ai-workflow-skill/docs/tests/orch-skill/strict-worktree-dispatch-to-cleanup-through-bundled-cli.md

Case: strict-worktree-dispatch-to-cleanup-through-bundled-cli

Test Type

This is a forward-test and a worktree-lifecycle skill validation.

The goal is to verify that a leader using the packaged orch skill can allocate a strict worktree, reconcile completion, and clean that worktree up through the bundled CLI while a worker completes the task through inbox.

Purpose

Validate that all of the following can be true at the same time:

• the leader can dispatch a code task with --strict-worktree through the bundled orch skill
• the worker can complete the resulting attempt thread through inbox
• the leader can reconcile the finished task and clean the attempt worktree
• the final filesystem state matches the cleanup contract

Preconditions

• orch skill path exists: ORCH_SKILL_PATH=skills/orch
• inbox skill path exists: INBOX_SKILL_PATH=skills/inbox
• bundled CLI executables exist at ORCH_SKILL_PATH/assets/orch and INBOX_SKILL_PATH/assets/inbox
• use an empty temporary directory TMPDIR
• initialize TMPDIR/coord.db before launching role agents through INBOX_SKILL_PATH/assets/inbox --db TMPDIR/coord.db --json init
• create TMPDIR/repo as a Git repository with one committed file before launching role agents

Agent Topology

• leader
• worker-a

Inputs

Leader Prompt

Use $orch at ORCH_SKILL_PATH to act as leader on the already initialized SQLite DB TMPDIR/coord.db. Only coordinate through the bundled orch CLI from the skill. Workflow: 1) create run run_blog_skill_worktree_001, 2) add one code task T1 for worker-a, 3) dispatch it with --repo-path TMPDIR/repo --workspace-root .orch/worktrees --strict-worktree, 4) record the returned THREAD_ID and WORKTREE_PATH, 5) wait until the worker completes, 6) reconcile, 7) clean up attempt 1, 8) stop after reporting RUN_ID, THREAD_ID, and WORKTREE_PATH. Do not use ordinary chat to coordinate with the worker.

Worker Prompt

Use $inbox at INBOX_SKILL_PATH to act as worker-a on SQLite DB TMPDIR/coord.db. Only coordinate through the bundled inbox CLI from the skill. Workflow: 1) fetch and claim the assigned task, 2) inspect the task payload enough to confirm a worktree path was provided, 3) finish the task with done, 4) stop after reporting the THREAD_ID you handled and whether you observed a worktree path. Do not use ordinary chat to coordinate with the leader.

Execution Parameters

• use the shared execution contract from README.md
• use the shared timeout defaults from README.md
• do not override the default cleanup policy

Execution Steps

1. Initialize TMPDIR/coord.db once through the bundled inbox CLI before launching agents
2. Create TMPDIR/repo with an initial commit before launching agents
3. Inject skills/orch/ into leader
4. Inject skills/inbox/ into worker-a
5. Point both agents at the same database path TMPDIR/coord.db
6. Launch leader and worker-a in parallel
7. Wait for both agents to finish
8. Resolve THREAD_ID and WORKTREE_PATH from the agent outputs
9. Independently run the validation commands from the main thread

Validation Commands

ORCH_SKILL_PATH/assets/orch --db TMPDIR/coord.db --json status --run run_blog_skill_worktree_001
INBOX_SKILL_PATH/assets/inbox --db TMPDIR/coord.db --json show --thread THREAD_ID
test ! -d WORKTREE_PATH

Expected Outcomes

• the leader reports a non-empty WORKTREE_PATH from dispatch
• the worker reports that the task payload exposed a worktree path
• the final run status is done
• the cleanup step removes the worktree directory

Assertions

• status.data.run.status == "done"
• status.data.tasks[0].status == "done"
• show.data.thread.status == "done"
• the task-side thread history includes a payload field or body content referencing the worktree path
• WORKTREE_PATH does not exist after cleanup

Cleanup

• use the default cleanup policy from README.md
• if the run fails, retain TMPDIR, coord.db, and the Git repo fixture for replay and manual inspection