AI Agent2026
Runs an LLM-driven agent loop that iteratively proposes, applies, tests, and commits small repo changes—each successful iteration becomes a separate git commit while failures are rolled back or preserved for repair. Supports multiple agent backends, worktrees for concurrency, live terminal status, and optional per-iteration pushes.
AI Client2026
Compresses LLM/agent replies into a terse “caveman” style to cut output tokens (~65–75%) while preserving technical accuracy. Offers per-agent skills, intensity modes, memory-compression and middleware to lower token cost and extend usable context.
AI Agent2026
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).
AI Agent2026
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.
AI Dataset2026
Provides 7,823 single-turn reasoning conversations generated by Anthropic's Claude Opus 4.7 and reformatted into Qwen-style chat templates for supervised fine-tuning (SFT). Includes explicit <think> chain-of-thought blocks and many long reasoning chains (avg ~4k tokens).
AI Dataset2026
Contains 8,124 reasoning conversations (extended-thinking + final responses) generated by Anthropic Claude Opus 4.7 for distillation into open-source LLMs. Each row stores the prompt, thinking trace, final answer and usage metadata; packaged under Apache‑2.0.
AI Dataset2026
Synthetic JSON dataset of model-generated prompts and step-by-step reasoning traces (≈90k rows, ~75M tokens) created with Claude Sonnet 4.6 and cross-checked by Gemini 3.1 Pro — intended for training or fine-tuning LLMs on natural reasoning, multi-domain code/math, and instruction following. Hosted on Hugging Face, MIT license.
AI Dataset2026
Provides 2,405 chain-of-thought reasoning traces generated by Claude Opus 4.7 for hard math, science, and formal problems. Each record pairs a problem with the model's full <think> working and a polished answer; available as parquet splits for non-commercial research under Anthropic's usage policy.
AI Video2026
Enables Claude to “watch” videos by extracting timestamped frames plus captions/transcripts and feeding them to Claude for grounded Q&A. Key features: native captions first, Whisper fallback, frame deduplication, and multiple detail modes (transcript/efficient/balanced/token-burner). Useful for summarizing, debugging, and extracting moments.
AI Dataset2026
Cleaned dataset of reasoning-distillation examples derived from Claude Opus 4.7 outputs — 4,807 retained JSON chat rows after removing simulated-thinking, duplicates, and missing fields. Packaged for model distillation and reasoning evaluation; Apache-2.0 packaging with upstream Anthropic usage constraints.
AI Agent2026
Performs agent-driven security scans of codebases using LLM coding agents to find and triage vulnerabilities. Combines fast regex discovery, per-file AI investigation and revalidation, with optional sandboxed parallel execution and Vercel AI Gateway integration for large monorepos.
AI Dataset2026
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.