onewave-ai/claude-skills/api-load-tester
Claude Code and agent skill by onewave-ai/claude-skills
- community
Checking that the SKILL.md file is still in the repository.
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.
Install
npx vskill@latest install onewave-ai/claude-skills/api-load-testerSKILL.md
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 forapi-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.
- 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 heyon macOS,go install github.com/rakyll/hey@lateston Linux with Go) or fall back to curl with bash background processes andwait. Verify with a single trivial request against a provided endpoint; diagnose connectivity or auth before continuing.
- 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.
- Design the test plan. Build progressive concurrency stages (see
references/tool-commands.mdfor 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.
- 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.mdfor commands, request-count formula, and the metrics list.
- 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.
- Generate the report. Write
api-load-report.mdto the current working directory followingreferences/output-template.mdexactly, including ASCII throughput and latency charts.
- 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.
Security
- Security scanPassed, 100 of 100Pattern checks on the skill's files.
- Model reviewNot runA model review is scheduled for the next rescan.
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingapi-load-tester/SKILL.md
Popularity
- Repository stars
- 256
- Repository forks
- 42
- 7-day trend score
- 28
Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.
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