bmad-performance-optimization
Diagnoses bottlenecks and designs performance optimization plans.
- Category: discovered
- Tags: github, community
- Version: 1.0.0
- Author: walid
- Downloads: 0
- GitHub stars: 11
- Updated: 2025-11-21
Download the latest version (v1.0.0) from this page.
SKILL.md
---
name: bmad-performance-optimization
description: Diagnoses bottlenecks and designs performance optimization plans.
allowed-tools: ["Read", "Write", "Grep", "Bash"]
metadata:
auto-invoke: true
triggers:
patterns:
- "performance budget"
- "optimize speed"
- "slow response"
- "profiling results"
- "latency regression"
- "load testing"
- "capacity planning"
keywords:
- performance
- latency
- throughput
- optimize
- scaling
- profiling
- benchmarking
capabilities:
- performance-audits
- load-testing-plans
- profiling-analysis
- optimization-roadmaps
- capacity-planning
prerequisites:
- bmad-architecture-design
- bmad-test-strategy
outputs:
- performance-brief
- benchmark-plan
- optimization-backlog
---
# 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.