Real Agent Cases

Run async code-research benchmarks with a coding agent

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How we verify

Evidence: Screenshots or logsThe source shows screenshots, a transcript or the agent's output.

Outcome

An async coding agent cloned several Python Markdown libraries, benchmarked them against cmarkgfm, and wrote a report with charts, with almost no human time spent.

Agent

Claude Code for web, OpenAI Codex

Prompt Original prompt

Exact prompt as published in the source.

Create a performance benchmark and feature comparison report on PyPI cmarkgfm compared to other popular Python markdown libraries—check all of them out from github and read the source to get an idea for features, then design and run a benchmark including generating some charts, then create a report in a new python-markdown-comparison folder (do not create a _summary.md file or edit anywhere outside of that folder). Make sure the performance chart images are directly displayed in the README.md in the folder.

Source

https://simonwillison.net/2025/Nov/6/async-code-research/

By Simon Willison · Published Nov 6, 2025 · Added Oct 15, 2026 · Last verified Oct 15, 2026

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