agent-learning-kit
General Purpose Evaluation and Simulation Environment for all your AI related Workflows
GraphCanon updated Sep 20, 2026 · GitHub synced Sep 20, 2026
190views this month
Decision brief
agent-learning-kit is a Python-based toolkit for evaluating and simulating AI workflows, particularly suited for AI agents. It offers optional extras for specific functionalities and a TypeScript SDK for broader language
Good fit when
- When you need a comprehensive environment for evaluating and simulating AI workflows, especially for AI agents
- If you are working with Python and want to leverage optional extras like livekit or nli for specific functionalities
Avoid when
- If your project strictly requires a different programming language other than Python or TypeScript
- When you need a tool that is already at a mature v1 release, as agent-learning-kit is still developing its TypeScript SDK and extras
Observed Sep 18, 2026 · Source: enrich:decision_facts
Verify the decision
Maintenance and security
Full trust report- Maintenance
- Very active (0d since push)
- As of Sep 18, 2026
- Provenance
- Not a fork · Organization account
- As of Sep 18, 2026
- Security (OSV)
- No lockfile
- As of Sep 18, 2026
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install agent-learning-kitSimilar tools
Same-category neighbours. No typed graph edges are catalogued for this tool yet.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
A Python-based toolkit for evaluating and simulating AI workflows, focusing on AI agents and their evaluation.
Capability facts
- CLI
- CLI entrypoint
Source: pyproject.toml:[project.scripts] · Sep 18, 2026
- Languages
- python
Source: github.language+pyproject.toml · Sep 18, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Sep 18, 2026)
Optional Python extras:Source link
Tags
README
Install Install from PyPI: To develop against source (contributors): (npm publishing of the TypeScript SDK lands at the v1 launch.) Optional Python extras: TypeScript evaluation package (npm at launch; today build from ):
For agents
This page has a .md twin and JSON over the API.