| name | pepe |
| description | Use this skill when the user wants to run HTTP load tests, benchmark endpoints, or generate traffic against a URL with configurable concurrency and request counts. |
pepe Plugin
HTTP load generator written in Rust. Send simple or advanced HTTP requests with configurable concurrency, timeouts, headers, and curl command parsing support.
Commands
Load Testing
pepe load test — Run HTTP load test against a target URL
Utility
pepe self version — Print pepe version
pepe _ _ — Passthrough to pepe CLI
Usage Examples
- "Load test https://example.com with 1000 requests"
- "Benchmark my API with 50 concurrent connections"
- "Run a POST load test with custom headers"
- "Convert a curl command into a load test"
- "Test my server with a 10-second timeout"
Installation
curl --proto '=https' --tlsv1.2 -sSf https://pepe.mhaimdat.com/install.sh | bash
Examples
pepe load test https://example.com
pepe load test https://example.com -n 1000 -c 20
pepe load test https://example.com -n 500 -c 10 -t 10
pepe load test https://api.example.com/data -n 100 -c 5 -m POST -H "Content-Type: application/json" -H "Authorization: Bearer token"
pepe load test https://example.com -n 200 -u "Mozilla/5.0"
pepe load test -n 1000 -c 10 --curl -- curl -X POST 'https://httpbin.org/post' -H 'Content-Type: application/json' -d '{"key": "value"}'
Key Features
- Simple syntax:
pepe <url> for quick tests
- Concurrent connections:
-c flag for parallelism
- Request count:
-n flag for total requests
- Timeout control:
-t flag for per-request timeout
- Custom headers:
-H flag (repeatable)
- HTTP methods:
-m flag for GET, POST, PUT, DELETE, etc.
- User-Agent:
-u flag for custom user agents
- Curl parsing:
--curl flag to parse and convert curl commands
- Rust-powered: Fast and efficient HTTP benchmarking
Notes
- Default settings: 200 requests, 50 concurrent connections, 2-second timeout
- The
--curl flag requires -- before the actual curl command
- Does not require curl to be installed when using the
--curl feature
- Results include latency percentiles and throughput metrics