A vendor-neutral blueprint for describing an AI agent’s identity, model settings, tools, permissions, and governance information. ADL stands for Agent Definition Language.

Use it to write portable agent definitions, specify models and tools, set permissions, provide retrieval inputs, and record governance metadata.

It separates the description of what an agent is allowed and expected to do from the software that runs it, making the definition easier to reuse across systems.

adl — Skill for Claude Code by Tyler-R-Kendrick/agent-skills

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent

npx skills add Tyler-R-Kendrick/agent-skills --skill adl

Clone the repo

git clone --depth 1 https://github.com/Tyler-R-Kendrick/agent-skills

Made for: Claude Code.

Or install agent-skills, the plugin that ships this one along with the rest of its 57 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/tyler-r-kendrick/agent-skills/adl/github.svg)](https://agentmods.dev/skills/tyler-r-kendrick/agent-skills/adl)

Your own site

<a href="https://agentmods.dev/skills/tyler-r-kendrick/agent-skills/adl"><img src="https://agentmods.dev/badge/skills/tyler-r-kendrick/agent-skills/adl/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/tyler-r-kendrick/agent-skills/adl"><img src="https://agentmods.dev/badge/skills/tyler-r-kendrick/agent-skills/adl.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 87 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,115 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00087	$0.01115
Opus 5.5	$0.00035	$0.00446
Sonnet 5.5	$0.00017	$0.00223
Haiku 4.5	$0.00009	$0.00112

Measured 2mo ago against content hash 49d705160563, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

adl scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/ai/adl/SKILL.md · 140 lines

How it starts

The opening of the file, as written. The whole thing — 140 lines — stays where its author put it; the contents beside it link to each section on GitHub.

ADL — Agent Definition Language

Overview

ADL is a vendor-neutral, declarative specification for defining AI agents — their identity, capabilities, tools, permissions, and governance metadata. It acts as a portable blueprint (like OpenAPI for APIs) that is independent of any runtime, framework, or vendor. Open-sourced by Next Moca under Apache 2.0, also adopted by Eclipse LMOS.

Purpose

ADL defines what an agent is and what it can do, not how it runs. It complements:

MCP — how agents call tools at runtime
A2A — how agents communicate
Agent Skills — how capabilities are packaged

Example

adl: "1.0"

agent:
  name: research-assistant
  version: "1.0.0"
  description: "Researches topics and produces structured summaries"
  author: "team-name"
  license: MIT

  llm:
    provider: anthropic
    model: claude-sonnet-4-5-20250929
    temperature: 0.3
    max_tokens: 4096
    system_prompt: |
      You are a research assistant. Produce well-structured,
      factual summaries with cited sources.

  tools:
    - name: web-search
      type: mcp
      server: "search-server"
      description: "Search the web for information"
    - name: read-document
      type: mcp
      server: "doc-server"
      description: "Read and parse documents"

  rag:
    - name: knowledge-base
      source: "vector-store://company-docs"
      description: "Internal documentation and policies"

  permissions:
    allowed_tools:
      - web-search
      - read-document
    denied_actions:
      - file_write
      - code_execution
    boundaries:
      max_tokens_per_request: 8192
      max_requests_per_minute: 30

  dependencies:
    - name: fact-checker
      type: agent
      description: "Validates factual claims before including them"

  governance:
    owner: "[email protected]"
    review_status: approved
    last_reviewed: "2026-01-15"
    tags:
      - research
      - internal

Schema Sections

Agent Identity

Field	Description
`name`	Unique agent identifier
`version`	Semantic version
`description`	What the agent does
`author`	Creator or team
`license`	SPDX identifier

Read the full file on GitHub · 140 lines

Files

What ships with it

11 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

2mo ago First seen · 140 lines · 87 tokens per session scan A 49d705160563

Subscribe to this mod's changes

adl is a skill published in the GitHub repository Tyler-R-Kendrick/agent-skills (13 stars, last pushed 5mo ago), licensed MIT. It adds 87 tokens to every session and 1,115 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Building agents

adl next to 6 skills from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
adlTyler-R-Kendrick/agent-skills	Skill	13	5mo ago	MIT	A	87	Claude Code
imagegenopenai/codex	Skill	133k	yesterday	Apache-2.0	A	113	Codex
playwright-climicrosoft/playwright	Skill	99k	yesterday	Apache-2.0	A	19	Claude Code
local-ai-agentsmicrosoft/ai-agents-for-beginners	Skill	79k	4d ago	MIT	A	200	Claude Code, Codex
systematic-debuggingobra/superpowers	Skill	313k	3d ago	MIT	A	21	Claude Code
next-cache-components-adoptionvercel/next.js	Skill	143k	yesterday	MIT	A	95	Claude Code
next-partial-prefetching-adoptionvercel/next.js	Skill	143k	yesterday	MIT	A	103	Claude Code