Which NSF programs are specifically supported?

The skill includes specialized reviewer profiles for CSSI (Cyberinfrastructure), POSE (Open-Source Ecosystems), and CAREER (Faculty Early Career Development) programs, but can be used for any NSF program.

What kind of feedback does the simulator provide?

It provides detailed strengths and weaknesses for both Intellectual Merit and Broader Impacts, a numerical-equivalent rating, and a panel summary that highlights common themes across multiple reviewers.

How does the skill generate reviewer personas?

It identifies the target program from your grant metadata and generates 3-5 fictional but realistic expert profiles, such as domain scientists or industry experts, to ensure a diverse range of feedback.

Does this skill require specific file structures?

Yes, it looks for an assembled_proposal.md file or individual response files like project_summary.md and project_description.md within your GrantKit directory.

NSF Panel Review Simulator

Name: NSF Panel Review Simulator
Author: GrantKit

byGrantKit

0•

생산성 및 워크플로

Simulates National Science Foundation (NSF) panel reviews to identify proposal weaknesses and provide actionable feedback before submission.

The NSF Panel Review Simulator is a specialized tool designed for researchers and academics using GrantKit to refine their grant proposals. By analyzing existing proposal drafts and program-specific metadata, it generates realistic reviewer personas—such as domain scientists, software engineers, or impact evaluators—to provide multi-perspective feedback. The skill produces standardized NSF-style reviews covering Intellectual Merit and Broader Impacts, complete with a panel summary and ratings ranging from Excellent to Poor. This allows applicants to stress-test their arguments and address potential criticisms in a simulated environment, significantly improving the quality of the final submission.

주요 기능

01Program-specific reviewer persona generation (CSSI, POSE, CAREER)

02Standardized evaluation of Intellectual Merit and Broader Impacts

03Comprehensive panel summaries with key themes and consensus ratings

04Simulated NSF rating scale from Excellent to Poor

05Actionable revision suggestions based on specific proposal content

060 GitHub stars

사용 사례

01Stress-testing the 'Broader Impacts' section against specialized evaluator perspectives

02Preparing for potential panel criticism by reviewing simulated negative feedback

03Identifying critical technical gaps or logic flaws in a draft proposal

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add grantkit/grantkit nsf-review

For use in Claude.ai and ChatGPT