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.
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-ai --skill neuron-structured-outputgit 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/skills/neuron-core/neuron-ai/neuron-structured-output)<a href="https://agentmods.dev/skills/neuron-core/neuron-ai/neuron-structured-output"><img src="https://agentmods.dev/badge/skills/neuron-core/neuron-ai/neuron-structured-output/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/skills/neuron-core/neuron-ai/neuron-structured-output"><img src="https://agentmods.dev/badge/skills/neuron-core/neuron-ai/neuron-structured-output.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00104 | $0.04678 |
| Opus 5.5 | $0.00042 | $0.01871 |
| Sonnet 5.5 | $0.00021 | $0.00936 |
| Haiku 4.5 | $0.00010 | $0.00468 |
Grade A, and why
neuron-structured-output 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 20d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- neuron-structured-output — 100% identical, 11 lines differ
How it starts
The opening of the file, as written. The whole thing — 858 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Neuron AI Structured Output
This skill helps you create structured output classes for extracting typed data from LLM responses in Neuron AI applications.
Core Concept
Neuron AI uses a two-layer approach for structured output:
- SchemaProperty - Controls the JSON schema sent to the LLM to guide generation
- Validation Rules - Verifies the LLM response meets your requirements
use NeuronAI\StructuredOutput\SchemaProperty;
use NeuronAI\StructuredOutput\Validation\Rules\NotBlank;
class Person
{
#[SchemaProperty(description: 'The user name.', required: true)]
#[NotBlank]
public string $name;
}
SchemaProperty Attribute
The SchemaProperty attribute defines how properties are represented in the JSON schema sent to the LLM.
Constructor Arguments
#[SchemaProperty(
string $title = null, // Property title in JSON schema
string $description = null, // Property description (guides LLM)
bool $required = null, // Override required status
int $min = null, // Minimum value (numbers) or items (arrays)
int $max = null, // Maximum value (numbers) or items (arrays)
int $minLength = null, // Minimum string length
int $maxLength = null, // Maximum string length
array $anyOf = null, // Array of allowed class/enum types
)]
Argument Implications
| Argument | JSON Schema Output | Usage |
|---|---|---|
title |
title: "..." |
Human-readable property title |
description |
description: "..." |
Critical: Guides LLM on what to generate |
required: true |
Adds to required array |
Property must be present |
required: false |
Excludes from required |
Property is optional |
min |
minimum (numbers) or minItems (arrays) |
Lower bound constraint |
max |
maximum (numbers) or maxItems (arrays) |
Upper bound constraint |
minLength |
minLength |
Minimum string characters |
maxLength |
maxLength |
Maximum string characters |
anyOf |
anyOf: [...] |
Polymorphic types (multiple possible classes) |
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.
- 20d ago Changed · +5 lines 3fbd293d57af
- 1mo ago First seen · 853 lines · 104 tokens per session scan A d2f589ef4810
neuron-structured-output is a skill published in the GitHub repository neuron-core/neuron-ai (2,148 stars, last pushed yesterday), licensed MIT. It adds 104 tokens to every session and 4,678 once invoked, about $0.0004 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.
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