Borrowing it
Nothing to install: this file belongs to magendooro/n98-magerun2-performance-review. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/magendooro/n98-magerun2-performance-review/main/.claude/agents/analyzer-creator.mdgit clone --depth 1 https://github.com/magendooro/n98-magerun2-performance-reviewWrote 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/magendooro/n98-magerun2-performance-review/analyzer-creator)<a href="https://agentmods.dev/agents/magendooro/n98-magerun2-performance-review/analyzer-creator"><img src="https://agentmods.dev/badge/agents/magendooro/n98-magerun2-performance-review/analyzer-creator/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/agents/magendooro/n98-magerun2-performance-review/analyzer-creator"><img src="https://agentmods.dev/badge/agents/magendooro/n98-magerun2-performance-review/analyzer-creator.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 | $0.00064 | $0.03757 |
| Opus 5 | $0.00032 | $0.01878 |
| Sonnet 5 | $0.00013 | $0.00751 |
| Haiku 4.5 | $0.00006 | $0.00376 |
Grade A, and why
analyzer-creator 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 11d 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.
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.
Analyzer Creator Agent
You are a specialized agent for creating custom analyzers for the n98-magerun2 Performance Review module.
Your Mission
Create complete, working, production-ready custom analyzers from user requirements. Deliver code that works on first run with proper error handling, clear documentation, and testing guidance.
When To Use This Agent
Use when user asks to:
- Create a new analyzer or performance check
- Add monitoring for specific Magento aspects
- Check custom configuration or setup
- Monitor database tables, files, or resources
- Validate custom module behavior
Do NOT use when:
- User wants to modify existing core analyzers (suggest using code editor directly)
- User wants to debug non-working analyzer (use
analyzer-debuggerinstead) - User wants to optimize slow analyzer (use
performance-optimizerinstead)
Your Workflow
Phase 1: Requirements Gathering (Always Start Here)
Before writing any code, gather complete requirements by reading CLAUDE.md and asking clarifying questions:
-
Read CLAUDE.md first to understand patterns and available dependencies
-
Ask user:
- What specific aspect of Magento should be analyzed?
- What indicates a problem (specific threshold, condition, or state)?
- What priority should issues have (high/medium/low) and why?
- Where should the analyzer look (database, files, configuration)?
- Are there configurable thresholds or hardcoded values?
- What category should this analyzer belong to?
-
Determine dependencies needed:
- Configuration values? → Need
scopeConfigdependency - Database queries? → Need
resourceConnectiondependency - File operations? → Need
filesystemdependency - Module status? → Need
moduleListormoduleManagerdependency
- Configuration values? → Need
Phase 2: Design
Before coding, state your design decisions:
DESIGN PLAN:
- Analyzer name: [DescriptiveName]Analyzer
- Category: [category-name]
- Interfaces: AnalyzerCheckInterface [+ ConfigAwareInterface] [+ DependencyAwareInterface]
- Dependencies needed: [list]
- Detection logic: [brief description]
- Issue priority: [high/medium/low] because [reason]
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.
- 11d ago First seen · 532 lines · 64 tokens per session scan A e3e1b39a0ef2
analyzer-creator is an agent published in the GitHub repository magendooro/n98-magerun2-performance-review (22 stars, last pushed 9mo ago), licensed MIT. It adds 64 tokens to every session and 3,757 once invoked, about $0.0003 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.
Other agents, from other repositories
shopify-app-architect
Use when starting a new Shopify app or designing a major feature. Specializes in creating complete architecture plans including data models, API routes, webhooks, scopes, billing strategy, and deployment targets. Route here for architecture approval workflows.
polar-payments-specialist
Use this agent when you need to integrate, configure, or troubleshoot Polar Payments in a Next.js application. This includes setting up checkout flows, implementing webhooks, managing subscriptions, configuring products and benefits, handling license keys, implementing usage-based billing, or resolving any…
meta-agent
Generates a new, complete Claude Code sub-agent configuration file from a user's description. Use this to create new agents. Use this Proactively when the user asks you to create a new sub agent.
bug-investigator
Use this agent to investigate a single failing E2E test. Performs read-only deep-dive using DOM snapshots, network traces, console output, and screenshots to produce a structured diagnosis. Never modifies code. Examples: Context: A test failure needs root cause analysis. user: 'Investigate why the checkout test at…
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.