Write and review Go tests using patterns suited to functions, file operations, and terminal interfaces. Cover multiple scenarios, check state changes, and compare rendered output with saved expected results while keeping slow integration tests separately skippable.
Trigger: Go tests, go test coverage, Bubbletea teatest, golden files. Apply focused Go testing patterns.
Review the instructions the agent will receive before you install.
Load this skill when writing or reviewing Go tests, adding coverage, testing Bubbletea/TUI flows, using teatest, or updating golden files.
t.Run(tt.name, ...).t.TempDir() for filesystem tests; never rely on a real home directory.testing.Short() when they run external commands or slow flows.Model.Update() directly for state changes; use teatest only for interactive flows.-update path and rerun tests without -update.| Target | Test pattern |
|---|---|
| Pure function or parser | Table-driven unit test. |
| Error behavior | Explicit success and failure cases. |
| File operations | t.TempDir() plus focused assertions. |
| TUI state transition | Direct Model.Update() call with tea.Msg. |
| Full TUI interaction | teatest.NewTestModel(). |
| Rendered output | Golden file test. |
| Real external command | Integration test; skip in -short. |
-update, inspect diff, then rerun without -update.Report test files changed, scenarios covered, commands executed, golden files updated, and any skipped integration scope.
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Prepare pull requests by checking approved issue links, change-type labels, and required automated checks. Draft the repository’s PR template using observed test results, while leaving commits, pushes, PR creation, and merging under human control.
Split changes exceeding 400 lines into linked pull requests with clear boundaries and dependencies. Choose a chain structure, keep tests and documentation with each work unit, and document review order, verification plans, and justified size exceptions.
Structure guides, READMEs, design documents, and pull request descriptions so readers can find answers quickly. Put outcomes first, introduce details gradually, and use examples, tables, and checklists to support understanding and review.
Draft clear, considerate comments for code reviews, issue replies, and team updates. Put the actionable point first, explain technical reasons when needed, and give a concrete next step while matching the conversation’s language.
Create and verify gentle-ai journeys, which are scripted sequences of product actions. Check their declarations separately from actual execution, review outdated expectations after behavior changes, and record execution results for pull requests.
Prepare Gentle AI changes for review by linking approved issues, following branch and commit naming rules, and drafting pull requests with observed test results. Check change size and required automated checks before claiming readiness.