Documentation
Everything you need to build with AINL.
194 documents synced from the AI Native Lang repository — language reference, runtime, adapters, operations guides, case studies, and more.
OpenClaw CLI (v1.3.0+): ainl install openclaw, ainl status (--json / --summary), ainl cron add, ainl dashboard (needs run_tests_and_emit — see quickstart), ainl doctor --ainl. Quickstart · README (CLI polish table) · Easy install.
Start here
What is AINL?
Start here
OpenClaw quickstart (5 min)
install openclaw, status, cron add, dashboard, doctor — v1.3.0+
Release notes
v1.3.0 Hermes + OpenClaw integration, CLI polish
Competitive & comparisons
LangGraph, Temporal, OpenClaw savings worksheet, comparison tables
Architecture Overview
Graph IR & pipeline
Grammar Reference
Language ops & syntax
Adapter Registry
Adapters, verbs, tiers
Capability Grants
Security model
Orchestration Guide
Runner + MCP integration
90-day roadmap
Milestones, community goals, and growth priorities
Growth plan
Mirofish-inspired strategy and risk mitigations
Validation deep dive
Reachability, strict diagnostics, and execution tape
MCP host integrations
install-mcp --host … for OpenClaw, ZeroClaw, Hermes Agent
ZeroClaw integration
Skill, MCP, ainl-run bootstrap
OpenClaw integration
Skill, install-mcp --host openclaw, openclaw.json MCP
Hermes Agent integration
hermes-install, config.yaml MCP, emit hermes-skill, ainl_run
Hermes hub (one-pager)
Quickstart + link to full Hermes guide
OpenClaw monitoring
Token budget, weekly trends, memory path
Whitepaper
Full technical paper
Benchmarks
Size tables (tiktoken cl100k_base, synced)
Benchmarks hub
Metrics, CI, make targets
For Platform Teams
Prioritize docs that reduce routine monitoring cost and improve reliability: compile-once economics, deterministic runtime behavior, and MCP integration patterns.
Open monitoring guide →For Enterprise Audit
Focus on strict compiler checks, policy gates, and JSONL execution tape for auditability and incident reconstruction across production workflows.
Read validation deep dive →Getting started
Architecture
Graph IR, compile-once/run-many, state discipline, introspection.
AI Native Lang (AINL) Architecture Overview
This document provides a publication-ready map of how AINL works end to end.
COMPILE ONCE RUN MANY
This document is a small, reproducible proof pack that shows how AINL already supports:
or
Goal: show how to inspect AINL's compiled IR/graph today using existing tools, without adding new semantics.
STATE DISCIPLINE
This document describes AINL's state model as a unified, tiered discipline. AINL workflows manage state through explicit…
Language Reference
Grammar, ops reference, core modules, and language extensions.
AI Native Lang (AINL) 1.0 — Grammar & Ops Reference
Version: 1.0 — Stable for conformance tests and model training. Formerly referred to as v2 draft; AINL 1.0 is the normat…
Compact Syntax Reference
Human-friendly compact syntax for AINL — Python-like, 66% fewer tokens, compiles to the same IR as standard opcodes.
Reference
Adapter registry, capability registry, IR schema, glossary, and tool API.
Agent Graph v1 Schema
This document defines the canonical graph shape that agents and tooling can rely on for query, diff, and rewrite. The ru…
AI Native Lang (AINL) Adapter Registry (AINL 1.0)
> OpenClaw (MCP skill): For skills/openclaw/, ainl install-openclaw, and ~/.openclaw/openclaw.json MCP wiring, see ../OP…
AI Native Lang (AINL) Glossary
> OpenClaw (MCP skill): ../OPENCLAWINTEGRATION.md(../OPENCLAWINTEGRATION.md) — skills/openclaw/, ainl install-openclaw, …
AI Native Lang (AINL) IR Schema (overview)
This document gives a small-model-oriented view of the IR shape produced by compilerv2.py. It is intentionally high leve…
AI Native Lang (AINL) v0.9 – Small‑Model Profile
This document defines a tiny, stable subset of AINL 1.0 that is optimized for 3B–7B parameter models running offline or …
Capability Registry and Tool API v2 Projection
> OpenClaw (MCP skill): For OpenClaw onboarding (skills/openclaw/, ainl install-openclaw, ainl-mcp, ~/.openclaw/), see .…
Structured Tool API
AINL includes a simple structured tool interface for local agent loops:
Runtime
Safe optimization policy, targets roadmap, and runtime internals.
AI Native Lang (AINL) targets roadmap — real-world and production
Expanding targets so AI Native Lang is usable in production and for mass adoption. Major runtime/data/reactive lanes bel…
Async Runtime
AINL runtime execution remains backward-compatible and sync-first by default. This document describes the optional nativ…
Safe Optimization Policy (AINL)
This policy defines how to improve benchmark results without harming AINL's primary goal: reliable generation and execut…
Operations & Deployment
Capability grants, sandbox profiles, container guide, audit logging, and orchestration.
1) run workflow with trajectory enabled
Status: This document does not change compiler or runtime semantics. It describes how external orchestrators can discove…
Agent + AINL operating model (long-term)
This page fixes roles, defaults, and evidence for humans and coding agents that use AINL alongside OpenClaw (or other ho…
Autonomous Ops Monitors — Index
Last updated: 2026-03-20
AUTONOMOUS OPS PLAYBOOK
Status: This is a truthful snapshot of what AINL already supports for autonomous operations. It does not introduce new s…
BATCH AUTOMATION GUIDE
This guide is for batch issue-solving and worktree-based repo automation environments (Dispatch-style systems, CI bots, …
Capability Grant Model
The capability grant is AINL's restrictive-only host handshake mechanism. It constrains what an execution surface (runne…
Embedding retrieval pilot (vector search vs `memory.list`)
Goal: Replace wide memory.list scans with top-k semantic retrieval for one workflow at a time.
Host pack: OpenClaw (reference bundle)
This is a documentation bundle for a supported OpenClaw stack: not a separate installer, but a single checklist so suppo…
OpenClaw bridge
Bridge token budget, daily memory path, and OpenClaw cron integration (see also Operations).
Adapter Registry Notes
The ADAPTERREGISTRY.json is the machine-readable catalog of adapter capabilities.
Agent Coordination Contract (Cursor ↔ OpenClaw)
The coordination substrate between AI agents uses a local file-backed mailbox. The agreed verbs are:
AINL Auto-Tuner — Complete Documentation
The autotuneainlcaps program automatically adjusts AINL-related environment variables in OpenClaw to maintain token savi…
Apollo Promoter AINL Module Contracts
This page documents the reusable AINL modules introduced while thinning apollo-x-bot Python prompt logic.
Bridge Token Budget Alert System
See also: openclaw/bridge/README.md(../../openclaw/bridge/README.md) (runner, monitoring table, cron snippets) · docs/op…
Email Monitor Wrapper
See also: openclaw/bridge/runwrapperainl.py(../../openclaw/bridge/runwrapperainl.py) (registry) · docs/ainlopenclawunifi…
Golden Instructions: AINL Integration for OpenClaw
Goal: Achieve 85–95% token savings on session bootstrap by using AINL's curated sessioncontext.md instead of full MEMORY…
Token-Aware Startup Context
Automatically generates a compact sessioncontext.md for OpenClaw session bootstrapping, reducing token usage on every ne…
Integrations
Adapters
OpenClaw adapters, Memory Contract v1 + v1.1, opt-in access-aware helpers (LACCESS_*).
AI Native Lang (AINL) for OpenClaw - Integration Guide
This document sketches how to expose OpenClaw actions as AINL adapters so that AINL programs can drive OpenClaw workflow…
AIRTABLE
Status: runtime adapter implementation + strict contract wiring.
Code context adapter (`code_context`)
codecontext is an optional AINL runtime adapter for tiered codebase context: index a local tree into a JSON file, then q…
Export workflow advisory results to JSONL
> OpenClaw (MCP skill): ../OPENCLAWINTEGRATION.md(../OPENCLAWINTEGRATION.md) — skills/openclaw/, ainl install-mcp --host…
or
Status: runtime adapter implementation + strict contract wiring.
or
Status: runtime adapter implementation + strict contract wiring.
or
Status: runtime adapter implementation + strict contract wiring.
or
Status: runtime adapter implementation + strict contract wiring.
Advanced
Agent coordination contracts and safe-use / threat model.
Competitive & comparisons
AINL vs LangGraph / Temporal, benchmark methodology, comparison tables.
Competitive & comparisons
One line: If you are weighing AINL against LangGraph, Temporal, CrewAI, or prompt-loop orchestration, start here — we se…
AINL + Temporal: best of both worlds
Temporal gives you durable execution, retries, and worker infrastructure. AINL gives you a compact authoring surface, st…
Comparison tables (committed data only)
Figures below are copied from committed artifacts only — BENCHMARK.md, tooling/benchmarksize.json, tooling/benchmarkrunt…
Competitive Differentiation Messaging
Strategic messaging framework for positioning AINL against LangGraph, Temporal, and other AI workflow tools.
From LangGraph to AINL in 15 minutes
If you already think in graphs and tool nodes, AINL should feel familiar — with one shift: the workflow is a compact pro…
Real OpenClaw production savings (template)
This page is a worksheet for teams documenting operational AI workflows that use AINL through OpenClaw (or ZeroClaw / Ne…
Versus LangGraph / Temporal: benchmark methodology
AINL’s public size and runtime benchmarks are reproducible from this repository. They are not a substitute for your prod…
Migration
Enterprise
Enterprise AINL: Frequently Asked Questions
Last updated: March 2026
Enterprise Support SLA
Service: AINL Hosted Runtime & Enterprise Features Effective Date: March 2026 Last Updated: March 30, 2026 Customers: En…
Metrics Dashboard & Monitoring Plan
Define KPIs, dashboards, and alerting for AINL adoption and operational health.
SOC 2 alignment checklist (AINL)
This document helps security and GRC teams map AINL deployments to common SOC 2 (Trust Services Criteria) expectations. …
Validation Transparency Framework
Technical specification for AINL's compile-time validation system and audit dashboard.
Community
AINL Champions Program
The AINL Champions Program recognizes and rewards community members who make a significant impact on the ecosystem.
Community spotlights
Monthly highlights of real AINL programs, contributors, and outcomes. Entries are curated; submit ideas via GitHub Discu…
Discussion: Enterprise audit & compliance use cases
Title (paste as discussion title)
Discussion: LangGraph → AINL migration experiences
Title (paste as discussion title)
Discussion: Share your first AINL workflow
Title (paste as discussion title)
GitHub Discussions — exact posts (title + body)
Live threads (created March 2026):
GitHub Discussions — seed topics (copy-paste)
Use this file to seed the AINL GitHub Discussions(https://github.com/sbhooley/ainativelang/discussions) forum.
Social announcement templates (X / Telegram)
Short copy for maintainers and community advocates. Replace LINKS with the current URLs before posting. Tone: profession…
General
General docs: install, OpenClaw, ZeroClaw & Hermes integration, glossary, integration story, and more.
AINL Growth Plan - Mirofish-Inspired (March 2026)
90-day milestones and community-first growth strategy for sustainable AINL adoption.
Validation Deep Dive
Reachability analysis, strict diagnostics, and JSONL execution tape for transparent workflow validation.
Adapter Developer Guide
AINL adapters allow pluggable integration with LLM providers and external tools. This guide explains how to add new adap…
AI Agent Continuity Guide
This project is intentionally designed for multi-session, multi-agent development. Use this guide to continue work safel…
AI Native Lang (AINL) Fine‑Tuning Quick Start
This guide trains a small model (<4GB) to generate correct AINL programs. Target hardware: MacBook Pro M2 (16GB RAM) or …
AI Native Lang (AINL) Open Core Charter (Draft)
This charter defines how AINL will balance ecosystem adoption with sustainable commercial development.
AI Native Lang (AINL) Patterns Library (v0.9 profile, 1.0-compatible)
This file describes named graph/label patterns that small models can reuse instead of re‑inventing common control flows.
AI Native Lang (AINL) Runtime Release Readiness
This document summarizes the current production-hardening surface and where each capability is implemented and validated…
Launch & Release
Release announcements, publish checklists, and GitHub release bodies.
AINL v1.1.0 — Short-Form Announcement Drafts
Use these for X/Twitter, LinkedIn, Hacker News, Reddit, or similar.
GITHUB RELEASE BODY
AINL is the open language for deterministic AI workflows. It compiles structured workflows to canonical graph IR and exe…
PUBLISH CHECKLIST
1. Confirm final tag: v1.1.0 2. Confirm final release title: AINL v1.1.0 — First Public GitHub Release (Open-Core Baseli…
SHORT POST
AINL v1.1.0 is out as the first public GitHub release baseline.
TECHNICAL POST
AINL v1.1.0 marks the first public GitHub release of the project as an open-core baseline.
Issues
Post-baseline GitHub issues, migration plans, and compatibility paths (see Release notes for shipped v1.2.x).
Post-v1.1.0 Issue Creation Plan
Suggested milestone/grouping for all items below: Post-v1.1.0
Title
Promote compiler structured diagnostics to first-class default contract
Title
Plan and execute migration of non-strict/legacy artifacts toward strict-valid coverage
Title
Define phased retirement plan for compatibility-only runtime/compiler paths
Title
Formalize strict adapter contract expansion policy for newly supported runtime adapters
Title
Post-release docs/onboarding tightening based on first external contributor feedback
Learning
Adapters Tutorial: Building a Multi-Adapter Graph
> ℹ️ TWO SYNTAX STYLES: This document shows two AINL syntax styles: > 1. Compact syntax (works now) — Python-like, recom…
Build Your First Agent (30-Minute Tutorial)
In this tutorial, you'll build a monitoring agent that watches a log file, classifies errors, and sends alerts. This is …
Cache Warmup Pattern
> ℹ️ TWO SYNTAX STYLES: This document shows two AINL syntax styles: > 1. Compact syntax (works now) — Python-like, recom…
Data Validation Pipeline Pattern
> ℹ️ TWO SYNTAX STYLES: This document shows two AINL syntax styles: > 1. Compact syntax (works now) — Python-like, recom…
Email Alert Classifier Pattern
> ℹ️ TWO SYNTAX STYLES: This document shows two AINL syntax styles: > 1. Compact syntax (works now) — Python-like, recom…
Emitters Tutorial: Deploy to LangGraph and Temporal
> ℹ️ TWO SYNTAX STYLES: This document shows two AINL syntax styles: > 1. Compact syntax (works now) — Python-like, recom…
Graphs & Intermediate Representation (IR)
> ℹ️ TWO SYNTAX STYLES: This document shows two AINL syntax styles: > 1. Compact syntax (works now) — Python-like, recom…
Idempotent API Calls Pattern
> ℹ️ TWO SYNTAX STYLES: This document shows two AINL syntax styles: > 1. Compact syntax (works now) — Python-like, recom…
Reactive
Advanced Durability Patterns for Reactive Graphs
No new adapter code required - use existing redis and postgres adapters in your graphs.
How to Get Started with Reactive Graphs in AINL
Build event-driven AI workflows that automatically react to database changes, realtime events, and pub/sub messages usin…
REACTIVE EVENTS
AINL treats reactive workflows (change feeds, pub/sub, webhooks) as first-class but bounded event sources that feed into…
