API Testing: Move from an endpoint list to authorization, contracts, exceptions, and idempotency validation

An HTTP 200 does not prove an API contract is safe. Field semantics, authorization, error paths, and idempotency can still break consumers after release.

The API Testing Skill treats requests, responses, negative paths, and data ownership as one coherent contract—not a pile of status-code checks.

This guide uses reproducible scenarios to show how to apply it: define the risk and evidence first, then organize the checks and results into a defensible next step.

Awesome QA Skills organizes Skills by language and testing stage. The series overview covers repository structure and shared installation options; this guide stays with API Testing.

Read the source Skill first

The main prompt covers Quality Bar, Workflow, Core Constraints, Progressive Disclosure, Pre-delivery Checklist. Those headings are navigation; the project artifacts still provide the facts.

The source directory contains 2 references, 17 script entries. Start with API Testing supporting references, Template conversion script.

Work through one concrete task

Design order API tests for authentication, contracts, idempotency, errors, and state transitions

Start with this compact input set.

Sources: current requirements, relevant pages or interfaces, known defects
Scope: journeys affected by this change
Unknowns: environment, accounts, data preparation
Expected output: risk order, coverage list, open questions

This output fragment demonstrates the contract. It is not an execution result.

PriorityTest pointBasisStatus
P0Core business journeyAcceptance criterion AC-01Not run
P1Error and recoveryHistorical defect BUG-17Data missing
P1Boundary and state changesBusiness rule BR-03Needs confirmation

Do not write “passed” during static design. Runtime evidence comes later.

Move from coverage ideas to a decision

The task is Design order API tests for authentication, contracts, idempotency, errors, and state transitions. Split by risk before deciding how many cases to write.

Risk questionTest designEvidence
Could the main journey block a transactionEnd-to-end path with state assertionsRun record, order state, build ID
Could retry create duplicate dataRepeat submission and idempotency checkRequest ID and data query
Can a user recover after failureTimeout, refresh, and re-entryUI state, logs, recovery result

Grow the table after Quality Bar and Workflow has been checked against the change. For each test point, ask which requirement or risk supports it, which environment and data it needs, and what remains after failure. An unanswered item is still an idea, not an execution handoff.

A prompt you can adapt

Replace the bracketed fields with project facts. Specific material leaves less room for guessing.

Use the api-testing Skill.

Task: Design order API tests for authentication, contracts, idempotency, errors, and state transitions
Version and environment: [requirement / build / environment]
Inputs: [file paths or links]
Scope: [included and excluded journeys]
Constraints: [accounts, data, time, compliance]

Order coverage by business risk and distinguish design from execution status. Give each test point a basis, data need, and expected evidence.
Finish with open questions. Do not invent missing facts.

Use the first pass to inspect structure and gaps. Supply missing material before asking for the handoff-ready artifact.

Advanced use, from one call to a maintained flow

Save the result of Design order API tests for authentication, contracts, idempotency, errors, and state transitions as a baseline. After requirement or code changes, perform impact analysis and rerun affected journeys plus the fixed gate set.

A three-Skill chain

requirements-analysisapi-testingtest-reporting

HandoffPayloadReceiver check
Upstream to api-testingSource versions, scope, risks, open questionsAPI Testing staleness and conflicts
api-testing to downstreamPrimary artifact, evidence index, unfinished workAPI Testing executability and owners
Feedback to api-testingRuns, defects, new risksAPI Testing baseline and regression update

Do not paste three complete outputs into one large prompt. Give API Testing a structured summary and accessible source artifacts. It saves context and makes defects traceable.

Team gates

GateCheckFailure action
api-testing inputVersion, environment, owner, accessible sourcesStop API Testing and list gaps
api-testing artifactMaterial claims carry basis and statusReturn API Testing for evidence
api-testing executionCommand, exit status, report are reproducibleClassify infrastructure or test failure
api-testing decisionResidual risks have accepter and dateDo not enter the next stage

Review API Testing adoption, human edit rate, unsupported claims, and failure-to-diagnosis time each sprint. Record a baseline for several cycles before setting targets.

What I would inspect during use

  • Scope points to a real business journey instead of turning API Testing into an encyclopedia.
  • Quality Bar is grounded in requirements, pages, interfaces, or defects.
  • Happy paths, exceptions, boundaries, and recovery are ordered by risk.
  • Status distinguishes designed, not run, passed, and failed.

Install and invoke

Install the individual Skill. The series overview carries the longer installation explanation.

npx skills add https://github.com/naodeng/awesome-qa-skills/tree/main/skills/en/testing-types/api-testing -g

Invoke it with “Use the api-testing Skill,” then attach the real artifacts.

Two practical questions

Can I use API Testing with incomplete material?

Yes, but the result should degrade to known facts, assumptions, and open questions. Missing environments or data cannot support an execution claim.

How do I know whether Workflow is sufficient?

Trace it back to requirements and risks. A handoff-ready result explains coverage, omissions, and the next action.

When is human review mandatory?

Require an accountable person for scope trade-offs, risk acceptance, release decisions, and source conflicts.

What should be archived?

Keep the input version, Skill output, human edits, and final evidence so the conclusion can be reconstructed.

Run API Testing against one real artifact and keep the input, output, and review notes. The fragments here establish structure; project evidence must still come from the project.

References

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