SuperAPI AI Directory

functional-testing

Testing & quality

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Updated 10-16 06:50

About this skill

Functional Testing (Chinese Version)

English version: See the corresponding English skill.

When to Use

  • You need to handle functional testing-related tasks in a real project.
  • You need a result that can be used directly 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 "current assumptions" and "questions to confirm / 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 not provided by the user.
  • 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/functional-testing.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 ready-made templates need to be applied: read output-templates/ for the matching template; do not invent conflicting structures.
  • When the user wants examples or to benchmark against existing assets: read examples/ for the relevant samples.
  • When in-depth materials such as framework specifications, troubleshooting, or report schemas are needed: read only references/ for files relevant to the current problem; do not read the entire directory.
  • When format conversion or auxiliary validation is needed: prefer using scripts/ existing 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 main prompt's output structure has been followed
  • Minimum coverage focus: scope, core flows, positive scenarios, exception scenarios, boundary scenarios, role or permission differences, data conditions, integration points… (details are subject to the main prompt)
  • The minimum checklist has been covered, or it is noted why items are omitted
  • High-risk items have explicit priorities
  • No details not provided by the user have been fabricated
  • 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.