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yukyeongleee/wikitrace

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Python
6
2 contributors
Apache License 2.0
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Control what AI can do before it acts

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Versioned graph database on object storage. Git-style workflows and multimodal retrieval

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Can AI agents reverse-engineer real websites?

Momentum

How fast yukyeongleee/wikitrace is gaining stars, and where it lands on Trendshift and GitHub Trending

Activity and trending

Stars, forks and merged pull requests each day or month, lined up with the repository's rank on Trendshift Trending

Nov 10 – Nov 11, 2026

Stars +5 in 2 days

0246
5

Forks +0 in 2 days

01

Merged PRs 0 in 2 days

01

Trendshift Trendingwhere the repository ranked each day it made the top 25

Not in the Trendshift top 25 in this period

Nov 10Nov 11
The left and right arrow keys step from day to day; Home and End go to the first and the last

Stars, forks, merged pull requests and Trendshift Trending rank, by day
DayStars gainedForks gainedMerged PRs
Tue, Nov 10, 2026+0+00
Wed, Nov 11, 2026+5+00
Total+5+00
  • 1#1 on the list
  • 7Rank that day
  • Not trending

Social mentions

Recent discussions about this repository across the web
  1. Nov 113 posts
    • Agent memory can break tasks an agent already solves. KAIST traced 52% of those failures to a lesson it followed, often a wrong one. WikiTrace links every lesson back to its source run so the agent…

      Read full on X, posted by @bvsbharat

      @bvsbharat · x.com

    • Why it matters: Building agent memory? Don't store only the summary. Link the raw trace so the agent can check a lesson before following it. Limits: all insights go in the first prompt, so it grows…

      Read full on X, posted by @randhir302

      @randhir302 · x.com

    • 📈 Across five benchmarks, WikiTrace scored 3.2 points higher on average than giving the agent the same lessons alone. On tasks the agent could solve without memory, the failure rate dropped from…

      Read full on X, posted by @yukyeongleee

      @yukyeongleee · x.com