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 agentmods add skills/neuron-core/neuron-ai/neuron-test-engineernpx skills add neuron-core/neuron-ai --skill neuron-test-engineergit 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-test-engineer)<a href="https://agentmods.dev/skills/neuron-core/neuron-ai/neuron-test-engineer"><img src="https://agentmods.dev/badge/skills/neuron-core/neuron-ai/neuron-test-engineer.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 | $0.00094 | $0.04924 |
| Opus 5 | $0.00047 | $0.02462 |
| Sonnet 5 | $0.00019 | $0.00985 |
| Haiku 4.5 | $0.00009 | $0.00492 |
Grade A, and why
neuron-test-engineer 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 5d 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-test-engineer — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 733 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Neuron AI Test Engineer
This skill helps you write comprehensive tests for Neuron AI applications using the built-in testing utilities in NeuronAI\Testing.
Testing Philosophy
Neuron AI provides fake implementations that:
- Never make real API calls - All AI provider calls are mocked
- Record all interactions - Inspect what was sent and when
- Provide fluent assertions - PHPUnit-style assertions for verification
Core Testing Utilities
1. FakeAIProvider
The primary tool for testing agents without real AI API calls.
use NeuronAI\Testing\FakeAIProvider;
use NeuronAI\Chat\Messages\AssistantMessage;
use NeuronAI\Chat\Messages\UserMessage;
// Create with predetermined responses
$provider = new FakeAIProvider(
new AssistantMessage('Hello! How can I help you?'),
new AssistantMessage('The answer is 42.')
);
// Or use static constructor
$provider = FakeAIProvider::make(
new AssistantMessage('Response 1'),
new AssistantMessage('Response 2')
);
Key Features:
- Responses are returned sequentially from queue
- Supports
chat(),stream(), andstructured()methods - Records all requests for assertion
2. FakeVectorStore
For testing RAG systems without real vector databases.
use NeuronAI\Testing\FakeVectorStore;
use NeuronAI\RAG\Document;
// Pre-populate with search results
$vectorStore = new FakeVectorStore([
new Document('France is a country in Europe. Its capital is Paris.'),
new Document('Germany is a country in Europe. Its capital is Berlin.'),
]);
// Or create empty and set results later
$vectorStore = FakeVectorStore::make();
$vectorStore->setSearchResults([
new Document('Relevant document content')
]);
3. FakeEmbeddingsProvider
For testing embeddings without real API calls.
use NeuronAI\Testing\FakeEmbeddingsProvider;
// Create with default dimensions (8)
$embeddings = new FakeEmbeddingsProvider();
// Or specify dimensions
$embeddings = new FakeEmbeddingsProvider(dimensions: 1536);
// Use static constructor
$embeddings = FakeEmbeddingsProvider::make();
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.
- 5d ago First seen · 733 lines · 94 tokens per session scan A 357c13bd67ee
neuron-test-engineer is a skill published in the GitHub repository neuron-core/neuron-ai (2,087 stars, last pushed yesterday), licensed MIT. It adds 94 tokens to every session and 4,924 once invoked, about $0.0005 per session on Opus 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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