SuperAPI AI Directory

test-case-reviewer

Testing & quality

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Updated 10-15 15:31

About this skill

Test Case Review (Chinese Version)

English version: See the corresponding English skill.

When to Use

  • You need to handle test case reviewer related tasks in a real project.
  • You need a result that can be directly used for execution, review, or follow-up.

Execution Flow

  1. Read and follow the main prompt in "Load as Needed" (coverage checklist, output structure, quality requirements).
  2. Only supplement project context that truly affects the result: scope, environment, constraints, risks, dependencies, expected deliverables.
  3. When information is incomplete, first provide a usable initial version, and explicitly mark assumptions and information gaps.
  4. Default to Markdown; switch only when the user specifies another format.

Core Constraints

  • Prioritize by risk/business impact; do not spread effort evenly.
  • Write "confirmed facts" and "current assumptions" separately.
  • Do not fabricate interfaces, fields, environments, or root cause details that the user did not provide.
  • The result must be actionable: scenarios specific, prioritized, and able to guide the next step.

Load as Needed

  • Before producing output, you must read and follow prompts/test-case-reviewer.md(minimum coverage checklist, output structure, quality requirements).
  • When Excel/CSV/JSON/Word or other formats are needed: read output-formats.md, and output according to the user's format requirements.
  • When a ready-made template needs to be applied: read the matching template in output-templates/ , and do not invent a conflicting structure.
  • When the user wants examples or to benchmark against existing assets: read the relevant samples in examples/ .
  • When in-depth materials such as framework specifications, troubleshooting, or report schema are needed: only read the files in references/ that are relevant to the current problem; do not read through the entire directory.
  • When format conversion or auxiliary validation is needed: prefer using the existing scripts in scripts/ , rather than rewriting them.
  • When evaluating/regressing this skill: use evals/, and validate and run with skill-up.
  • When the user only wants the shortest onboarding path: read quick-start.md。

Pre-delivery Self-check

  • The output structure of the main prompt has been followed
  • Minimum coverage concerns: coverage gaps, missing positive scenarios, missing exception scenarios, missing boundary scenarios, requirement traceability, step clarity, expected result quality, data quality… (details are subject to the main prompt)
  • The minimum checklist has been covered, or it is indicated why it was omitted
  • High-risk items have clear priorities
  • No details were fabricated that the user did not provide
  • Assumptions and information gaps have been marked

Common Pitfalls

  • When both scope and context are unclear, do not pretend it is already complete and usable.
  • Do not write all items as equally important.
  • Do not skip assumptions and information gaps.
  • Do not output large sections of vague theory unrelated to the current toolchain.