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agent-thanks

agent-thanks

Verified

Trace the open source a coding task actually used, with evidence you can review and export.

All-time rank score
15

Developer Tools tool by 유진 홍 on Smol Launch.

Launched
September 2026
Website
github.com
Maker
@yujinhong3

Screenshots

About

agent-thanks is a consent-first Python CLI for reconstructing the open-source footprint of a single coding task.

It compares dependency files against a Git baseline and can optionally scan a local agent transcript. Every result includes its evidence: a newly added direct dependency, a clone or Git install command, a submodule, an explicit provenance line, or a GitHub URL that was only viewed. A bare URL stays a low-confidence reference and cannot be starred.

Detection is deterministic, with no second model. Session logs stay local. Package resolution can query PyPI, npm, or crates.io; --offline disables those lookups. Results can be reviewed in the terminal or exported as Markdown for a PR or release note.

Every eligible GitHub Star requires a separate, default-No y/N decision in an interactive terminal. There is no auto mode, approve-all flag, piped confirmation, or unattended Star path.

Try the read-only demo with Python 3.10+:
pipx install git+https://github.com/dbwls99706/[email protected]
agent-thanks demo

Reviews, comments, and launches

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Frequently asked questions

What is agent-thanks?
Trace the open source a coding task actually used, with evidence you can review and export.
Is agent-thanks free?
Yes — agent-thanks is free to use.
Who made agent-thanks?
agent-thanks was built by 유진 홍.
What category does agent-thanks belong to?
agent-thanks is listed in the Developer Tools category on Smol Launch.
When did agent-thanks launch?
agent-thanks launched on Smol Launch the week of September 28, 2026.

AI-readable Markdown