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actava-ai/chi-bench

Χ-Bench: Can AI Agents Automate End-to-End, Long-Horizon, Policy-Rich Healthcare Workflows?

#LLM evaluation
Visit GitHub
Python
71
18
5 contributors
Apache License 2.0
website
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ClawBench

a benchmark for personal agents

Momentum

How fast actava-ai/chi-bench 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

Sep 2 – Oct 23, 2026

Stars +14 in 52 days

01
1

Forks +9 in 52 days

012
2

Merged PRs 3 in 52 days

012
2

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

Not in the Trendshift top 25 in this period

Sep 2Sep 9Sep 16Sep 23Sep 30Oct 7Oct 14Oct 21
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
Wed, Sep 2, 2026+1+10
Thu, Sep 3, 2026+1+00
Fri, Sep 4, 2026+0+00
Sat, Sep 5, 2026+0+10
Sun, Sep 6, 2026+1+00
Mon, Sep 7, 2026+0+00
Tue, Sep 8, 2026+0+00
Wed, Sep 9, 2026+1+10
Thu, Sep 10, 2026+0+00
Fri, Sep 11, 2026+0+00
Sat, Sep 12, 2026+0+00
Sun, Sep 13, 2026+0+00
Mon, Sep 14, 2026+0+00
Tue, Sep 15, 2026+1+00
Wed, Sep 16, 2026+0+00
Thu, Sep 17, 2026+0+00
Fri, Sep 18, 2026+0+00
Sat, Sep 19, 2026+1+00
Sun, Sep 20, 2026+0+00
Mon, Sep 21, 2026+0+00
Tue, Sep 22, 2026+0+00
Wed, Sep 23, 2026+0+00
Thu, Sep 24, 2026+0+00
Fri, Sep 25, 2026+0+00
Sat, Sep 26, 2026+0+00
Sun, Sep 27, 2026+0+00
Mon, Sep 28, 2026+1+00
Tue, Sep 29, 2026+1+00
Wed, Sep 30, 2026+0+00
Thu, Oct 1, 2026+0+00
Fri, Oct 2, 2026+1+20
Sat, Oct 3, 2026+0+00
Sun, Oct 4, 2026+0+00
Mon, Oct 5, 2026+1+00
Tue, Oct 6, 2026+0+00
Wed, Oct 7, 2026+0+02
Thu, Oct 8, 2026+0+10
Fri, Oct 9, 2026+0+00
Sat, Oct 10, 2026+0+00
Sun, Oct 11, 2026+0+10
Mon, Oct 12, 2026+1+00
Tue, Oct 13, 2026+0+00
Wed, Oct 14, 2026+0+00
Thu, Oct 15, 2026+0+01
Fri, Oct 16, 2026+0+00
Sat, Oct 17, 2026+1+00
Sun, Oct 18, 2026+0+00
Mon, Oct 19, 2026+1+00
Tue, Oct 20, 2026+1+10
Wed, Oct 21, 2026+0+00
Thu, Oct 22, 2026+0+10
Fri, Oct 23, 2026+0+00
Total+14+93
  • 1#1 on the list
  • 7Rank that day
  • Not trending

Social mentions

Recent discussions about this repository across the web
  1. Jun 41 post

    • Huge congrats to @Humana's Erius agent taking the #1 spot on CHI-Bench for Prior Auth and 6th for all domains. It outperforms every frontier lab on one of healthcare's hardest workflows.

      Read full on X, posted by @iscreamnearby

      @iscreamnearby · x.com

  2. May 301 post

    • χ-Bench moved agent evals into the right operating environment: policy-dense healthcare workflows. But 28% pass@1 is not interpretable as deployment evidence yet. Not without calibrated human and…

      Read full on X, posted by @osanpochuudayo

      @osanpochuudayo · x.com

  3. May 281 post

    • CHI-Bench was built with a 20+ institution research collaboration spanning health systems 🏥 @HopkinsMedicine @AlvinLiu_MD @WellstarHealth Hank Capps, MD FAAFP @YaleMed Tianyi Zeng and university &…

      Read full on X, posted by @iscreamnearby

      @iscreamnearby · x.com

  4. 8 days earlier
  5. May 202 posts4 posts

    • 4/ Leaderboard 🏆 Best overall: Claude Code Opus 4.6 — 28% pass@1 Runner-up: Codex GPT-5.5 — 21% By domain: • Utilization review: 41% • Care management: 32% • Prior-auth paperwork: 29% The field is…

      Read full on X, posted by @dmon2048

      @dmon2048 · x.com

    • (5/n) Built with collaborators from 19 organizations, hospitals and universities: Johns Hopkins, Yale, Stanford, CMU, Oxford, MBZUAI, and more. Healthcare AI evaluation has to be done with clinicians…

      Read full on X, posted by @HaolinChen11

      @HaolinChen11 · x.com

    • 4/🧵Leaderboard Results Best overall: Anthropic's Claude Code Opus 4.6 — 28% pass@1. Runner-up: OpenAI's Codex GPT-5.5 — 21%. By domain: utilization review 41%; care management 32%; prior-auth…

      Read full on X, posted by @iscreamnearby

      @iscreamnearby · x.com

    • In real healthcare operations, agents must do far more than answer medical questions. They need to read charts, interpret clinical and operational policies, verify coverage, route referrals, draft…

      Read full on X, posted by @CaimingXiong

      @CaimingXiong · x.com

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