What is neural-patterns?

A neural-learning feature for improving how coding agents search, edit files, split up tasks, and coordinate with one another.

Train or inspect coordination patterns, analyze recent edits, and monitor learning across sessions.

It uses successful past operations to refine future agent behavior and track changes in learned patterns.

neural-patterns — Command for Claude Code by natea

Install

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.

Clone the repo

git clone --depth 1 https://github.com/natea/ExoMind

Made for: Claude Code.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/commands/natea/exomind/neural-patterns.svg)](https://agentmods.dev/commands/natea/exomind/neural-patterns)

Your own site

<a href="https://agentmods.dev/commands/natea/exomind/neural-patterns"><img src="https://agentmods.dev/badge/commands/natea/exomind/neural-patterns.svg" alt="Measured on agentmods" height="20"></a>

Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.

When invoked 399 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin 92% copy Near-identical to another mod in the catalogue.

Token cost

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	$0.00000	$0.00399
Opus 5	$0.00000	$0.00199
Sonnet 5	$0.00000	$0.00080
Haiku 4.5	$0.00000	$0.00040

Measured 3d ago against content hash 80ea2d4261c4, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

neural-patterns 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 3d 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.

Origin

This is a copy

92% identical to neural-patterns — 31 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.

.claude/commands/training/neural-patterns.md · 74 lines

What it actually says

Neural Pattern Training

Purpose

Continuously improve coordination through neural network learning.

How Training Works

1. Automatic Learning

Every successful operation trains the neural networks:

Edit patterns for different file types
Search strategies that find results faster
Task decomposition approaches
Agent coordination patterns

2. Manual Training

Tool: mcp__claude-flow__neural_train
Parameters: {
  "pattern_type": "coordination",
  "training_data": "successful task patterns",
  "epochs": 50
}

3. Pattern Types

Cognitive Patterns:

Convergent: Focused problem-solving
Divergent: Creative exploration
Lateral: Alternative approaches
Systems: Holistic thinking
Critical: Analytical evaluation
Abstract: High-level design

4. Improvement Tracking

Tool: mcp__claude-flow__neural_status
Result: {
  "patterns": {
    "convergent": 0.92,
    "divergent": 0.87,
    "lateral": 0.85
  },
  "improvement": "5.3% since last session",
  "confidence": 0.89
}

Pattern Analysis

Tool: mcp__claude-flow__neural_patterns
Parameters: {
  "action": "analyze",
  "operation": "recent_edits"
}

Benefits

🧠 Learns your coding style
📈 Improves with each use
🎯 Better task predictions
⚡ Faster coordination

CLI Usage

# Train neural patterns via CLI
npx claude-flow neural train --type coordination --epochs 50

# Check neural status
npx claude-flow neural status

# Analyze patterns
npx claude-flow neural patterns --analyze

Changes

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.

3d ago First seen · 74 lines · 0 tokens per session scan A 80ea2d4261c4

Subscribe to this mod's changes

neural-patterns is a command published in the GitHub repository natea/ExoMind (21 stars, last pushed 10mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 399 tokens. A static security scan graded it A with 0 findings. It is 92% identical to neural-patterns, differing in 31 lines, and is treated as a copy.

Building agents

neural-patterns