# Api Load Tester

> Load tests API endpoints with progressive concurrency. Measures response times, error rates, throughput, and identifies breaking points. Generates a detailed report with latency percentiles, throughput curves, bottleneck analysis, and optimization recommendations.

- **Type:** Skill
- **Install:** `agentstack add skill-onewave-ai-claude-skills-api-load-tester`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [OneWave-AI](https://agentstack.voostack.com/s/onewave-ai)
- **Installs:** 0
- **Category:** [AI & ML](https://agentstack.voostack.com/c/ai-and-ml)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [OneWave-AI](https://github.com/OneWave-AI)
- **Source:** https://github.com/OneWave-AI/claude-skills/tree/main/api-load-tester
- **Website:** https://www.onewave-ai.com

## Install

```sh
agentstack add skill-onewave-ai-claude-skills-api-load-tester
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# API Load Tester

Stress-test HTTP endpoints under increasing load, identify breaking points, and produce a report with actionable recommendations.

## Contents

- `references/tool-commands.md` -- tool invocations (hey/wrk/ab/curl), default concurrency stages, per-stage data to capture.
- `references/metrics-interpretation.md` -- latency, throughput, error, breaking-point, and bottleneck classification.
- `references/output-template.md` -- exact structure for `api-load-report.md`, including ASCII charts and scaling table.
- `references/rules-and-examples.md` -- safety rules, error handling, and example invocations.

## Inputs

Collect from the user. Ask before proceeding if a required input is missing.

**Required**: endpoint URL(s) (with method, headers, body as needed); expected latency thresholds. Default thresholds if unspecified: p50 < 100ms, p95 < 300ms, p99 < 1000ms.

**Optional**: concurrent users or range (default ramp 1 to 100); authentication; request payloads; custom headers; test duration (default 10s per stage); ramp pattern (default step ramp, doubling each stage); success criteria (default 2xx); known rate limits; environment label (prod/staging/dev).

## Workflow

Follow these steps in order.

1. **Select a tool.** Check in priority order: `which hey`, `which wrk`, `which ab`, `which curl`. If none of hey/wrk/ab exist, install hey (`brew install hey` on macOS, `go install github.com/rakyll/hey@latest` on Linux with Go) or fall back to curl with bash background processes and `wait`. Verify with a single trivial request against a provided endpoint; diagnose connectivity or auth before continuing.

2. **Validate endpoints.** Send one request per endpoint with the specified method, headers, auth, and body. Confirm the status matches the success criteria and record baseline single-request latency. On failure, surface the error and ask whether to skip or fix.

3. **Design the test plan.** Build progressive concurrency stages (see `references/tool-commands.md` for the default progression), trimming or extending to the user's concurrency range. Define per-endpoint method, URL, headers, body, success codes, and timeout (default 30s). Print the plan for review before executing.

4. **Execute stages.** For each endpoint, run every concurrency stage sequentially with the selected tool, waiting 2 seconds between stages. Capture and store the per-stage metrics. See `references/tool-commands.md` for commands, request-count formula, and the metrics list.

5. **Interpret metrics.** Compute latency percentiles and profile, throughput curve and ceiling, error rates and onset, the breaking point, and the bottleneck classification. See `references/metrics-interpretation.md`.

6. **Generate the report.** Write `api-load-report.md` to the current working directory following `references/output-template.md` exactly, including ASCII throughput and latency charts.

7. **Post-report actions.** Print a 3-5 line summary to the console, state the report path, explicitly highlight any critical issues, and offer to re-run specific stages with different parameters.

## Rules

Apply the safety rules, error handling, and example invocations in `references/rules-and-examples.md`. Key constraints: never load-test production without explicit confirmation, only test GET by default, mask auth tokens, respect 429 rate limits, count timeouts as failures, and never extrapolate beyond tested ranges.

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [OneWave-AI](https://github.com/OneWave-AI)
- **Source:** [OneWave-AI/claude-skills](https://github.com/OneWave-AI/claude-skills)
- **License:** MIT
- **Homepage:** https://www.onewave-ai.com

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** yes
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-onewave-ai-claude-skills-api-load-tester
- Seller: https://agentstack.voostack.com/s/onewave-ai
- Browse the marketplace: https://agentstack.voostack.com/browse

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Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.