plugin/skills/test-strategy/SKILL.md
Use this skill when writing tests, designing test plans, setting up test infrastructure, or evaluating test quality — test strategy design, a test writing guide, and coverage targets, providing patterns for unit, integration, E2E, and API testing.
npx skillsauth add avav25/ai-assets test-strategyInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Systematic testing skill covering strategy, patterns, and quality gates. Produces consistent, maintainable test suites across tech stacks.
TESTING.md documentation/run-tests workflow instead)code-review skill)Agent(devops-engineer) role)Follow the test pyramid for cost-effective coverage:
/ E2E \ Few — critical user journeys only
/----------\
/ Integration \ Moderate — API, DB, service boundaries
/----------------\
/ Unit Tests \ Many — fast, isolated, comprehensive
/--------------------\
| Layer | What to Test | Speed | Count | |---|---|---|---| | Unit | Pure logic, transformations, validators, utils | < 50ms | Many | | Integration | DB queries, API endpoints, service interactions | < 5s | Moderate | | E2E | Critical user journeys, happy paths, key flows | < 30s | Few |
should_return_404_when_user_not_found| Metric | Target | Hard Minimum | |---|---|---| | Line coverage | ≥ 80% | ≥ 60% | | Branch coverage | ≥ 75% | ≥ 50% | | Critical path coverage | 100% | 100% | | New code coverage | ≥ 90% | ≥ 80% |
Critical paths = authentication, authorization, payment, data mutations, error handling.
Projects should have a TESTING.md at the root (and per-service in monorepos) documenting test infrastructure, commands, credentials, and organization. Scaffolded by /ai-skills-init (per detected stack) and authored using Agent(qa-engineer). Always read TESTING.md before writing or running tests.
Agent(qa-engineer) (test strategy, automation, local test infra), Agent(software-engineer) (code quality)/test-local (full local QA cycle), /run-tests (lightweight execution), /ai-skills-init (TESTING.md scaffold), /develop, /feature-dev (single-agent fallback), /bugfix, /pre-committest-writing-guide.mdTESTING.md (root + per-service)development
Use this skill when running the recurring (daily) knowledge-base rescan for a repo that already has knowledge/.knowledge-sync.yml — the main-thread dispatcher that reads the config, computes the git delta since last_scanned_sha, maps changed paths to affected doc areas, early-exits cheaply when nothing changed, then fans out one Agent(content-writer) per affected area, applies the propose/direct update policy, advances the baseline only on success, and writes an L4 run log — all with the G1 untrusted-content choke-point, secret-scan, deny-list, and budget controls woven in. For first-time setup use /knowledge-sync-init.
development
Use this skill when bootstrapping scheduled knowledge-base sync for a repo that has no knowledge/.knowledge-sync.yml yet — to run one-time setup that detects the knowledge_root from CLAUDE.md/AGENTS.md, maps doc areas to source globs, records opt-in external sources (Linear/Notion/WebFetch, all disabled by default), captures a baseline last_scanned_sha, sets the per-area update policy, generates or seeds knowledge/CONVENTIONS.md, provisions the L4 memory dir, and offers to register the daily routine. Routes ongoing recurring sync operations to /knowledge-sync.
tools
Use this skill when bootstrapping a target repository to be ai-skills-aware — on the first run of any ai-skills workflow in a fresh repo, when adopting the ai-skills plugin in an existing repo, or after upgrading to a plugin version that adds new memory paths or templates, including when the user does not say "init" but asks to "set up" or "onboard" the repo — to detect codebase type, create CLAUDE.md + AGENTS.md scaffolding, initialize the .ai-skills-memory/ directory tree from L1 templates, and configure .gitignore. Idempotent — safe to re-run. Accepts `--codebase-type <type>` and `--overwrite`. Not for re-initializing only memory — use `/memory-init` instead.
tools
Use this skill when extending, repairing, or improving plugin assets, when ingesting a `/feedback` report as a fix-cycle backlog, or when you do not remember which lower-level command is right for the job — the umbrella workflow for ai-skills plugin-asset authoring and maintenance: creating, auditing, fixing, improving, refactoring, and migrating skills, agents, rules, hooks, prompts, schemas, and rubrics inside the plugin. Auto-classifies the request, loads the right knowledge skills (`@prompt-engineering`, `@context-engineering`, `@team-protocols`), and spawns the right subagents (`prompt-engineer`, `system-architect`, `python-engineer`, `software-engineer`, `qa-engineer`, `eval-judge`) via the `Agent` tool.