---
name: AINL
slug: ainl-2
category: AI Engineering
description: AINL compiles deterministic .ainl graphs for Hermes Agent. Use it to import workflows, run them safely, and expose MCP tools for repeatable execution and closed learning loops.
github: "https://github.com/sbhooley/ainativelang/tree/main/skills/hermes"
language: Python
stars: 714
forks: 29
install: "npx degit https://github.com/sbhooley/ainativelang/tree/main/skills/hermes ~/.claude/skills/hermes"
installs_to: ~/.claude/skills/hermes
source_path: skills/hermes/SKILL.md
collection_size: 3
category_size: 2451
collection_url: "https://dirskills.com/collections/sbhooley/ainativelang"
added: 2026-08-23T05:20:19.946Z
last_synced: 2026-08-23T05:20:19.946Z
canonical_url: "https://dirskills.com/skills/ainl-2"
---

# AINL

AINL compiles deterministic .ainl graphs for Hermes Agent. Use it to import workflows, run them safely, and expose MCP tools for repeatable execution and closed learning loops.

**Install:**

```bash
npx degit https://github.com/sbhooley/ainativelang/tree/main/skills/hermes ~/.claude/skills/hermes
```

## README

# AINL for Hermes Agent

**AINL** is an AI-native language that compiles **deterministic graphs**. In Hermes Agent, use it to import workflows, compile them, run them, and expose **`ainl-mcp`** tools to the agent for safe, repeatable execution.

**Package:** `ainativelang` **v1.8.0** (this tree; **PyPI** after publish — **`docs/RELEASING.md`**). Optional extras: `[mcp]`, `[solana]`.

## Agent instructions

Follow this skill when the user is on **Hermes Agent** (or wants a **closed learning loop** on top of **deterministic `.ainl` graphs**). Prefer **`./install.sh`** from a checked-out skill folder, or the manual path:

`pip install 'ainativelang[mcp]' && ainl install-mcp --host hermes`

After bootstrap, suggest the prompt below when it fits.

## When to use this skill

- The user wants **portable, compiled workflows** (`.ainl`) instead of ad-hoc prompt loops.
- They mention **import**, **compile**, **skills**, **learning loop**, or **MCP**.
- They want Hermes to evolve behavior while keeping a strict, checkable graph source of truth.

## Install (pick one)

1. **From this skill directory:** run `./install.sh`  
   That upgrades `ainl[mcp]` (if needed), installs a skill folder to `~/.hermes/skills/ainl/`, and wires MCP via `ainl install-mcp --host hermes`.

2. **Manual:**  
   `pip install 'ainativelang[mcp]' && ainl install-mcp --host hermes`

## After install — prompt suggestion

Tell the user they can say in Hermes:

> Import the morning briefing using AINL.

## MCP

Hermes reads MCP config from `~/.hermes/config.yaml` under `mcp_servers`. The host should run **`ainl-mcp`** as a stdio MCP server. `ainl install-mcp --host hermes` merges that entry when missing.

## Bridge (optional)

This pack includes `ainl_hermes_bridge.py` as a lightweight utility for:

- writing AINL trajectory/audit tapes into Hermes-friendly local memory files
- exporting Hermes-evolved behaviors back into `.ainl` (so you can re-run `ainl check --strict`)