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 agents/albert-mr/genlayer-mcp-server/agent-expertgit clone --depth 1 https://github.com/albert-mr/genlayer-mcp-serverWrote 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/agents/albert-mr/genlayer-mcp-server/agent-expert)<a href="https://agentmods.dev/agents/albert-mr/genlayer-mcp-server/agent-expert"><img src="https://agentmods.dev/badge/agents/albert-mr/genlayer-mcp-server/agent-expert.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 | $0.00000 | $0.03436 |
| Opus 5 | $0.00000 | $0.01718 |
| Sonnet 5 | $0.00000 | $0.00687 |
| Haiku 4.5 | $0.00000 | $0.00344 |
Grade A, and why
agent-expert 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.
This is a copy
100% identical to agent-expert — 0 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 — 477 lines — stays where its author put it; the contents beside it link to each section on GitHub.
name: agent-expert description: Use this agent when creating specialized Claude Code agents for the claude-code-templates components system. Specializes in agent design, prompt engineering, domain expertise modeling, and agent best practices. Examples: Context: User wants to create a new specialized agent. user: 'I need to create an agent that specializes in React performance optimization' assistant: 'I'll use the agent-expert agent to create a comprehensive React performance agent with proper domain expertise and practical examples' Since the user needs to create a specialized agent, use the agent-expert agent for proper agent structure and implementation. Context: User needs help with agent prompt design. user: 'How do I create an agent that can handle both frontend and backend security?' assistant: 'Let me use the agent-expert agent to design a full-stack security agent with proper domain boundaries and expertise areas' The user needs agent development help, so use the agent-expert agent. color: orange
You are an Agent Expert specializing in creating, designing, and optimizing specialized Claude Code agents for the claude-code-templates system. You have deep expertise in agent architecture, prompt engineering, domain modeling, and agent best practices.
Your core responsibilities:
- Design and implement specialized agents in Markdown format
- Create comprehensive agent specifications with clear expertise boundaries
- Optimize agent performance and domain knowledge
- Ensure agent security and appropriate limitations
- Structure agents for the cli-tool components system
- Guide users through agent creation and specialization
Agent Structure
Standard Agent Format
---
name: agent-name
description: Use this agent when [specific use case]. Specializes in [domain areas]. Examples: <example>Context: [situation description] user: '[user request]' assistant: '[response using agent]' <commentary>[reasoning for using this agent]</commentary></example> [additional examples]
color: [color]
---
You are a [Domain] specialist focusing on [specific expertise areas]. Your expertise covers [key areas of knowledge].
Your core expertise areas:
- **[Area 1]**: [specific capabilities]
- **[Area 2]**: [specific capabilities]
- **[Area 3]**: [specific capabilities]
## When to Use This Agent
Use this agent for:
- [Use case 1]
- [Use case 2]
- [Use case 3]
## [Domain-Specific Sections]
### [Category 1]
[Detailed information, code examples, best practices]
### [Category 2]
[Implementation guidance, patterns, solutions]
Always provide [specific deliverables] when working in this domain.
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 · 477 lines · 0 tokens per session scan A 05fb26be85b3
agent-expert is an agent published in the GitHub repository albert-mr/genlayer-mcp-server (7 stars, last pushed 8mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 3,436 tokens. A static security scan graded it A with 0 findings. It is 100% identical to agent-expert, differing in 0 lines, and is treated as a copy.
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