SuperAPI AI Directory

api-version-compatibility-testing

Testing & quality

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Updated 10-16 01:34

About this skill

API Version Compatibility Testing

design compatibility candidates from version contracts, old clients, server changes, and deprecation evidence. Produce AVC-## findings. This Skill organizes traceable API-quality candidates only; it does not execute tests or turn a design inventory into coverage, pass, or release evidence.

When to Use

  • When you need version compatibility candidates from version contracts, change logs, old-client samples, compatibility policies, deprecation timelines, gateway routes, and response comparisons.
  • When you need selection rationale, applicability constraints, evidence gaps, and the smallest validation action.
  • When inputs are incomplete but a bounded first pass can preserve blocked or unassessed boundaries.

Do not use it to execute tests, invent contract or behavior, replace a complete strategy, or accept risk for a Human.

Output Format Options

  • Use Markdown by default; use tables, JSON, or CSV only when explicitly requested or required by the delivery format.
  • Separate static analysis, unexecuted work, evidence states, and Human decisions; keep items unassessed, blocked, or NOT_RUN when runtime evidence is absent.

How to Use

  1. Read prompts/api-version-compatibility-testing.md and provide the objective, scope, material, environment, and evidence.
  2. Complete the known, missing, conflicting, stale, out_of_scope, and assumptions input audit before findings.
  3. Record AVC-## with the subject, preconditions, behavior of concern, source evidence, and validation, plus impact/priority, owner role, close condition, and evidence state.
  4. Preserve conflicts, unknown constraints, and open questions when evidence is incomplete.

Domain Execution Essentials

  • Identify contract/client/server versions, support/deprecation timeline and migration order; build applicable old/new client by old/new server combinations.
  • Deliver the version matrix and wire/semantic differences, retaining unsupported/unknown cells; scope compatibility to sourced client behavior and support.
  • When deriving domain candidates, read and follow prompts/api-version-compatibility-testing.md for the domain procedure and oracle; retain valid controls, evidence gaps, and validation actions for each item.

Core Constraints

  • Do not execute tests, assume missing rules, versions, thresholds, data, or responses, or treat candidate counts as coverage proof.
  • File presence, names, design declarations, and Eval configuration are not runtime evidence.
  • Mark unknowns unassessed, blocked, or pending clarification instead of filling them with convention.
  • Do not edit requirements, code, test assets, or target systems.

Pre-delivery Check

  • Recorded the known, missing, conflicting, stale, out_of_scope, and assumptions input audit.
  • Every AVC-## has source, evidence state, impact/priority, owner role, close condition, and validation.
  • Facts, inferences, recommendations, unexecuted work, and Human decisions remain separate.
  • Findings are not execution results, coverage proof, or release claims.

Reference Files

  • Read evals/eval.yaml and matching cases for regression; configuration does not prove project results.
  • Use evals/trigger-prompts.csv and evals/local-rules.json for trigger checks; missing skill.selection evidence is BLOCKED.

Common Pitfalls

  • Do not turn a method name, file presence, or candidate count into test execution, coverage, pass, or release evidence when scope or evidence is incomplete.
  • Do not fill in missing rules, thresholds, data, environments, or results from convention; preserve unassessed, blocked, and pending items.
  • Do not expand this specialist design or review into a complete strategy, full test cases, runtime execution, or a release decision.

Best Practices

  • Complete the six-part input audit before selecting the smallest traceable and verifiable finding scope.
  • Keep the source, evidence state, impact/priority, owner role, close condition, validation method, and residual risk for every finding.
  • Write validation suggestions as next actions; do not upgrade package structure, candidate counts, or local Eval configuration into real quality conclusions.