API Test Restassure

api-test-restassure (EN)

Chinese version： See the corresponding Chinese skill.

When to Use

• Need API outputs that should land in REST Assured based automation.
• The project is Java-based or already uses REST Assured.

Workflow

1. Read and follow the main prompt listed under Progressive disclosure (coverage, structure, quality bar).
2. Add only project context that changes the result: scope, environment, constraints, risks, dependencies, expected deliverable.
3. If input is incomplete, return a usable first draft and explicitly mark assumptions and gaps.
4. 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.
• Do not invent endpoints, fields, environments, or root causes the user did not provide.
• Use placeholders or env-var semantics for auth/secrets; never hardcode real credentials.
• Keep output executable: concrete scenarios, clear priority, clear next steps.

Progressive Disclosure

• Before producing output, read and follow prompts/api-test-restassure.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: suite structure, common setup, auth handling, priority endpoints, positive scenarios, negative and boundary scenarios, assertion focus, test data strategy, ... (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.