What is specialization?

A training command that helps agents build expertise in particular file types and task areas. It uses successful edits, reviews, fixes, and optimisations as learning examples.

Creating specialised agents, checking their active expertise, and building knowledge from previous work.

It helps an agent apply more relevant knowledge when working with languages or tasks such as TypeScript, React, or testing.

specialization — Command for Claude Code by ruvnet: A training command that helps agents build expertise in…

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.

agentmods

npx agentmods add commands/ruvnet/ruv-fann/specialization

Clone the repo

git clone --depth 1 https://github.com/ruvnet/ruv-FANN

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/ruvnet/ruv-fann/specialization.svg)](https://agentmods.dev/commands/ruvnet/ruv-fann/specialization)

Your own site

<a href="https://agentmods.dev/commands/ruvnet/ruv-fann/specialization"><img src="https://agentmods.dev/badge/commands/ruvnet/ruv-fann/specialization.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 283 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. Scan, not verified.

Origin original No closer match found 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	$0.00283
Opus 5	$0.00000	$0.00142
Sonnet 5	$0.00000	$0.00057
Haiku 4.5	$0.00000	$0.00028

Measured 2d ago against content hash 1805d6a4ea2f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

Grade A, and why

specialization 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 2d 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

Copies of this mod

5 near-identical copies found in the catalogue:

specialization — 95% identical, 18 lines differ
specialization — 95% identical, 18 lines differ
specialization — 95% identical, 18 lines differ
specialization — 95% identical, 28 lines differ
specialization — 95% identical, 18 lines differ

.claude/commands/training/specialization.md · 53 lines

What it actually says

Agent Specialization Training

Purpose

Train agents to become experts in specific domains for better performance.

Specialization Areas

1. By File Type

Agents automatically specialize based on file extensions:

.js/.ts: Modern JavaScript patterns
.py: Pythonic idioms
.go: Go best practices
.rs: Rust safety patterns

2. By Task Type

Tool: mcp__ruv-swarm__agent_spawn
Parameters: {
  "type": "coder",
  "capabilities": ["react", "typescript", "testing"]
}

3. Training Process

The system trains through:

Successful edit operations
Code review patterns
Error fix approaches
Performance optimizations

4. Specialization Benefits

# Check agent specializations
Tool: mcp__ruv-swarm__agent_list
Parameters: {"filter": "active"}

Result shows expertise levels:
{
  "agents": [
    {
      "id": "coder-123",
      "specializations": {
        "javascript": 0.95,
        "react": 0.88,
        "testing": 0.82
      }
    }
  ]
}

Continuous Improvement

Agents share learnings across sessions for cumulative expertise!

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.

2d ago First seen · 53 lines · 0 tokens per session scan A 1805d6a4ea2f

Subscribe to this mod's changes

specialization is a command published in the GitHub repository ruvnet/ruv-FANN (378 stars, last pushed 27d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 283 tokens. 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 2026-09-03.

Building agents Learning and teaching

specialization