Performance profiling
AI coding agent runtime that makes LLMs understand your codebase with repository-aware context, memory, and continuous learning
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Profile likely hotspots and turn performance work into measurable next steps.
SKILL.md
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Performance Profiling
Trigger Signals
- the task is slow, resource-heavy, or performance-sensitive
Inspect First
- hotspot code paths, timing data, memory cues, and benchmark surfaces
Workflow
- identify the slow path and measurement surface
- isolate likely bottlenecks
- define low-risk experiments and verification
- report findings and next action
Output Contract
- hotspot summary
- likely bottlenecks
- measurement or benchmark plan
- recommended next step
Failure Modes
- no measurable baseline exists
Escalation
- escalate when optimization risks correctness or public contracts