PhysicianBench — security grade SAFE, quality 72/100

Security audit verdict: SAFE · quality 72/100

No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

by HealthRex · Agent Tool · ★ 51

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

🔒 Is PhysicianBench safe to install? View the security audit →

About PhysicianBench

PhysicianBench: Evaluating LLM Agents in Real-World EHR Environments Overview PhysicianBench is a benchmark for evaluating LLM agents on physician tasks grounded in real clinical workflows. It comprises 100 long-horizon tasks (670 sub-checkpoints) adapted from real primary-care/specialty consultations across 21 specialties, executed in an EHR environment with real patient records accessed via standard FHIR APIs. Solving each task requires retrieving data across encounters, reasoning over heterogeneous clinical information, executing consequential clinical actions, and producing clinical documentation. Main Results Overall model performance on PhysicianBench, ranked by pass@1 success rate. Trajectory Example !

benchmarkehrhealthcare-aillm-agentmedical-ai

Quick Facts

Stars51
Forks4
LanguagePython
CategoryAgent Tool
LicenseApache-2.0
Quality Score72.2209338015781/100
Open Issues1
Last Updated2026-08-13
Created2026-04-28
Platformspython
Est. Tokens~14k

Compatible Skills

These tools work well together with PhysicianBench for enhanced workflows:

  • PawBench — semantic(0.47)+complementary+same_lang+similar_pop+shared_platform (66%)
  • OpenClawProBench — semantic(0.46)+complementary+same_lang+similar_pop+shared_platform (66%)
  • Toucan — semantic(0.34)+complementary+same_lang+similar_pop+shared_platform (62%)
  • MCPBench — semantic(0.31)+complementary+same_lang+similar_pop+shared_platform (61%)
  • toolathlon_gym — semantic(0.30)+complementary+same_lang+similar_pop+shared_platform (61%)

PhysicianBench alternative? Top 6 similar tools

Looking for a PhysicianBench alternative? If you're comparing PhysicianBench with other agent tool tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

  • HealthChain by healthchainai · ⭐ 221

    Python SDK for healthcare AI — typed, validated FHIR tools for agents, real-time EHR connectivity, production

  • EhrAgent by wshi83 · ⭐ 139

    [EMNLP'24] EHRAgent: Code Empowers Large Language Models for Complex Tabular Reasoning on Electronic Health Re

  • HealthFlow by yhzhu99 · ⭐ 54

    [npj Digital Medicine 2026] HealthFlow: Automating electronic health record analysis via a strategically self-

  • MCPBench by modelscope · ⭐ 251

    The evaluation benchmark on MCP servers

  • agent-studio by ltzheng · ⭐ 232

    [ICLR 2025] A trinity of environments, tools, and benchmarks for general virtual agents

  • llm-price-compass by arc53 · ⭐ 223

    This project collects GPU benchmarks from various cloud providers and compares them to fixed per token costs.

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Frequently Asked Questions

What is PhysicianBench?

PhysicianBench is The benchmark tasks and evaluation harness for "PhysicianBench: Evaluating LLM Agents in Real-World EHR Environments".. It is categorized as a Agent Tool with 51 GitHub stars.

What programming language is PhysicianBench written in?

PhysicianBench is primarily written in Python. It covers topics such as benchmark, ehr, healthcare-ai.

How do I install or use PhysicianBench?

You can find installation instructions and usage details in the PhysicianBench GitHub repository at github.com/HealthRex/PhysicianBench. The project has 51 stars and 4 forks, indicating an active community.

What license does PhysicianBench use?

PhysicianBench is released under the Apache-2.0 license, making it free to use and modify according to the license terms.

What are the best alternatives to PhysicianBench?

The top alternatives to PhysicianBench on Agent Skills Hub include HealthChain, EhrAgent, HealthFlow. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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