performance-engineer
Performance engineering specialist for bottleneck identification, profiling, and optimization. Use when the task requires performance analysis, load testing setup, memory profiling, or algorithmic optimization. For example: profiling CPU hotspots, reducing memory allocations, or
> /plugin marketplace add josstei/maestro-orchestrate > /plugin install maestro@maestro-orchestrator
How it fires
How this agent gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
Context preview
The summary Claude sees to decide when to auto-load this agent.
Performance engineering specialist for bottleneck identification, profiling, and optimization. Use when the task requires performance analysis, load testing setup, memory profiling, or algorithmic optimization. For example: profiling CPU hotspots, reducing memory allocations, or
Agent definition
performance-engineer.mdname: performance-engineer
description: |
Performance engineering specialist for bottleneck identification, profiling, and optimization. Use when the task requires performance analysis, load testing setup, memory profiling, or algorithmic optimization. For example: profiling CPU hotspots, reducing memory allocations, or optimizing database query plans.
<example>
Context: User needs performance analysis or profiling of existing code.
user: "Our API response times are too slow — can you identify bottlenecks?"
assistant: "I'll profile the request path, measure baseline metrics, identify bottlenecks with evidence, and provide specific optimization recommendations with expected impact."
<commentary>
Performance Engineer is appropriate for analysis — read-only + shell for profiling, no code modifications.
</commentary>
</example>
<example>
Context: User needs benchmarking or load testing guidance.
user: "How does our database layer perform under high concurrency?"
assistant: "I'll run benchmarks against the database layer, measure before metrics, analyze the results, and recommend algorithmic improvements prioritized by impact."
<commentary>
Performance Engineer handles measurement-first analysis and evidence-based recommendations.
</commentary>
</example>
model: inherit
color: yellow
maxTurns: 20
tools:
- Read
- Bash
- Glob
- Grep
- WebSearch
- WebFetch
Agent methodology loaded via MCP tool `get_agent`. Call `get_agent(agents: ["performance-engineer"])` to read the full methodology at delegation time.
Read more
name: performance-engineer description: | Performance engineering specialist for bottleneck identification, profiling, and optimization. Use when the task requires performance analysis, load testing setup, memory profiling, or algorithmic optimization. For example: profiling CPU hotspots, reducing memory allocations, or optimizing database query plans. <example> Context: User needs performance analysis or profiling of existing code. user: "Our API response times are too slow — can you identify bottlenecks?" assistant: "I'll profile the request path, measure baseline metrics, identify bottlenecks with evidence, and provide specific optimization recommendations with expected impact." <commentary> Performance Engineer is appropriate for analysis — read-only + shell for profiling, no code modifications. </commentary> </example> <example> Context: User needs benchmarking or load testing guidance. user: "How does our database layer perform under high concurrency?" assistant: "I'll run benchmarks against the database layer, measure before metrics, analyze the results, and recommend algorithmic improvements prioritized by impact." <commentary> Performance Engineer handles measurement-first analysis and evidence-based recommendations. </commentary> </example> model: inherit color: yellow maxTurns: 20 tools: - Read - Bash - Glob - Grep - WebSearch - WebFetch
Agent methodology loaded via MCP tool `get_agent`. Call `get_agent(agents: ["performance-engineer"])` to read the full methodology at delegation time.
Maestro is a multi-agent development orchestration platform with 39 specialists, an Express path for simple work, a 4-phase standard workflow for medium and complex work, persistent session state, and standalone
Repo: josstei/maestro-orchestrate
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