How do I install the API Test Supertest skill?

Run npx skillmds add naodeng/api-test-supertest in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is API Test Supertest safe to use?

This skill has not completed SkillMD's automated safety review yet. Capability flags: executes scripts. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with API Test Supertest?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is API Test Supertest free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published API Test Supertest?

naodeng (@naodeng) published this skill. Their other Agent Skills are listed on their SkillMD profile.

API Test Supertest by naodeng — Agent Skill

Name: API Test Supertest
Rating: 4.5 (4 reviews)
Author: naodeng

File contents

api-test-supertest (EN)

Chinese version： See the corresponding Chinese skill.

When to Use

Need API outputs that should land in Supertest based automation.
The project is Node.js-based or already uses Supertest/Jest.

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.
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-supertest.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, environment setup, auth handling, priority endpoints, positive scenarios, negative and boundary scenarios, assertion focus, 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.

---name: api-test-supertestdescription: Use this skill when you need to parse multi-format API definitions and generate executable Supertest scripts; triggers include Supertest, Node.js API testing, and Supertest automation.--- # api-test-supertest (EN) **Chinese version：** See the corresponding Chinese skill. ## When to Use - Need API outputs that should land in Supertest based automation. - The project is Node.js-based or already uses Supertest/Jest. ## 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-supertest.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, environment setup, auth handling, priority endpoints, positive scenarios, negative and boundary scenarios, assertion focus, 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.

Frequently asked questions