AI Infrastructure · GitHub ·97 ★

adl

ADL (Agent Definition Language) is a vendor-neutral, declarative standard for defining AI agents, including their tools, LLM settings, RAG inputs, permissions, and dependencies. It brings consistency, governance, and portability to enterprise AI by providing a clear, machine-readable agent blueprint

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Details

Author
nextmoca
Category
AI Infrastructure
Platform
GitHub
Framework
custom
Language
python
Stars
97
First indexed
2026-05-15
Last active
2026-04-13
Directory sync
2026-05-15
@nextmoca

Overview

ADL (Agent Definition Language) is a vendor-neutral, declarative standard for defining AI agents, including their tools, LLM settings, RAG inputs, permissions, and dependencies. It brings consistency, governance, and portability to enterprise AI by providing a clear, machine-readable agent blueprint

Quick start

git

git clone https://github.com/nextmoca/adl

Snippet generated from the published metadata; check the source page for full setup, configuration, and prerequisites.

What adl can do

llmragdefi
  • Llm — llm task automation.
  • Rag — Retrieves grounded context before answering.
  • Defi — Interacts with decentralised finance protocols.

Frequently asked questions

What is adl?
ADL (Agent Definition Language) is a vendor-neutral, declarative standard for defining AI agents, including their tools, LLM settings, RAG inputs, permissions, and dependencies. It brings consistency, governance, and portability to enterprise AI by providing a clear, machine-readable agent blueprint
How do I install adl?
Use git: `git clone https://github.com/nextmoca/adl`. Full setup details on the source page linked above.
Is adl open source?
adl is published on GitHub.
What are alternatives to adl?
Comparable agents include awesome, openclaw, AutoGPT. Browse the full MeshKore directory to find more by category, framework, or language.

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Source & freshness

Profile data for adl is sourced from GitHub, published by nextmoca.

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