Every quote is checked
A model can misquote someone, so a script looks up every quote in the transcript it came from. In the benchmark it found 158 of 160 cited quotes word for word. The two it missed were video titles.
Does it beat plain Claude?
On 40 questions over two wikis, a blind judge compared each wwxd answer with an answer from plain Claude. The judge came from another lab, Google, and had no access to the transcripts. It preferred wwxd on 34 of 40. Judges from three more labs, Anthropic among them, scored the same pairs and preferred wwxd at least as often. Claude with web search did no better: the judge from Google again preferred wwxd on 34 of 40.
On 24 opinion questions, a prompt that told the model to answer as the person contradicted that person 8 times. The wwxd answers contradicted them 0 times.
Ask a panel
Panel mode asks several people at once. Each answers from their own wiki. wwxd then maps where they agree, where they split and why, runs a debate round labelled as inferred, and ends with a synthesis. Answers read as prose, with the sources listed underneath.
What it can't do
It does not predict opinions a person hasn't voiced yet. I held back positions people took in 2026, and wwxd guessed them no better than plain Claude. It knows what someone has said, not what they will say next.
How it's built
A Python command-line tool and a Claude Code plugin, built in October 2026 under the MIT licence. The design follows Andrej Karpathy's "LLM wiki" idea. It can transcribe audio locally with faster-whisper and check by voice who is speaking. On 12 October 2026 it had 135 tests, which run in CI on Linux, macOS and Windows.
Python, Typer, yt-dlp, trafilatura, rapidfuzz, faster-whisper, Claude Code.