How do I install the Load Testing skill?

Run npx skillmds@latest add ashutoshsrivastava17/load-testing in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Load Testing safe to use?

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Which AI agents work with Load Testing?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Load Testing free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Load Testing?

ashutoshsrivastava17 (@ashutoshsrivastava17) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Load Testing by ashutoshsrivastava17

Name: Load Testing
Author: ashutoshsrivastava17

Load Testing

Plan load testing — workload modeling, user journey scripts, ramp-up profiles, SLA thresholds, bottleneck identification, and capacity recommendations. TRIGGER when: user says /load-testing, needs to plan performance testing, or asks about stress testing and capacity validation.

File contents

Load Testing Plan

Process

Step 1: Define Test Objectives

Test Type	Purpose	When to Use
Load test	Validate under expected load	Pre-release
Stress test	Find breaking point	Capacity planning
Soak test	Find memory leaks, degradation	Pre-release
Spike test	Handle sudden traffic surges	Event planning

Step 2: Model Workload

Scenario	Requests/sec	User Pattern	% of Traffic
Browse catalog	X rps	Read-heavy	X%
Search	X rps	CPU-intensive	X%
Checkout	X rps	Write + external calls	X%
API integration	X rps	Burst pattern	X%

Step 3: Design Ramp-Up Profile

Phase	Duration	Load	Purpose
Warmup	5 min	10% target	Cache warmup
Ramp	10 min	10% → 100%	Gradual increase
Steady state	30 min	100% target	Sustained load
Peak	10 min	150% target	Headroom validation
Cool down	5 min	Decrease to 0	Graceful degradation

Step 4: Set SLA Thresholds

Metric	Target	Failure Threshold
p50 latency	< 200ms	> 500ms
p95 latency	< 500ms	> 2000ms
p99 latency	< 1000ms	> 5000ms
Error rate	< 0.1%	> 1%
Throughput	X rps	< 80% target

Step 5: Execute and Monitor

Monitor	What to Watch
Application	Latency, error rate, throughput
Infrastructure	CPU, memory, disk I/O, network
Database	Query time, connections, locks
External deps	API latency, timeout rate

Step 6: Analyze and Recommend

Bottleneck	Evidence	Recommendation
[component]	[metric at failure]	[scaling/optimization]

Output Format

## Load Test Report: [System]
### Test Config: [Type, duration, peak load]
### Results Summary
| Metric | Target | Actual | Status |
|--------|--------|--------|--------|
### Bottlenecks: [Identified with evidence]
### Capacity: [Max sustainable load]
### Recommendations: [Scaling/optimization actions]

Quality Checklist

Workload model reflects production patterns
Test environment matches production (or scaled proportionally)
SLA thresholds defined before testing
All system layers monitored during test
Results analyzed for bottlenecks
Recommendations are specific and actionable

Edge Cases

For serverless, test cold start impact under load
For distributed systems, test cross-region latency
If test env differs from prod, document scaling assumptions

---name: load-testingdescription: Plan load testing — workload modeling, user journey scripts, ramp-up profiles, SLA thresholds, bottleneck identification, and capacity recommendations. TRIGGER when: user says /load-testing, needs to plan performance testing, or asks about stress testing and capacity validation.---# Load Testing Plan## Process### Step 1: Define Test Objectives| Test Type | Purpose | When to Use ||-----------|---------|------------|| Load test | Validate under expected load | Pre-release || Stress test | Find breaking point | Capacity planning || Soak test | Find memory leaks, degradation | Pre-release || Spike test | Handle sudden traffic surges | Event planning |### Step 2: Model Workload| Scenario | Requests/sec | User Pattern | % of Traffic ||----------|-------------|-------------|-------------|| Browse catalog | X rps | Read-heavy | X% || Search | X rps | CPU-intensive | X% || Checkout | X rps | Write + external calls | X% || API integration | X rps | Burst pattern | X% |### Step 3: Design Ramp-Up Profile| Phase | Duration | Load | Purpose ||-------|----------|------|---------|| Warmup | 5 min | 10% target | Cache warmup || Ramp | 10 min | 10% → 100% | Gradual increase || Steady state | 30 min | 100% target | Sustained load || Peak | 10 min | 150% target | Headroom validation || Cool down | 5 min | Decrease to 0 | Graceful degradation |### Step 4: Set SLA Thresholds| Metric | Target | Failure Threshold ||--------|--------|------------------|| p50 latency | < 200ms | > 500ms || p95 latency | < 500ms | > 2000ms || p99 latency | < 1000ms | > 5000ms || Error rate | < 0.1% | > 1% || Throughput | X rps | < 80% target |### Step 5: Execute and Monitor| Monitor | What to Watch ||---------|-------------|| Application | Latency, error rate, throughput || Infrastructure | CPU, memory, disk I/O, network || Database | Query time, connections, locks || External deps | API latency, timeout rate |### Step 6: Analyze and Recommend| Bottleneck | Evidence | Recommendation ||-----------|----------|---------------|| [component] | [metric at failure] | [scaling/optimization] |## Output Format```markdown## Load Test Report: [System]### Test Config: [Type, duration, peak load]### Results Summary| Metric | Target | Actual | Status ||--------|--------|--------|--------|### Bottlenecks: [Identified with evidence]### Capacity: [Max sustainable load]### Recommendations: [Scaling/optimization actions]```## Quality Checklist- [ ] Workload model reflects production patterns- [ ] Test environment matches production (or scaled proportionally)- [ ] SLA thresholds defined before testing- [ ] All system layers monitored during test- [ ] Results analyzed for bottlenecks- [ ] Recommendations are specific and actionable## Edge Cases- For serverless, test cold start impact under load- For distributed systems, test cross-region latency- If test env differs from prod, document scaling assumptions

Frequently asked questions