Who should use agentgrade?

agentgrade is an open-source project built for AI developers and researchers.

Yes — agentgrade is open source under the MIT license and free to use.

What platforms does agentgrade run on?

agentgrade runs on the command line. It can also be self-hosted.

Is agentgrade still maintained?

Unverified. agentgrade has not been re-checked since it entered the index, so there is no finding either way — and only a positive finding would say otherwise.

What are alternatives to agentgrade?

Similar projects tracked by PulseGate include AgentGrade, agent-genesis, and agentaudit-eval.

Who develops agentgrade?

agentgrade is developed by Shengyong Niu.

How long has agentgrade been around?

agentgrade first shipped in 2026.

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agentgrade

Name: agentgrade
Author: Shengyong Niu

PyPIInfrastructure

agentgrade is an open-source testing framework for multi-agent AI systems. It provides regression tests, credit assignment, and prompt patching, enabling developers and researchers to evaluate and improve agent workflows efficiently.

Open SourceMITCLISelf-hosted

Visit PyPI

Overview

5 features

In the AI space, agentgrade takes a focused approach. It focuses on testing and evaluating multi-agent AI workflows with automated regression and prompt patching. agentgrade is an open-source project aimed at AI developers and researchers. The project is open source (MIT). agentgrade is available on the command line, and it can be self-hosted.

Behind agentgrade is Shengyong Niu, and it first shipped in 2026. Key capabilities include regression testing, prompt patching, and credit assignment.

Summary written by a language model from the project’s public pages.

Regression testing
Prompt patching
Credit assignment
Multi-agent support
Pytest integration

Built with & integrations

Runs on

CLISelf-hosted

Trust & compliance

License

MIT

Verified signals

HTTPSOpen Source GitHub

Indexing history

What PulseGate has recorded for this listing

Indexed1 Jul · 02:04 UTC
agentgrade verified against its public source
Source: PulseGate · Open

Frequently asked questions about agentgrade

What does agentgrade do?: Agentgrade focuses on testing and evaluating multi-agent AI workflows with automated regression and prompt patching. It is catalogued under AI on PulseGate.
Who should use agentgrade?: agentgrade is an open-source project built for AI developers and researchers.
Is agentgrade free?: Yes — agentgrade is open source under the MIT license and free to use.
What platforms does agentgrade run on?: agentgrade runs on the command line. It can also be self-hosted.
Is agentgrade still maintained?: Unverified. agentgrade has not been re-checked since it entered the index, so there is no finding either way — and only a positive finding would say otherwise.
What are alternatives to agentgrade?: Similar projects tracked by PulseGate include AgentGrade, agent-genesis, and agentaudit-eval.AgentGrade agent-genesis agentaudit-eval See all 10 alternatives
Who develops agentgrade?: agentgrade is developed by Shengyong Niu.
How long has agentgrade been around?: agentgrade first shipped in 2026.

At a glance

Platforms: Cli
Languages: English
Open source: Yes (GitHub)
License: MIT
First seen: 1 Jul 2026
Built for: AI developers and researchers
Model: Open source
Solves: Testing and evaluating multi-agent AI workflows with automated regression and prompt patching.

Registered as

GitHub: shengyongniu/agentgrade
PyPI: agentgrade

Developer

Shengyong Niu

GitHub

Open source

View on GitHub

Index record

Identity confidence: Low · 64
Indexed: 1 Jul 2026
Lifecycle: Alive
First seen: Jul 2026
Last seen: 1 Jul 2026

Identity audit (12)

Slug: agentgrade-pypi-org
Lifecycle last checked: 8 Aug 2026
Verification state: Indexed for public listing
Listing state: Listed: yes
Index status: Included in index
Latest evidence snapshot: 1 Jul 2026
Timeline basis: Indexed-at chronology (no inferred launch/funding milestones).
Name from: Written by a language model from the project's public pages.
Category from: Assigned by a language model.
Summary from: Written by a language model from public pages.
Languages from: Detected by a language model from page content.
Canonical URL: https://pypi.org/project/agentgrade

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