---
name: performance-baseline-capturer-dff5a4df903e
description: Capture performance baselines before migration for regression comparison and SLA verification
allowed-tools: ["Bash", "Read", "Write", "Grep", "Glob", "Edit"]
graph:
  domains: [domain:software-engineering]
  specializations: [specialization:code-migration-modernization]
  skillAreas: [skill-area:performance-testing, skill-area:performance-monitoring-profiling]
  roles: [role:backend-engineer, role:sre]
  workflows: [workflow:technical-debt-reduction]
  topics: [topic:refactoring]
---

# Performance Baseline Capturer Skill

Captures comprehensive performance baselines before migration to enable post-migration regression comparison and SLA verification.

## Purpose

Enable performance benchmarking for:
- Response time measurement
- Throughput baseline
- Resource utilization tracking
- Load test execution
- Percentile calculation

## Capabilities

### 1. Response Time Measurement
- Capture response times
- Measure latency percentiles
- Track by endpoint
- Document SLA targets

### 2. Throughput Baseline
- Measure requests per second
- Track concurrent users
- Document peak capacity
- Establish limits

### 3. Resource Utilization Tracking
- Monitor CPU usage
- Track memory consumption
- Measure disk I/O
- Record network usage

### 4. Load Test Execution
- Run baseline load tests
- Execute stress tests
- Perform soak tests
- Document results

### 5. Percentile Calculation
- Calculate P50/P90/P95/P99
- Track distribution
- Identify outliers
- Set thresholds

### 6. Regression Threshold Setting
- Define acceptable ranges
- Set alert thresholds
- Document tolerances
- Create comparison criteria

## Tool Integrations

| Tool | Purpose | Integration Method |
|------|---------|-------------------|
| JMeter | Load testing | CLI |
| Gatling | Performance testing | CLI |
| k6 | Modern load testing | CLI |
| Locust | Python load testing | CLI |
| Artillery | Node.js testing | CLI |
| wrk | HTTP benchmarking | CLI |

## Output Schema

```json
{
  "baselineId": "string",
  "timestamp": "ISO8601",
  "environment": {
    "name": "string",
    "resources": {}
  },
  "metrics": {
    "responseTime": {
      "p50": "number",
      "p90": "number",
      "p95": "number",
      "p99": "number",
      "mean": "number"
    },
    "throughput": {
      "requestsPerSecond": "number",
      "peakRps": "number",
      "concurrentUsers": "number"
    },
    "resources": {
      "cpu": {},
      "memory": {},
      "disk": {},
      "network": {}
    }
  },
  "thresholds": {
    "responseTime": {},
    "throughput": {},
    "errors": {}
  }
}
```

## Integration with Migration Processes

- **migration-testing-strategy**: Baseline establishment
- **performance-optimization-migration**: Performance tracking

## Related Skills

- `migration-validator`: Post-migration comparison
- `test-coverage-analyzer`: Test planning

## Related Agents

- `performance-validation-agent`: Performance verification
- `migration-testing-strategist`: Test planning


---
Source attribution: a5c-ai
Original project: https://github.com/a5c-ai/babysitter
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Mega AI Hub.

## Upstream license notice

MIT License

Copyright (c) 2026 Gabriel Moreira

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.



# Mega AI Hub resource metadata

Creator / publisher: a5c-ai
Original project: https://github.com/a5c-ai/babysitter
Attribution basis: Upstream repository explicitly recorded in package mirror path

Fields of work: Data & Analytics, Development & Engineering, Product Management
Roles: Data Analyst, DevOps / SRE, Product Manager, QA / Test Engineer, Technical Product Manager
Specialties: DevOps, Testing
Tools: Artillery, Gatling, Jmeter, Locust, K6, Wrk
Country applicability: Country not specified
Classification basis: Source catalog labels
Instruction SHA-256: a3a99bed6bb0e3a3bef155a187b320f1ada931a06ef3595d1d79162b26f24946