LingxiangXu/traceclause
Local-first document requirements and evidence review workbench with traceable citations and human review.
About the project
A local-first workbench for reviewing requirements against evidence: it compares a requirements document with a proposal or response, surfaces candidate quotations, and records human decisions with traceable citations. It runs without external AI calls and keeps data on the machine.
Useful for
- Compare a requirements document with a proposal text and get candidate quotations to inspect.
- Record a reviewer decision with rationale and export a traceable report in Markdown, CSV or JSON.
- Check numerical discrepancies between requirements and a response and get a review reminder.
README summarized by DeepSeek V4.1 Flash. Details may be inaccurate.
Why it’s trending
- 0 stars so far today, about 51 expected by the end of the day.
- The spike has held for 2 days in a row — not a one-off blip.
- The repository is 1 day old and already has 58 stars.
- Top new repositories this week: #196.
Stars per day
Bars are daily stars, the line is the usual pace. Red marks spike days.
Numbers
- Total stars
- 58
- Stars in a day
- 50
- Forks
- 4
- Issues and pull requests
- 0
- Watchers
- 3
- Language
- Python
- License
- MIT
- Latest release
- v0.1.0 · September 18, 2026
- Created
- September 18, 2026
- Last push
- September 18, 2026
Star trust
Growth looks organic: forks and discussion are in line with active projects, and stars arrive unevenly, the way people give them.
These are heuristics, not a verdict: we judge by the repository’s behavior, not by a list of stargazers.
Spotted in
- September 19, 2026Top new repositories this week: #194
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