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honest-scholar — a CLI for honest, defensible AI-assisted research (tooling for the honest-scholar plugin)

Project description

honest-scholar

Research you can defend.

honest-scholar helps you keep research honest — especially now that AI is in the loop. You (not the AI) make and sign off every material decision, and you must be able to explain and defend the work; the tool keeps the accounts, advises, and probes. It supports honest, disclosable AI-assisted research — it does not certify that any work is honest.

This package is the CLI / tooling behind the honest-scholar Claude Code plugin. The plugin (skills + methodology) stays pure-markdown; this package provides the honest-scholar command it calls — literature, dataset, defend, backlog, and doctor — installed isolated, so it never touches your project's ML environment.

Install

uv tool install honest-scholar     # recommended (isolated tool env)
# or: pipx install honest-scholar
# or: pip install honest-scholar

honest-scholar --version
honest-scholar doctor              # reports python / uv / rclone

Pre-releases are on TestPyPI (--index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple/).

CLI

honest-scholar --version
honest-scholar doctor                                        # environment report (implemented)
honest-scholar literature resolve|cites|refs|enrich|neighbors   # issue #1
honest-scholar dataset    validate|ingest|emit                    # issue #2
honest-scholar dataset    fetch|verify|mirror|audit               # issue #3
honest-scholar defend     record                                # issue #4
honest-scholar backlog    park|add|list|rank|promote|drop       # issue #5

Currently only doctor and --version are implemented; the domain sub-commands are typed stubs exiting with a pointer to their tracking issue.

Learn more

Status

Early / pre-release — see https://github.com/davorrunje/honest-scholar/blob/main/STATUS.md.

License

Apache-2.0.

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