About performance-test-k6
performance-test-k6 is a skill for producing performance-testing outputs in k6 structure. It guides users toward executable scenarios and risk-focused coverage while marking assumptions where service targets or traffic data are missing.
Key features
- 01k6-ready test scenarios
- 02Risk-based scenario selection
- 03Load model and threshold guidance
- 04Assumptions and open questions
- 05Secret-safe placeholders
Use cases
- 01Creating k6 performance test scenarios
- 02Planning tests when traffic or SLA data is missing
- 03Prioritizing critical performance bottlenecks
Install
Copy the command and run it in a terminal.
$
npx skills add https:/After installing, type/performance-test-k6in Claude Code to confirm it loaded.
Bundled files
References and scripts installed along with SKILL.md.
README.mdagents/openai.yamlevals/eval.yamlevals/cases/basic-success.yamledge-incomplete-input.yamledge-risk-priority.yamlreview-closed-model-control.yamlreview-offline-arrival-artifacts.yamlevals/fixtures/load-profile.mdevals/graders/review-offline-arrival-artifacts.pyexamples/seckill-sample.envoutput-templates/template-markdown.mdprompts/performance-test-k6.mdreferences/framework-spec.mdreferences/local/performance-testing_EN.mdreports/.gitignoreREADME.mdscripts/config.jshelpers.jsrun-local-smoke.shrun-tests.shscripts/tests/api-smoke.jsload.jssoak.jsspike.jsstress.jsscripts/tools/compare_k6.pylocal_mock_server.pysummarize_k6.pyDetails
From the project READMEperformance-test-k6 (EN)
Chinese version： See the corresponding Chinese skill.
When to Use
- Need performance outputs that should land in k6 structure.
- The project already uses k6 or wants k6-ready scenarios.
Workflow
- Read and follow the main prompt listed under Progressive disclosure (coverage, structure, quality bar).
- Add only project context that changes the result: scope, environment, constraints, risks, dependencies, expected deliverable.
- If input is incomplete, return a usable first draft and explicitly mark assumptions and gaps.
- Default to Markdown; switch formats only when the user asks.
Core Constraints
- Prioritize by risk / business impact — do not treat everything equally.
- Separate confirmed facts from current assumptions; with no SLA/traffic, label every number as Assumption and list Open Questions.
- Do not invent endpoints, fields, environments, or root causes the user did not provide; secrets are placeholders /
__ENVonly — never real tokens. - Keep output executable: concrete scenarios, clear priority, clear next steps.
- Default to only the most critical 1–2 scenario types — do not run baseline/load/stress/spike/soak all by default.
Progressive Disclosure
- Before producing output, read and follow
prompts/performance-test-k6.md(minimum coverage, output structure, quality bar). - When a ready-made template fits: use matching files under
output-templates/. - When the user wants examples or alignment with existing assets: read relevant
examples/. - For deep framework/troubleshoot/schema notes: read only the relevant file(s) under
references/, do not load the whole directory. - For format conversion or helper checks: prefer existing
scripts/over reinventing. - For evaluating/regressing this skill: use
evals/with skill-up.
Pre-delivery Checklist
- Followed the main prompt's output structure
- Minimum coverage focus: target scenarios, load model, data setup needs, VU or duration profile, thresholds, environment and monitoring, priority bottlenecks, reporting needs, ... (details in main prompt)
- Covered the minimum checklist, or explained omissions
- High-risk items have explicit priority
- Did not invent details the user did not provide
- Assumptions and gaps are marked
Common Pitfalls
- Do not pretend completeness when scope/context is missing.
- Do not treat every item as equally important.
- Do not skip assumptions and information gaps.
- Do not dump generic theory unrelated to the current toolchain.
Comments
Markdown supported