# Bmad Performance Optimization

> Diagnoses bottlenecks and designs performance optimization plans.

- Skill: `majiayu000/bmad-performance-optimization` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds add majiayu000/bmad-performance-optimization`
- Raw SKILL.md: https://api.skillmd.com/api/skills/majiayu000/bmad-performance-optimization/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: majiayu000 (https://skillmd.com/u/majiayu000)
- Updated: 2026-09-09
- Page: https://skillmd.com/skills/majiayu000/bmad-performance-optimization

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# BMAD Performance Optimization Skill

## When to Invoke

Trigger this skill when the user:
- Reports latency, throughput, or resource regressions.
- Requests load/performance testing guidance or results interpretation.
- Needs to set or validate performance budgets and SLAs.
- Wants to plan scaling strategies ahead of a launch or marketing event.
- Asks how to tune code, queries, caching, or infrastructure for speed.

If the user only needs to implement a specific optimization already defined, delegate to `bmad-development-execution`.

## Mission

Deliver actionable insights, testing strategies, and prioritized optimizations that keep the product within agreed performance budgets while balancing cost and complexity.

## Inputs Required

- Current architecture diagrams and deployment topology.
- Observability data: metrics dashboards, traces, profiling dumps, load test reports.
- Performance requirements (SLAs/SLOs, budgets, target response times).
- Workload assumptions and peak usage scenarios.

Gather missing telemetry by coordinating with `bmad-observability-readiness` if instrumentation is lacking.

## Outputs

- **Performance brief** summarizing current state, key bottlenecks, and risks.
- **Benchmark and load test plan** aligning tools, scenarios, and success criteria.
- **Optimization backlog** ranked by impact vs. effort with owner and verification plan.
- Updated performance budget recommendations or SLO adjustments when necessary.

## Process

1. Validate inputs and ensure instrumentation coverage. Escalate gaps to observability skill.
2. Analyze telemetry to pinpoint hotspots (CPU, memory, I/O, DB, network, frontend paint times).
3. Assess architecture decisions for scalability (caching, asynchronous workflows, data partitioning).
4. Define performance goals and acceptance thresholds with stakeholders.
5. Create load/benchmark plans covering baseline, stress, soak, and spike scenarios.
6. Recommend optimizations across code, database, infrastructure, and CDN layers.
7. Produce backlog with measurable acceptance criteria and regression safeguards.

## Quality Gates

- Recommendations trace back to observed data or projected workloads.
- Each backlog item includes measurement approach (before/after metrics).
- Performance budgets and SLAs updated or reaffirmed.
- Risks communicated when goals require major architectural change.

## Error Handling

- If telemetry contradicts assumptions, schedule hypothesis-driven experiments rather than guessing.
- Flag when performance targets are unrealistic within constraints; propose trade-offs.
- When required tooling is unavailable, document blockers and coordinate with observability & dev skills.