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-agentgit 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)<a href="https://agentmods.dev/skills/neuron-core/neuron-laravel/neuron-agent"><img src="https://agentmods.dev/badge/skills/neuron-core/neuron-laravel/neuron-agent/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-laravel/neuron-agent"><img src="https://agentmods.dev/badge/skills/neuron-core/neuron-laravel/neuron-agent.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 | $0.00048 | $0.05666 |
| Opus 5.5 | $0.00019 | $0.02266 |
| Sonnet 5.5 | $0.00010 | $0.01133 |
| Haiku 4.5 | $0.00005 | $0.00567 |
Grade A, and why
neuron-agent scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 15d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
91% identical to neuron-agent — 185 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 532 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Neuron AI Agent
Agent is a composition built on Workflow. Extend it when its defaults fit, use its entry/exit hooks for additional stages, or compose a Workflow from the standalone components when control flow differs substantially. This skill covers the current major-version APIs; use the implementation's class names and signatures rather than older examples.
Use Agent::submitApprovalDecisions($decisions) for tool approval and Agent::submitToolResults($results) for deferred tool results. Both accept maps keyed by tool call ID and stage a continuation; finish with run() for an AgentState or events() for a stream.
Core Agent Structure
A Neuron agent extends the Agent class and implements key methods:
use NeuronAI\Agent\Agent;
use NeuronAI\Chat\Messages\SystemMessage;
use NeuronAI\Chat\Messages\UserMessage;
use NeuronAI\Providers\AIProviderInterface;
use NeuronAI\Providers\Anthropic\Anthropic;
class MyAgent extends Agent
{
protected function provider(): AIProviderInterface
{
return new Anthropic(
key: $_ENV['ANTHROPIC_API_KEY'],
model: $_ENV['ANTHROPIC_MODEL'],
);
}
protected function instructions(): SystemMessage|string
{
return new SystemMessage("You are a helpful AI assistant.");
}
}
Workflow Boundaries and Custom Nodes
The default path is:
AgentStartEvent → AgentStartNode → inference ⇄ tools
final response → AgentOutputEvent → AgentEndNode → StopEvent
ChatNode handles chat and streaming; StructuredOutputNode handles structured inference. Tools may pause for approval or deferred results before returning to inference. AgentOutputEvent means the final answer is available for output processing; it is not a terminal event.
nodes()rebuilds the graph from the current configuration each execution segment.entryNodes()defaults toAgentStartNode;exitNodes()defaults toAgentEndNode.- A node's
__invoke(EventType $event, AgentState $state)receives one exact routed event type.addNode()registers a handler; array order does not connect nodes, and duplicate handlers are rejected. - For preprocessing, override
startEvent()with anAgentStartEventsubclass, register a node for it inentryNodes(), and return the originalAgentStartEventto retainparent::entryNodes(). This keeps request initialization and tool-run resets inAgentStartNode. Replacing that initialization entirely requires handling those responsibilities yourself. - For postprocessing, override
exitNodes()with a node acceptingAgentOutputEvent. Return an application event to continue through another node, orStopEventto finish. Replace the default ending: includingparent::exitNodes()alongside another output handler creates a duplicate. AgentState::$requestholds instructions, messages, tools, and run options. Events route execution; collaborators such as providers and history remain node dependencies.getMessage()reads the provider response, while extra artifacts can use state keys.
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 15d ago First seen · 532 lines · 48 tokens per session scan A defafdc1d27a
neuron-agent is a skill published in the GitHub repository neuron-core/neuron-laravel (122 stars, last pushed 16d ago), licensed MIT. It adds 48 tokens to every session and 5,666 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 91% identical to neuron-agent, differing in 185 lines, and is treated as a copy.
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