Live and Docker/Parallels workflows

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Live and Docker/Parallels workflows

• Live suite (models + gateway tool/image probes): pnpm test:live
• Target one live file quietly: pnpm test:live -- src/agents/models.profiles.live.test.ts
• Runtime performance reports: dispatch OpenClaw Performance with live_openai_candidate=true for a real openai/gpt-5.6-luna agent turn or deep_profile=true for Kova CPU/heap/trace artifacts. Daily scheduled runs publish mock-provider, deep-profile, and GPT-5.6 Luna lane reports to openclaw/clawgrit-reports from a separate artifact-consuming publisher job; missing or invalid publisher authentication fails scheduled and profile=release runs. Manual non-release dispatches keep the GitHub artifacts and treat report publication as advisory. The mock-provider report also includes source-level gateway boot, memory, plugin-pressure, repeated fake-model hello-loop, and CLI startup numbers.
• Docker live model sweep: pnpm test:docker:live-models
  • Each selected model runs a text turn plus a small file-read-style probe. Models whose metadata advertises image input also run a tiny image turn. Disable the extra probes with OPENCLAW_LIVE_MODEL_FILE_PROBE=0 or OPENCLAW_LIVE_MODEL_IMAGE_PROBE=0 when isolating provider failures.
  • CI coverage: daily OpenClaw Scheduled Live And E2E Checks and manual OpenClaw Release Checks both call the reusable live/E2E workflow with include_live_suites: true, which includes Docker live model matrix jobs sharded by provider.
  • For focused CI reruns, dispatch OpenClaw Live And E2E Checks (Reusable) with include_live_suites: true and live_models_only: true.
  • Add new high-signal provider secrets to scripts/ci-hydrate-live-auth.sh plus .github/workflows/openclaw-live-and-e2e-checks-reusable.yml and its scheduled/release callers.
• Native Codex bound-chat smoke: pnpm test:docker:live-codex-bind
  • Runs a Docker live lane against the Codex app-server path, binds a synthetic Slack DM with /codex bind, exercises /codex fast and /codex permissions, then verifies a plain reply and an image attachment route through the native plugin binding instead of ACP.
• Codex app-server harness smoke: pnpm test:docker:live-codex-harness
  • Runs gateway agent turns through the plugin-owned Codex app-server harness, verifies /codex status and /codex models, and by default exercises image, cron MCP, sub-agent, and Guardian probes. Disable the sub-agent probe with OPENCLAW_LIVE_CODEX_HARNESS_SUBAGENT_PROBE=0 when isolating other failures. For a focused sub-agent check, disable the other probes: OPENCLAW_LIVE_CODEX_HARNESS_IMAGE_PROBE=0 OPENCLAW_LIVE_CODEX_HARNESS_MCP_PROBE=0 OPENCLAW_LIVE_CODEX_HARNESS_GUARDIAN_PROBE=0 OPENCLAW_LIVE_CODEX_HARNESS_SUBAGENT_PROBE=1 pnpm test:docker:live-codex-harness. This exits after the sub-agent probe unless OPENCLAW_LIVE_CODEX_HARNESS_SUBAGENT_ONLY=0 is set.
• Codex on-demand install smoke: pnpm test:docker:codex-on-demand
  • Installs the packaged OpenClaw tarball in Docker, runs OpenAI API-key onboarding, and verifies the Codex plugin plus @openai/codex dependency were downloaded into the managed npm project root on demand.
• Codex npm-plugin live package smoke: pnpm test:docker:live-codex-npm-plugin
  • Installs the candidate OpenClaw package and exact Codex plugin into Docker, then uses a real OpenAI key for CLI preflight and same-session turns.
  • Its zero-retry medium-thinking follow-through turn must send progress, keep working through randomized workspace reads and an exact artifact write, then send completion. A progress-only terminal turn fails the lane.
• Live plugin tool dependency smoke: pnpm test:docker:live-plugin-tool
  • Packs a fixture plugin with a real slugify dependency, installs it through npm-pack:, verifies the dependency under the managed npm project root, then asks a live OpenAI model to call the plugin tool and return the hidden slug.
• OpenClaw rescue command smoke: pnpm test:live:system-agent-rescue-channel
  • Opt-in belt-and-suspenders check for the message-channel rescue command surface. Exercises /openclaw status, queues a persistent model change, replies /openclaw yes, and verifies the audit/config write path.
• OpenClaw first-run Docker smoke: pnpm test:docker:system-agent-first-run
  • Starts from an empty OpenClaw state dir and first proves the packaged openclaw setup CLI fails closed without inference. It then tests and activates fake Claude through the packaged activation module. Only afterward does a fuzzy packaged CLI request reach the planner and resolve to typed setup, followed by one-shot model, agent, Discord config, and SecretRef operations. It validates config and audit entries. This is supporting gate/operation evidence, not an interactive onboarding or OpenClaw agent/tool/approval proof. The same lane is exposed in QA Lab by pnpm openclaw qa suite --scenario system-agent-ring-zero-setup.
• Moonshot/Kimi cost smoke: with MOONSHOT_API_KEY set, run openclaw models list --provider moonshot --json, then run an isolated openclaw agent --local --session-id live-kimi-cost --message 'Reply exactly: KIMI_LIVE_OK' --thinking off --json against moonshot/kimi-k2.6. Verify the JSON reports Moonshot/K2.6 and the assistant transcript stores normalized usage.cost.