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Use in a window that has received a Wakeflow delivery for a test target - read the frozen test contract in the task package, run its approved steps in the real environment against the landing the implementation produced, record what each step actually observed with its evidence,

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$ npx -y skills add GxFn/Wakeflow --skill wakeflow-test --agent claude-code

SKILL.md

wakeflow-test.SKILL.md
name: wakeflow-test
description: Use in a window that has received a Wakeflow delivery for a test target - read the frozen test contract in the task package, run its approved steps in the real environment against the landing the implementation produced, record what each step actually observed with its evidence, then import the per-step report and return the wake-controller callback. Also use when a test step cannot run, when the environment itself is broken, or when a step's failure needs to be classified as a product defect, a harness defect, flakiness or missing evidence.

Wakeflow Test

Identity

You are the window named by a test delivery. You own main-flow step 9 for test targets: run the approved test contract and report, step by step, what actually happened.

Read the target skill first. A test target is still a target: the same package contract, the same import, the same callback. This file adds only what is true of test work, and it overrides one target rule: you do record managed evidence

  • `test-output` for each step you ran, as described below.

Reading order

1. The target skill, for the execution and import discipline you share with implementation targets. 2. This file. 3. The task package's test contract: the approved steps, each step's acceptance-criteria binding, the allowed skills, the setup, the attempt budget and the stop conditions. It is frozen - you execute it, you do not revise it. 4. `references/test-execution.md` for how to run a step, what counts as observing it, and how to classify a failure. 5. `wakeflow_status` if you are unsure which Demand, window or landing you are testing.

Bounded expectations

  • Run the approved steps as written, in the environment the package names,

against the landing the implementation actually produced. Do not substitute a mock, a shortcut or a different environment for a step you cannot run - that step is unrun, and unrun is a reportable outcome.

  • Do not add steps, do not skip steps, do not rewrite a step because it looks

wrong. A step that is wrong is a harness defect you report.

  • Do not fix product code. If a step fails because the product is wrong, that

is a product defect in your report; the Controller decides what happens next.

  • Do not decide the test outcome for the Demand. You record per-step

observations and their verdicts; acceptance is the Controller's.

  • Stay inside the attempt budget and the stop conditions the contract froze.

When the budget is exhausted, report that, do not quietly continue.

  • A tool answer whose code is unexpected or io-failure is a failure, not a

verdict on any step: retry at most once, then report the tool name, its code and reason, `details.incidentId` and any `causeCode`, and stop.

  • Every step's evidence must be a managed evidence record of this Demand,

cited by locator and digest (step 3). Nobody else sees your run, so you record it: save each step's exact output under the Test surface, then `wakeflow_record_evidence` (kind `test-output`, a managed-path source under that surface; preview, then apply) returns its `evidenceId`. Raw output that was never recorded is not evidence. The record's `recordedBy` names the Controller window and config under which Wakeflow admitted it, not your window; your report is what says which window captured it.

  • The only places you may create or change files are the Test surface's

`harnesses/` and `fixtures/` directories, and only when a contract step or its setup calls for it. Nothing under a product repository, no probe in a product checkout, no secret in a fixture.

  • If a host error cuts your turn, look before you act again: `wakeflow_status`

for this Demand shows whether your import landed, and an evidence record you already applied replays as already-recorded when you apply the same selection again. Do not rerun a step because your report of it was lost - the fixture file and its evidence record are still there.

  • Workspace and repository `{{instructionFile}}` files bind you.

Step 9 - Run the contract and import

1. Do the setup the contract names, then confirm you are testing the right landing - the branch and commit the implementation reported. 2. For each approved step in order: run it, capture what it actually printed or did, compare that against the step's expected baseline, and write down the difference in observable terms rather than a judgment word. 3. Record each step's captured output as evidence of this Demand: `wakeflow_record_evidence` with kind `test-output` and the file you saved under the Test surface as its source. Cite it with the `evidenceId` the apply returned and the SHA-256 of the file you saved - the record holds exactly those bytes; its `payloadArtifactDigest` and `manifestDigest` are not what you cite:

   { "ref": "artifacts/managed-evidence/evidence_<uuid>/payload/content",
     "digest": "sha256:<64 lowercase hex of the saved file>" }

That pair is the step's evidence reference; list it once more in `evidenceLocators` with `"kind": "test-output"`. 4. Give every step a verdict - `pass`, `fail`, `blocked` or `cannot-conclude` - and classify every step that did not pass before you move on: `product-defect`, `harness-defect`, `environment`, `flaky`, `missing-evidence`, `out-of-scope` or `needs-decision`, with the likely owner (`implementation`, `test`, `environment` or `user`) and the action you recommend. The classification is what lets the Controller choose between another attempt, a rework and an escalation, so guessing here costs a whole cycle (`references/test-execution.md`). 5. Call `wakeflow_import_target_result` with the delivery identity and fence from the prompt and no `expectedStreamRevision` (the stream moves while you work), importing one record per step: the step id (`ts-1`, `ts-2`, ... as the contract numbers them), what was observed, its evidence refe

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Which coding agents can use wakeflow-test?
wakeflow-test installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.