AGENT SKILL

smoke-tests

Use when running VS Code smoke tests or working on smoke-test CI steps. Covers pnpm run smoketest / smoketest-no-compile, grep filtering tests, and a temporary repeat-loop technique for tracking down flaky smoke tests in CI.

License 许可
MIT
所属仓库
microsoft/vscode
最近更新
2026-11-11
Stars
★ 20w
Forks
4.4w

01 前言 Front Matter

name
smoke-tests
description
Use when running VS Code smoke tests or working on smoke-test CI steps. Covers pnpm run smoketest / smoketest-no-compile, grep filtering tests, and a temporary repeat-loop technique for tracking down flaky smoke tests in CI.

03 SKILL.md 正文

Running Smoke Tests

Smoke tests live in test/smoke/ and drive a full VS Code instance (Electron, web, or remote) through end-to-end user flows.

Scripts

  • pnpm run smoketest — compiles the smoke tests first (test/smoke), then runs them.
  • pnpm run smoketest-no-compile — runs the already-compiled smoke tests. CI uses this after an explicit compile step.

Both forward extra arguments after -- to the runner (test/smoke/test/index.js).

Common options

Option Description
-g <pattern> (alias -f) Grep filter on test/suite titles (mocha grep).
--build <path> Run against a packaged build instead of the compiled-from-source dev build.
--tracing Capture Playwright traces (and screenshots on failure).
--web Run the browser smoke tests instead of Electron.
--headless Headless browser (used with --web).
--remote Run the remote smoke tests.
--shard <index>/<total> Run only one part of the top-level suites, for example --shard 1/2. Suites are balanced across shards by estimated duration (see test/smoke/src/shard.ts); each suite runs in exactly one shard.
# Run everything (Electron, from source)
pnpm run smoketest

# Run only a subset of suites by name, with tracing (replace <suite name> with your suite, e.g. "Agents Window")
pnpm run smoketest -g "<suite name>" --tracing

# Run against a packaged build (CI style)
pnpm run smoketest-no-compile --tracing --build "/path/to/VSCode-darwin-arm64/Code - OSS.app"

The -g pattern matches against test/suite titles. For example, -g "Agents Window" matches all three Agents Window suites (Agents Window, Agents Window (local AgentHost), and Agents Window (local AgentHost, SDK sandbox)); use whatever substring identifies the suite(s) you care about.

The runner exits non-zero if any test fails, so a 0 exit code means every selected test passed.

Sharding in PR CI

The GitHub PR workflows split the Electron smoke tests into shards: the electron-smoke-1 through electron-smoke-3 jobs of .github/workflows/pr-linux-test.yml and pr-win32-test.yml pass their SMOKE_SHARD_INDEX/SMOKE_SHARD_TOTAL env to the runner as --shard. They report as <OS> / Electron-Smoke (shard 1/3) through <OS> / Electron-Smoke (shard 3/3). On Windows, the WSL Dev Container suite runs in its own electron-smoke-wsl job instead of a shard, which reports as Windows / Electron-Smoke (WSL). The electron-smoke-1 and electron-smoke-2 jobs of pr-darwin-test.yml split them into two shards on macOS, but pr.yml does not run the macOS jobs for now (see its commented-out macos-tests job). On Linux, the remote smoke tests also run in their own Linux / Remote (smoke) job, and on Windows in two shards, Windows / Remote (smoke, shard 1/2) and Windows / Remote (smoke, shard 2/2), next to <OS> / Remote (integration). The PR Gate job (pr-gate) reports a single check for every job of the workflow and fails if any shard did not succeed. The shards are skipped, and the gate passes, when the pull request only changes paths the smoke tests cannot read (see .github/actions/detect-changes/detect.ts). To change the shard count of a platform, add or remove electron-smoke-<index> jobs in its workflow, and update the shard numbers in the names and env of all of them. Near the top of each shard's smoke-test-runner.log, a Running smoke test shard <index>/<total> line lists the suites that shard ran.

Some placement is coupled to the workflows:

  • WSL: The electron-smoke-wsl job of pr-win32-test.yml (env WSL_SMOKE_TESTS) provisions WSL, runs only the WSL Dev Container suite (-g), and then the WSL Kerberos proxy run. The provisioning runs in the background while the job installs and builds, and a step before the smoke tests waits for it. The shards don't set the VSCODE_SMOKE_TEST_WSL_* variables, so every shard skips the WSL suite and computes the same split. The WSL job runs on the 1ES pool instead of the vscode-large-runners-windows-8-core larger runners, so it sets up without a workspace image: GitHub-hosted Windows runners intermittently freeze while WSL2 provisions a distribution (actions/runner-images#14938), which leaves the check pending for about 45 minutes until GitHub reports that it lost communication with the runner.
  • WSL version: the agents' Windows Server 2022 image only has the inbox WSL, so provisioning installs the WSL release pinned in build/checksums/wsl.txt (see build/azure-pipelines/common/wsl.psm1). To update it, put the SHA256 and file name of a newer wsl.<version>.x64.msi from the microsoft/WSL releases there. The installer caches key on that file; pr-pnpm-store.yml fills the GitHub cache on main.
  • Prepared WSL distribution: the wsl-distro job of pr-workspace-images.yml (1ES pool, daily schedule and manual runs only) runs wslDevContainer.ps1 -Operation Prepare and saves the exported VHD in a cache keyed on the hash of wslDevContainer.ps1 and build/checksums/wsl.txt. The WSL job restores the newest entry for its hash and imports it with wsl --import-in-place instead of building the distribution. It builds the distribution when there is no entry for its hash (for example after a change to either file, until the next daily run or a manual run of the workflow on main), or when the import fails. On Azure Pipelines, the Windows x64 smoke job prepares the distribution itself: on a miss of its daily cache key, it runs Prepare before Setup and saves the VHD when the job succeeds (see test/smoke/README.md).
  • macOS proxy runs: In pr-darwin-test.yml, the PAC, Kerberos and Basic proxy Agents Window runs happen only in the last shard, so test/smoke/src/shard.ts reserves their time there.

Every shard must register the same suites; otherwise suites can be skipped or run twice. Don't make suite registration depend on anything that differs between shards.

When a run finishes, the runner prints each top-level suite's duration, longest first. When you add a smoke suite that takes much longer than launching the app (about 20 seconds), or the printed durations drift from suiteDurations in test/smoke/src/shard.ts, update that table so the shards stay balanced. Use the durations of the PR workflows, and a condition on process.platform for a suite whose duration differs between platforms, such as Terminal, which takes seconds on Linux and over two minutes on macOS and Windows.

Temporarily looping a suite to hunt flaky CI tests

When a smoke test fails intermittently only in CI, a useful technique is to temporarily run the suspect suite many times in a row and fail on the first failure. This reproduces the flake under the real CI environment and captures its traces/screenshots, instead of waiting for it to recur naturally across unrelated PRs.

This is a debugging aid, not a permanent CI fixture:

  • Add it on a throwaway branch, push, and let CI run it. Iterate until you reproduce (and then fix) the flake.
  • Remove the loop before merging — leaving it in would add ~an hour per platform to every run.
  • It is not specific to any one suite. Point the -g filter at whichever suite you are investigating (the examples below use "Agents Window", but substitute your own).

Where to add it

Drop the loop next to the existing Electron smoke step, gated on the same condition, in the test step(s) for the platform(s) where the flake reproduces. In the sharded GitHub PR workflows, also gate it on a single shard (as in the example below) so it does not run in every shard:

GitHub PR workflows (run from source, no --build):

  • .github/workflows/pr-linux-test.yml (bash; sets DISPLAY: ":10")
  • .github/workflows/pr-win32-test.yml (PowerShell)

Azure DevOps test steps (run against the packaged build via --build):

  • build/azure-pipelines/linux/steps/product-build-linux-test.yml
  • build/azure-pipelines/darwin/steps/product-build-darwin-test.yml
  • build/azure-pipelines/win32/steps/product-build-win32-test.yml

Shape

Loop N iterations (e.g. 20) and abort on the first failing run. Give it a generous timeout — N sequential runs of a ~3-minute suite can take roughly an hour.

Bash (Linux/macOS):

# TEMPORARY: loop the suite to reproduce a flaky failure. Remove before merge.
# Replace <suite name> with the suite you're investigating (e.g. "Agents Window").
- name: 🧪 Smoke test flakiness probe (TEMPORARY)
  if: ${{ env.ELECTRON_TESTS == 'true' && env.SMOKE_TESTS == 'true' && env.SMOKE_SHARD_INDEX == '1' }}
  timeout-minutes: 60
  run: |
    for i in $(seq 1 20); do
      echo "::group::Smoke probe run $i/20"
      pnpm run smoketest-no-compile --tracing -g "<suite name>" || { echo "::error::Smoke test failed on run $i/20"; exit 1; }
      echo "::endgroup::"
    done

PowerShell (Windows) checks $LASTEXITCODE after each run and exit 1 on failure. The AzDO variants use set -e (bash) / $LASTEXITCODE (pwsh) for fail-fast and append --build "<packaged app path>".

Why fail-fast

The loop is a probe: the first failure is the signal. Stopping immediately preserves the failing run's traces/screenshots (under the logs artifact) and avoids burning ~an hour of agent time finishing a run that has already proven flaky.

Debugging CI smoke failures

Both CI systems publish the smoke runner's per-platform logs (the .build/logs directory) as a downloadable artifact. The artifact's internal layout is identical on both — only the artifact name and the download tool differ.

Downloading the logs artifact

GitHub Actions

The GitHub PR workflows upload the artifact as logs-<os>-<arch>-<suite>-<attempt>, where <os> is linux / windows, <suite> identifies the job (for example electron, browser, remote-smoke, or electron-smoke-shard1 for the first Electron smoke shard), and <attempt> is the run attempt (e.g. logs-linux-x64-electron-smoke-shard1-1).

The run id is the number in the run/job URL — for …/actions/runs/<run-id>/job/<job-id> use <run-id>. Download with the gh CLI:

# A specific artifact into ./logs
gh run download <run-id> -n logs-<os>-<arch>-<suite>-<attempt> -D ./logs

# Or every artifact from the run
gh run download <run-id>

gh run view <run-id> lists the run's jobs/artifacts; the run summary page in the browser also has an Artifacts section at the bottom.

Azure DevOps

The artifact name depends on which pipeline produced it:

  • Product build (product-build-<os>.yml): logs-<os>-<arch>-<attempt> — no suite segment, e.g. logs-macos-arm64-1.
  • Suite-split CI build (product-build-<os>-ci.yml): logs-<os>-<arch>-<suite>-<attempt> — the <suite> segment is lower(VSCODE_TEST_SUITE) (e.g. electron), so e.g. logs-macos-arm64-electron-1 (same shape as GitHub).

<os> is linux / macos / windows, <arch> is x64 / arm64, and <attempt> is $(System.JobAttempt). Download with the Azure CLI:

az pipelines runs artifact download \
  --org <ORG_URL> --project <PROJECT_NAME> \
  --run-id <BUILD_ID> --artifact-name <artifact-name> \
  --path ./logs

For the VS Code build that is --org https://dev.azure.com/monacotools --project Monaco; see the azure-pipelines skill for finding the <BUILD_ID>.

Inside the artifact

Under smoke-tests-<suite>/ (smoke-tests-electron/, smoke-tests-browser/, or smoke-tests-remote/, matching the suite that ran):

  • smoke-test-runner.log — the mocha driver output plus, for suites that use the mock LLM server, its verbose request/response bodies (look for request body:). On a Copilot CLI / Copilot session failure it also carries a tail of the captured Copilot runtime logs (see below).
  • <N>_suite_<Suite_Name>/copilot-runtime-logs/process-*.log — the Copilot runtime (copilot-runtime from @github/copilot-sdk-<platform>) process logs, captured by dumpFailureDiagnostics when a Copilot-runtime session fails. Check these first for a hang or "Timed out waiting for response": they are the SDK/CLI's own account of what it did (startup, auth, model request, turn lifecycle, and any panic / out-of-order event / protocol error) and explain a timeout that the test error alone does not. Agent Host sessions (Agents Window / local AgentHost) write a full log run at trace (chat.agentHost.copilotSdk.logLevel). Chat Sessions editor (Copilot CLI / Claude) and Local sessions run the SDK in-process and write only a minimal startup log here (Server started, waiting for requests) — enough to tell whether the runtime came up; their detailed model/turn diagnostics are in the GitHub Copilot Chat.log below. (Claude / Codex sessions use a different runtime and are not captured here.)
  • <N>_suite_<Suite_Name>/window2/exthost/<extension>/…log — per-suite extension-host logs (e.g. GitHub.copilot-chat/GitHub Copilot Chat.log). Many diagnostics are gated behind a setting the suite enables in its before hook, so check the suite's setup if an expected log line is missing.
  • <N>_suite_<Suite_Name>/playwright-screenshot-*.png — last-frame screenshot captured when a test fails (only when the suite ran with --tracing).

<Suite_Name> is the mocha suite title with non-word characters replaced by _. See also the code-oss-logs skill.

Distinction from other test types

  • Unit tests (.test.ts) → scripts/test.sh / runTests tool (see the unit-tests skill).
  • Integration tests (.integrationTest.ts + extension tests) → scripts/test-integration.sh (see the integration-tests skill).
  • Smoke tests (test/smoke/) → pnpm run smoketest — full end-to-end UI flows.

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