready Agent Skills that turn tasks—presentation production, image generation, local KB retrieval, article assembly, and web-design—into agent-loadable skill folders. Uses a SKILL.md contract, supports multiple agent runtimes (Claude Code, Cursor, Codex), and offers modular install paths with pinned release zips.
Drop-in Jinja chat templates for Qwen 3.5/3.6 that fix rendering errors, token waste, and tool-calling failures across runtimes (LM Studio, llama.cpp, vLLM, MLX). Adds a think-on/think-off toggle, auto-closes broken thinking tags, robust tool-argument handling, and a graceful fallback for missing user queries.
Supervised fine-tuning dataset of 7,716 reasoning-focused Q&A examples distilled from the DeepSeek‑V4‑Flash teacher; provided as a cleaned JSONL train split for distillation and SFT experiments.
Turns 530+ GPT-Image2 examples into a structured 'Prompt-as-Code' library and style skill for reproducible image-generation workflows; includes a browsable gallery, 20+ industrial templates, and an agent-ready style skill for automation.
Generates page-scale UI designs and audits for Claude Code, Cursor, and Codex using a 57-gate “anti-AI-slop” rule set — produces distinct, non-template HTML+CSS outputs and supports audit, redesign, and study verbs with a built-in pre-emit self-critique.
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.
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.
Instruction‑tuning dataset of 8,706 Claude Opus 4.6/4.7–generated examples where each assistant turn begins with a synthetic <think> block to emulate chain‑of‑thought. Provided as four splits (full/instruct/roleplay/code), ~17M tokens total, Apache‑2.0, not manually reviewed.
Structured, downloadable JSONL dataset of Seedance 2.0 video-generation prompts with matching MP4 previews and cover images; includes English/Chinese texts and standardized metadata (duration, resolution, safety) and is released under CC BY 4.0 for reuse.
A prompt-only mixture of ~478k prompts designed to support antidoom-style generation and preference-data pipelines for reducing model repetition (doom loops). Prompts are stripped of answers and labels and sourced from many public datasets so it’s usable for FTPO/adapter generation but not for supervised QA evaluation.
Provides 19,331 multi-turn ChatML Hermes reasoning traces produced by DeepSeek V4 Pro for LoRA fine-tuning of agent-style models; includes VRAM-tiered variants, train/valid/test splits, and dense tool-calling annotations in Parquet format.
Provides 19,331 multi-turn ChatML Hermes reasoning traces for LoRA fine-tuning of local models to behave as Hermes agents. Includes train/valid/test splits, VRAM-tiered variants (nano→spark), ~138K tool-call annotations, and Parquet format under Apache-2.0.