Umbrella for experimentation-SDK test harnesses: the shared offline-datafile / hermetic-init pattern (commit a point-in-time flag/experiment config fixture, initialize the SDK with no network, pin arms per test, assert assignment integrity), with per-vendor references for Statsig (localMode + overrideGate), Optimizely (datafile + forced decisions), Split.io / Harness FME (localhost mode + features map or YAML fixture), Amplitude Experiment (local evaluation + bootstrap), and VWO (settings file + deterministic bucketing). Use when writing tests for application code instrumented with any of these five experimentation SDKs; for experiment DESIGN gates use ab-test-validity-checklist, and to read results use experiment-results-interpreter.
日本語の概要は準備中です。原文の説明を表示しています。
実行スコア 未検証
インストール方法を見るインストールする前に、エージェントに与えられる指示の中身を確認できます。
Every major experimentation SDK ships the same hermetic-test mechanism under a different name: a point-in-time config fixture (datafile, settings file, flag payload, features map) that the SDK evaluates locally, so tests make zero network calls, pollute no production analytics, and stay deterministic. The vendor-specific mechanics differ only in how the fixture is loaded and how an arm is pinned.
| SDK | Offline mechanism | Arm pinning | Reference |
|---|---|---|---|
| Statsig | localMode: true | overrideGate / overrideConfig | references/statsig.md |
| Optimizely | JSON datafile fixture | set_forced_decision | references/optimizely.md (+ optimizely-recipes.md) |
| Split.io / Harness FME | authorizationKey: 'localhost' + features map / YAML | Per-key fixture entry (no override API) | references/split-io.md (+ split-io-example.md) |
| Amplitude Experiment | LocalEvaluationClient + bootstrap | Fixture edit or evaluateV2 mock | references/amplitude.md |
| VWO | Settings file + is_development_mode | Deterministic bucketing on user ID | references/vwo.md |
ab-test-validity-checklist Step 3.Regardless of vendor, the suite has the same five steps:
tests/fixtures/ and
refreshed deliberately (drift between fixture and prod config is
invisible otherwise).localMode, datafile string, 'localhost' key, bootstrap,
is_development_mode).Plus two integrity tests every suite should carry:
The team ships a new_checkout_flow flag with a treatment_a variation
and needs a deterministic test that a premium-plan user is routed into the
treatment:
import json
from optimizely import optimizely
# Step 1-2: committed fixture, offline init - no SDK key, no network
with open("tests/fixtures/optimizely-datafile.json") as f:
client = optimizely.Optimizely(f.read())
def test_premium_user_in_treatment():
# Step 3: context carries the attributes targeting needs
user = client.create_user_context("user-1", {"plan": "premium"})
decision = user.decide("new_checkout_flow")
# Step 4: assert on enabled + variation_key, not IDs
assert decision.enabled is True
assert decision.variation_key == "treatment_a"
def test_assignment_deterministic():
user = client.create_user_context("user-1")
d1 = user.decide("new_checkout_flow")
d2 = user.decide("new_checkout_flow")
assert d1.variation_key == d2.variation_key
The fixture drives the whole decision; the same shape translates to each vendor via its reference above.
| Anti-pattern | Why it fails | Fix |
|---|---|---|
| Live API key in tests | Production analytics polluted; rate limits; flakes | The vendor's offline switch |
| Fixture not version-controlled | Tests flake when prod config changes | Commit; refresh deliberately |
| Overrides / forced decisions leak across tests | Cross-test pollution | Per-test context + cleanup |
| Asserting on internal config / variation IDs | IDs change per environment | Assert keys and values |
| Skipping client shutdown / destroy | Event-flush timers and handles leak | Teardown in afterAll |
| Trusting one user ID to cover both arms | May bucket into one arm only | Distribution test across many IDs |
ab-test-validity-checklist.experiment-results-interpreter.sample-ratio-mismatch-detector agent.まだレビューはありません。使ってみた感想をお寄せください。
ログインなしで書き込めます。使ってみた感想、質問、動かなかった環境などを気軽にどうぞ。
まだコメントはありません。最初のコメントを書いてみませんか。
Builds a CI gate that fails the build on **new** WCAG / a11y violations introduced by a PR while grandfathering pre-existing violations on a per-rule / per-page baseline. Aggregates verdicts from axe-core / pa11y / Lighthouse a11y / WAVE / IBM Equal Access scans. Use when a project has accumulated a11y debt and a strict "zero violations" gate would block every PR - the ratchet pattern lets the team ship while preventing regressions.
日本語の概要は準備中です。原文の説明を表示しています。
Workflow skill that builds an A/B-test validity checklist from an experiment proposal, walking the canonical design-correctness gates - pre-registered OEC/power/guardrails, randomization unit + SRM check, assignment integrity, telemetry, peeking discipline, novelty/primacy, post-experiment SRM re-check - into a per-experiment checklist + sign-off form. Use when launching, auditing, or governing an experiment. For pitfall mechanics (guardrails, peeking) see experiment-results-interpreter's references; to read an already-valid result use experiment-results-interpreter; for per-SDK harness tests use experiment-sdk-testing - this gates DESIGN, not SDK code.
日本語の概要は準備中です。原文の説明を表示しています。
The single install-flow skill: the reference contract for the PWA install flow (installability gate fields, `beforeinstallprompt` handshake, per-platform paths - Android WebAPK / iOS Share menu / Firefox no-op - and the `display-mode` post-install signal, in references/install-flow-reference.md) plus the build-an-X workflow that emits the Add-to-Home-Screen suite. Walks the four-stage timeline, emitting one test per gate cell per [web.dev/articles/install-criteria][install-criteria], the deferred-prompt → `prompt()` → `userChoice` chain per [web.dev/articles/customize-install][customize-install], the iOS Safari manual-metadata branch (`apple-touch-icon`) per [web.dev/learn/pwa/installation][learn-pwa], and the post-install `(display-mode: standalone)` MQ assertion. Output: a Playwright spec with per-stage cells plus a coverage matrix. Use when a PWA's manifest, icons, or install handler change, when install conversion drops at an unknown stage, or when triaging a flaky install assertion.
日本語の概要は準備中です。原文の説明を表示しています。
Build-an-X workflow that uses an LLM to map existing tests to spec sections - given a spec doc + the test suite, the LLM identifies which tests cover which sections, surfaces uncovered sections (gap), and recommends specific tests to add. Output is a coverage matrix per spec ID. Scope is mapping tests that already exist and naming the gaps, not authoring tests for new acceptance criteria. Use when a spec doc and a test suite both exist but nobody can say which requirements are actually covered - before a release sign-off, an audit, or a decision about where to spend the next round of test effort.
日本語の概要は準備中です。原文の説明を表示しています。
Generates tests from natural-language specs (acceptance criteria, user stories, requirements) using an LLM, with confidence scoring per test case (LLM self-assessment plus heuristics: assertion quality, naming, completeness), batching uncertain cases for human review, and integration with the team's existing test framework. Use when the user asks to generate unit tests from acceptance criteria, convert user stories to test cases, automate test creation from requirements, or augment a spec-driven test suite with AI-generated stubs that are then curated before merge.
日本語の概要は準備中です。原文の説明を表示しています。
Configures Allure Report (test-runner adapter install, `allure-results` directory wiring, `categories.json` for failure classification, `history-trend.json` retention via the copy-history-between-runs pattern), runs the Allure CLI to convert `allure-results` to a static HTML site, and uploads the report as a CI artifact. Use when the team needs richer test reporting than JUnit XML - step-level attachments, per-test history, retry tracking, and severity / epic / feature labeling across framework-agnostic adapters (pytest, Jest, JUnit, TestNG, NUnit, Mocha). As a rich static HTML report generator, it is the open-source alternative to the sunset ExtentReports (JVM/.NET per-test HTML narrative); for hosted cross-run flakiness analytics rather than a static per-run report use currents-integration.
日本語の概要は準備中です。原文の説明を表示しています。