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Hundreds of agent skills for medical research, including protocol design, data analysis, evidence insights, and academic writing.

909 starsPython

We Evaluates Medical Research Agent Skills

by The_resa·Apr 9, 2026·2 points·0 comments

AI Analysis

MidNiche Gem

Curated prompt library with 420+ skills, but agent skill marketplaces already exist.

Strengths
  • Veto gate evaluation framework checks stability, security, and scientific integrity
  • Domain-specific focus on medical research workflows across four categories
  • Compatible with multiple agent platforms including OpenClaw and Claude
Weaknesses
  • Essentially a curated template collection like Shopify Sections or prompt libraries
  • Evaluation framework not clearly usable independently from AIPOCH's platform
Category
Target Audience

AI agent developers building medical research tools

Similar To

LangChain tools · CrewAI skills · Prompt libraries

Post Description

What is AIPOCH Medical Skill Auditor?

Medical Skill Auditor is an evaluation framework that AIPOCH uses to assess the quality of its medical research agent skills before they are made available to users. It acts as a gatekeeper, ensuring that skills meet defined standards in reliability, usability, security, and scientific integrity.

How does Medical Skill Auditor work?

Veto Gates

To enforce strict quality control, Skill Auditor is designed with two layers of veto mechanisms. Any failure in these checks may lead to immediate rejection of a skill.

Skill Veto

Operational Stability Structural Consistency Result Determinism System Security

Research Veto

Scientific Integrity Practice Boundaries Methodological Ground Code Usability

Core Capability

Evaluates a skill’s design and contract against key dimensions such as Functional Suitability, Reliability, Performance & Context, Agent Usability, Human Usability, Security, Agent-Specific and Maintainability.

Medical Task

Assesses actual outputs of a skill with layered criteria.

For skill testing, the AI automatically generates inputs. The number of inputs in specific categories will increase or decrease depending on the complexity of the skill. The following 7 inputs represent the most comprehensive version.

/Canonical /Variant A /Edge /Variant B /Stress /Scope Boundary /Adversarial

Skill Complexity Classification

Label Code/Rank Definition

Simple S Narrow task scope

Moderate M Moderate branching or multiple task types

Complex C Broad or multi-step specialized skill

Simple (S):3 inputs

Moderate (M):5 inputs

Complex (C):7 inputs

Final Score

The Skill Evaluator uses a two-stage scoring system: static evaluation (design quality, accounting for 40%) and dynamic evaluation (runtime performance, accounting for 60%). The final overall score is derived by combining both.

Static (40%) Dynamic (60%)

Final Score = Static Score × 40% + Dynamic Score × 60%

You can view evaluation results for selected AIPOCH skills here:https://www.aipoch.com/agent-skills/medical-research-literat....

This framework is still under active development, we’d love to hear your feedback! Right now this assessment framework is only applied to a subset of AIPOCH’s skills, but we’re considering expanding it more broadly. If this evaluation framework could be used to assess third‑party skills in the future, would you consider trying it in your own projects? Are there evaluation frameworks you’re already using?

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