Write out the full test cases for a feature
feature.verifyGuidedStarts a multi-step job and tells your agent what to do next.What it does
Step 3 of the loop (project.initialize → feature.implement → feature.verify → testrun.create → pdlc.verify). Despite the name it does not run or grade anything: it collects the acceptance-criterion test cases in one suite so you can turn them from short outlines into complete tests with steps and expected results. An acceptance criterion (AC) is one testable promise the feature makes; an AC test case is any case with an acceptanceCriterionLabel such as "AC1". Pass a feature id to get the cases of the feature and of every user story and sub-feature under it, or a story id for just that story. Returns snapshot.acceptanceCriteria (id, acceptanceCriterionLabel, title, description, isWaived, suiteId = the suite the case is filed under) plus prompt: {name: "ac-to-testcase", args}: fetch that prompt with prompts/get using those args and follow it. Then call case.update for each case, write the code that makes the ACs true, record results with testrun.create, and grade them with pdlc.verify. With sessionId the session moves from PLAN to AUTHOR (writing tests), so pass it only on the first call.
Ask your agent
You don’t call feature.verify yourself. Say something like this to Claude Code, Cursor or another MCP-connected agent:
- “Write the full test steps for the password reset stories”
- “Flesh out the acceptance tests for this user story before we code it”
- “Turn the checkout acceptance criteria into proper test cases”
Inputs
| Name | Type | Description |
|---|---|---|
suiteIdrequired | string | Id of the suite that holds the AC test cases. Usually a user story id (the id userstory.create returned, since feature-spec attaches ACs to stories), or the feature id if ACs were attached to the feature itself. Must belong to the connected workspace. |
sessionIdoptional | string | Optional PDLC session id (from project.initialize or pdlc.list). When given, moves the session from PLAN to AUTHOR; the session must be in PLAN, otherwise the call returns an error. |
The MCP call
What the agent’s MCP client sends (placeholders in angle brackets):
{
"jsonrpc": "2.0",
"id": 1,
"method": "tools/call",
"params": {
"name": "feature.verify",
"arguments": {
"suiteId": "<suiteId>"
}
}
}Connect your agent
npx -y @testmaze/mcp init tmt_xxx claude mcp add tm --scope project -- npx -y @testmaze/mcp
Create the token in your Test Maze workspace under Settings → MCP. Setup for Cursor, Cline, Gemini CLI and Codex CLI is shown there too.
More guided workflows tools
- Start the build-and-verify loop for this repo
project.initialize - Start a new feature and plan its tests
feature.implement - Grade a test run and say what to fix next
pdlc.verify