Neuron AI is a PHP framework for building AI applications in which agents connect language models, tools, data loaders, vector databases, memory, and user interfaces. PHP developers use it to create and manage applications with agent workflows, multi-agent coordination, streaming, monitoring, and human involvement.
Borrowing it
Nothing to install: this file belongs to neuron-core/neuron-ai. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/neuron-core/neuron-ai/4.x/AGENTS.mdgit clone --depth 1 https://github.com/neuron-core/neuron-aiWrote 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.
[](https://agentmods.dev/instructions/neuron-core/neuron-ai/agents-md)<a href="https://agentmods.dev/instructions/neuron-core/neuron-ai/agents-md"><img src="https://agentmods.dev/badge/instructions/neuron-core/neuron-ai/agents-md/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.
<a href="https://agentmods.dev/instructions/neuron-core/neuron-ai/agents-md"><img src="https://agentmods.dev/badge/instructions/neuron-core/neuron-ai/agents-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.01599 | $0.01599 |
| Opus 5.5 | $0.00640 | $0.00640 |
| Sonnet 5.5 | $0.00320 | $0.00320 |
| Haiku 4.5 | $0.00160 | $0.00160 |
Grade A, and why
neuron-ai AGENTS.md 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 7d 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.
How it starts
The opening of the file, as written. The whole thing — 132 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Neuron AI - Project Overview
This repository contains Neuron AI, a PHP framework for building agentic applications.
The Mental Model: Neuron Is a Composable Workflow
Before writing any Neuron code, internalize this — it shapes every correct decision:
-
Workflow is the foundation. Everything else is built on it. A Workflow is an event-driven graph of nodes that you can compose freely to create any agentic behaviour.
-
A catalog of components, wired by interfaces. Neuron ships a large collection of standalone, interchangeable building blocks — AI providers, the messaging layer, chat history, tools & toolkits, structured output, RAG, vector stores, data loaders, MCP, observability. They are connected by small, focused interfaces, so each can be used on its own or swapped for your own implementation.
-
Agentis an inspiration, not a cage. TheAgentclass is itself a Workflow: it composes the components above (chat/stream/structured nodes, tools, history, middleware) into a ready-to-use agentic entity. Study it to see how a Workflow is assembled. Then choose your path:- Extend
Agentwhen its defaults fit your use case (most common starting point). - Customize
Agentby swapping nodes or adding middleware when you need targeted changes without rebuilding from scratch. - Compose your own Workflow from the component catalog when you need bespoke control flow —
AgentandRAGcan even be used as nodes inside it.
- Extend
You never fight the framework: the architecture you use on day one is the same one running your most complex system later.
Modules
| Module | Purpose | Dependencies |
|---|---|---|
src/Workflow/ |
Event-driven orchestration, nodes, interruptions, persistence | Observability |
src/Agent/ |
AI agent with chat/stream/structured modes | Workflow, Chat, Providers, Tools |
src/Chat/ |
Messages, stream content blocks, chat history | None |
src/Providers/ |
AI provider abstractions (Anthropic, OpenAI, etc.) | Chat, HttpClient |
src/Tools/ |
Tool system and built-in toolkits | None |
src/RAG/ |
Document retrieval and vector stores | Agent, VectorStore |
src/StructuredOutput/ |
JSON schema extraction | Chat |
src/HttpClient/ |
HTTP client abstraction | None |
src/MCP/ |
Model Context Protocol connector | HttpClient |
src/Observability/ |
PSR-14 event dispatching and observers | Workflow |
src/Console/ |
CLI commands (make:*, evaluation) | Evaluation |
src/Evaluation/ |
AI evaluation framework (incl. multi-turn conversation eval) | Agent, Chat, Workflow, Tools |
src/Testing/ |
Test fakes and utilities | Providers |
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.
- 7d ago Changed · +1 lines · +25 tokens per session 0350bd6223c9
- 1mo ago Changed · -2 lines · -27 tokens per session 98dc9cc2ede9
- 1mo ago Changed · -6 lines · +151 tokens per session d70dd21ba8cd
- 2mo ago First seen · 139 lines · 1,450 tokens per session scan A 9adfbe2f739f
neuron-ai AGENTS.md is an instructions file published in the GitHub repository neuron-core/neuron-ai (2,166 stars, last pushed yesterday), licensed MIT. It adds 1,599 tokens to every session, about $0.0064 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 2026-08-30.
neuron-ai AGENTS.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| neuron-ai AGENTS.mdneuron-core/neuron-ai | Instructions file | 2.2k | yesterday | MIT | A | 1,599 | Codex, OpenCode |
| vscode buildNext.instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 9,719 | GitHub Copilot |
| next.js AGENTS.mdvercel/next.js | Instructions file | 143k | today | MIT | A | 7,461 | Codex, OpenCode |
| langchain AGENTS.mdlangchain-ai/langchain | Instructions file | 149k | today | MIT | A | 4,680 | Codex, OpenCode |
| vscode oss-third-party-notices.instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 5,516 | GitHub Copilot |
| vscode copilot-instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 3,093 | GitHub Copilot |
| deepseek-harness AGENTS.mddeepseek-ai/deepseek-harness | Instructions file | 274k | 2d ago | MIT | A | 4,313 | Codex, OpenCode |