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.
npx skills add neuron-core/neuron-laravel --skill neuron-agent-buildergit clone --depth 1 https://github.com/neuron-core/neuron-laravelWrote 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/skills/neuron-core/neuron-laravel/neuron-agent-builder)<a href="https://agentmods.dev/skills/neuron-core/neuron-laravel/neuron-agent-builder"><img src="https://agentmods.dev/badge/skills/neuron-core/neuron-laravel/neuron-agent-builder.svg" alt="Measured on agentmods" 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 | $0.00089 | $0.02179 |
| Opus 5 | $0.00044 | $0.01090 |
| Sonnet 5 | $0.00018 | $0.00436 |
| Haiku 4.5 | $0.00009 | $0.00218 |
Grade A, and why
neuron-agent-builder 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 8d 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.
This is a copy
95% identical to neuron-agent-builder — 11 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 381 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Neuron AI Agent Builder
This skill helps you create and configure Neuron AI agents for building agentic applications in PHP.
Core Agent Structure
A Neuron agent extends the Agent class and implements key methods:
use NeuronAI\Agent;
use NeuronAI\Agent\SystemPrompt;
use NeuronAI\Providers\AIProviderInterface;
use NeuronAI\Providers\Anthropic\Anthropic;
class MyAgent extends Agent
{
protected function provider(): AIProviderInterface
{
return new Anthropic(
key: 'ANTHROPIC_API_KEY',
model: 'ANTHROPIC_MODEL',
);
}
protected function instructions(): string
{
return (string) new SystemPrompt(
background: [
"You are a helpful AI assistant."
]
);
}
}
Agent Execution Methods
Chat Mode (Synchronous)
For standard back-and-forth conversations:
$agent = MyAgent::make();
$response = $agent->chat(
new UserMessage("Hello!")
)->getMessage();
echo $response->getContent();
Stream Mode (Real-time)
For streaming responses as chunks arrive. Chunks represents pieces of context that are generated by the model.
The TextChunk class is used to represent a piece of text, but there are other chunk types available:
NeuronAI\Chat\Messages\Chunks\TextChunkNeuronAI\Chat\Messages\Chunks\ImageChunkNeuronAI\Chat\Messages\Chunks\AudioChunkNeuronAI\Chat\Messages\Chunks\ToolCallChunkNeuronAI\Chat\Messages\Chunks\ToolResultChunk
$handler = $agent->stream(new UserMessage("Hello"));
foreach ($handler->events() as $event) {
if ($event instanceof TextChunk) {
echo $event->content;
}
}
Streaming Adapters for UI Integration
When connecting a frontend UI to an agent, use streaming adapters to format the response for specific protocols. This enables seamless integration with popular AI UI libraries.
When to use:
- Building a chat interface with React/Vue/Next.js
- Using Vercel AI SDK's
useChathook - Implementing AG-UI protocol for agent-frontend communication
- Any SSE-based real-time UI updates
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.
- 8d ago First seen · 381 lines · 89 tokens per session scan A 56f1e63bc6ec
neuron-agent-builder is a skill published in the GitHub repository neuron-core/neuron-laravel (120 stars, last pushed 2mo ago), licensed MIT. It adds 89 tokens to every session and 2,179 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 95% identical to neuron-agent-builder, differing in 11 lines, and is treated as a copy.
Other skills, from other repositories
neuron-evaluation-engineer
Create and run AI evaluations with datasets, assertions, and output drivers in Neuron AI. Use this skill whenever the user mentions evaluation, testing AI systems, creating evaluators, dataset-driven testing, assertion-based validation, or wants to measure AI system performance. Also trigger for tasks involving…
neuron-structured-output
Design and implement structured output classes for Neuron AI agents using SchemaProperty attributes and validation rules. Use this skill when the user mentions structured output, JSON schema extraction, data validation, output classes, DTOs for AI responses, extracting structured data from LLM, or configuring property…
neuron-test-engineer
Write tests for Neuron AI agents, RAG systems, workflows, and tools using the built-in testing utilities. Use this skill when the user mentions testing agents, writing unit tests, mocking AI providers, testing tool execution, verifying RAG retrieval, testing workflow behavior, or creating test cases for Neuron AI…
neuron-agent-builder
Create and configure Neuron AI agents with providers, tools, instructions, and memory. Use this skill whenever the user mentions building agents, creating AI assistants, setting up LLM-powered chat bots, configuring chat agents, or wants to create an agent that can talk, use tools, or handle conversations. Also…
neuron-debugger
Debug and monitor Neuron AI applications with Inspector APM, event observability, logging, and performance analysis. Use this skill whenever the user mentions debugging, monitoring, observability, performance analysis, tracing, Inspector, or needs to understand why an agent is behaving a certain way. Also trigger for…
wiki
Manage LLM-compiled wikis in Codex: ingest/import, shape/promote Ideas, review portfolios, track inventory/datasets, archive, compile/query/lint/audit, research/plan, manage sessions, private adapters, personal specialists, and outputs. Activates when the user mentions wiki workflows, knowledge-base management…