dev-testing
The dev-testing skill guides users through Phase 8 of an AI development lifecycle, helping them write unit and integration tests, measure code coverage, and validate test documentation for configured features. Use it when you need to add comprehensive test coverage, close coverage gaps, run coverage analysis, update testing documentation, or complete the testing phase of feature development.
git clone --depth 1 https://github.com/codeaholicguy/ai-devkit /tmp/dev-testing && cp -r /tmp/dev-testing/skills/dev-testing ~/.claude/skills/dev-testingSKILL.md
# Dev Testing Run testing work for configured AI docs features. Before changing docs or code, propose the concrete plan for this phase and wait for user approval unless the user already approved the exact phase plan. ## Phase Contract 1. Run `npx ai-devkit@latest lint` before phase work. 2. If working on a named feature, run `npx ai-devkit@latest lint --feature <name>`. 3. Read the testing doc, requirements, design, implementation notes, and current diff before changes. 4. Apply the `verify` skill before making coverage or test-pass claims. 5. If parent `dev-lifecycle` established usable task tracing, emit testing phase, next-action, and evidence events per `task`. ## Write Tests Use for Phase 8. 1. Run `npx ai-devkit@latest lint --feature <name>` and reference the testing doc path it validates. If manual path resolution is unavoidable, first resolve `.ai-devkit.json` `paths.docs`, falling back to `docs/ai`. 2. Gather context: feature name, changes summary, environment, existing test suites, flaky tests to avoid. 3. Analyze the testing template, success criteria, edge cases, available mocks, and fixtures. 4. Add unit tests for happy paths, edge cases, and error handling for each module. Highlight missing branches. 5. Add integration tests for critical cross-component flows, setup/teardown, and boundary/failure cases. 6. Run coverage tooling, identify gaps, and suggest additional tests if below the target. 7. If task tracing is available, record evidence for each fresh test/coverage command per `task`. 8. Update the selected testing doc with test file links and results. Next: `dev-review`. If tests reveal design flaws, return to `dev-design`.
AI DevKit · Exchange information with active Codex, Claude Code, and other AI agents using ai-devkit agent list, detail, and send. Use when an agent needs to find another active agent, read its recent context, send it information, or request information back.
AI DevKit · Manage running AI agents with ai-devkit agent commands. Use when an agent needs to identify itself, list agents, start workers, inspect agent detail, assign work, group agents, resume sessions, stop agents, or delegate work to other agents.
AI DevKit · Supervise multi-agent workflows over repeated passes: poll progress, unblock waiting agents, coordinate dependencies, relay outputs, resolve conflicts, and verify completion. Use only for ongoing multi-agent coordination, not one-off list/detail/send/start/kill actions.
AI DevKit · Use when the user asks to brainstorm, ideate, generate ideas, expand options, challenge ideas, pressure-test ideas, compare concepts, narrow choices, name something, plan content angles, explore strategy, evaluate product ideas, technical approaches, experiments, or decisions.
AI DevKit · Compare implementation with design and requirements docs to ensure alignment.
AI DevKit · Pre-push code review against design docs.
AI DevKit · Safe git commit workflow for AI coding agents. Use when the user asks to commit, prepare a commit, stage changes, create a PR-ready checkpoint, or finish work with a conventional commit while avoiding unrelated user changes.
AI DevKit · Design phase guidance for reviewing feature design against requirements. Use when the user wants to validate architecture, review design docs, resolve design trade-offs, or run dev-lifecycle phase 3.