ainl
Deterministic compiled graphs for Hermes Agent (importer, runtime, MCP tools, learning-loop bridge)
Informations de source
- Dépôt
- sbhooley/ainativelang
- Dernière activité de la source
- 5 mai 2026 à 15:34
- Langue détectée de SKILL.md
- anglais
- Étoiles
- 650
- Forks
- 23
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SKILL.md
Instructions source · Aperçu en lecture seule- name
- AINL
- description
- Deterministic compiled graphs for Hermes Agent (importer, runtime, MCP tools, learning-loop bridge)
- install
- ./install.sh
- install_alt
- pip install 'ainativelang[mcp]' && ainl install-mcp --host hermes
- commands
- ["ainl import <source> — convert Markdown / ecosystem packs into `.ainl` graphs","ainl compile <file.ainl> — compile and validate deterministic graph IR","ainl run <file.ainl> — run compiled workflow (when your graph uses the runtime path)","~/.hermes/bin/ainl-run <file.ainl> — compile-then-run wrapper after install-mcp --host hermes (add ~/.hermes/bin to PATH)"]
- tags
- ["ainl","graphs","mcp","hermes"]
- metadata
- {"hermes":{"kind":"skill","upstream":"https://github.com/sbhooley/ainativelang","package_pypi":"ainativelang","mcp_server_key":"ainl","config_file":"~/.hermes/config.yaml","skills_dir":"~/.hermes/skills","onboarding_note":"Hermes Agent reads MCP config from ~/.hermes/config.yaml (mcp_servers). This pack installs a local AINL skill folder and expects ainl-mcp to be registered as a stdio MCP server."}}
# 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`)
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