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173 lines
6.8 KiB
Markdown
173 lines
6.8 KiB
Markdown
# s17: Worktree Isolation — Separate Directories, No Conflicts
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[English](README.md) · [中文](README.zh.md) · [日本語](README.ja.md)
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s01 → ... → s15 → s16 → `s17` → [s18](../s18_mcp_plugin/) → s19 → s20 → s21
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> *"Separate directories, no conflicts"* — Tasks own the goal, worktrees own the directory, bound by ID.
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>
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> **Harness Layer**: Isolation — Parallel execution in separate directories.
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---
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## The Problem
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In s16, Alice and Bob both work in the same directory. Alice's task is "refactor auth module", Bob's task is "refactor UI login page".
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Alice calls `write_file("config.py", ...)`. Bob also calls `write_file("config.py", ...)`. Both edit the same file, overwriting each other. And there's no clean rollback — you can't tell whose changes are whose.
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s15-s16 solved "who does what" (task system) and "how to communicate" (message bus), but not "where to work".
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---
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## The Solution
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Git worktree lets you create multiple independent working directories in the same repo, each with its own branch. Alice works in `.worktrees/auth-refactor/`, Bob in `.worktrees/ui-login/` — no conflicts.
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Carries forward s16's MessageBus, protocols, and autonomous claiming. This chapter adds:
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| Capability | Purpose |
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|------------|---------|
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| create_worktree | Create isolated directory + branch for a task |
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| bind_task_to_worktree | Bind task and directory (no status change) |
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| remove_worktree / keep_worktree | Cleanup or preserve after completion |
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| validate_worktree_name | Reject path traversal and illegal characters |
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---
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## How It Works
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### Creation: Task-Worktree Binding
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```python
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def create_worktree(name: str, task_id: str = "") -> str:
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validate_worktree_name(name) # Only [A-Za-z0-9._-]{1,64}
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path = WORKTREES_DIR / name
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ok, result = run_git(["worktree", "add", str(path), "-b", f"wt/{name}", "HEAD"])
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if not ok:
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return f"Git error: {result}"
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if task_id:
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bind_task_to_worktree(task_id, name)
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log_event("create", name, task_id)
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return f"Worktree '{name}' created at {path}"
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def bind_task_to_worktree(task_id: str, worktree_name: str):
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task = load_task(task_id)
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task.worktree = worktree_name # Write worktree field only
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save_task(task) # Status stays pending, waits for teammate claim
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```
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Binding rule: one task binds to one worktree. Binding does NOT change task status — the task stays `pending`, and advances to `in_progress` only when a teammate claims it. This way Lead can pre-create tasks and worktrees, and teammates naturally claim worktree-bound tasks during idle.
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### Teammate Tool Cwd Switching
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Each teammate keeps a `wt_ctx` dictionary with its current worktree path. When a teammate claims a task bound to a worktree, the runtime updates `wt_ctx`; that teammate's `bash`, `read_file`, and `write_file` calls then run in the worktree directory:
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```python
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# Inside teammate thread
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wt_ctx = {"path": None}
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def _run_claim_task(task_id):
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result = claim_task(task_id, owner=name)
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if "Claimed" in result:
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task = load_task(task_id)
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if task.worktree:
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wt_ctx["path"] = str(WORKTREES_DIR / task.worktree)
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return result
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def _run_bash(command):
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return run_bash(command, cwd=wt_ctx["path"]) # Execute in worktree
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```
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### Cleanup: Keep or Remove
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After task completion, two choices:
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```python
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def remove_worktree(name: str, discard_changes: bool = False) -> str:
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# Safety check: refuse by default if changes exist
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if not discard_changes:
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files, commits = _count_worktree_changes(path)
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if files > 0 or commits > 0:
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return "Has uncommitted changes. Use discard_changes=true to force, or keep_worktree"
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ok, _ = run_git(["worktree", "remove", str(path), "--force"])
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if not ok:
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return "Remove failed"
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run_git(["branch", "-D", f"wt/{name}"])
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log_event("remove", name)
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def keep_worktree(name: str) -> str:
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log_event("keep", name)
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return f"Worktree '{name}' kept for review (branch: wt/{name})"
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```
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Keep = preserve branch for manual review and merge. Remove = refuse by default if uncommitted changes; requires `discard_changes=true` to confirm. Does NOT auto-complete task — task completion is triggered explicitly by the teammate's `complete_task`.
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### Event Log: Auditable
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Each lifecycle operation writes to a log for auditing:
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```python
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def log_event(event_type: str, worktree_name: str, task_id: str = ""):
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event = {"type": event_type, "worktree": worktree_name,
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"task_id": task_id, "ts": time.time()}
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# append to .worktrees/events.jsonl
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```
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Event types are `create`, `remove`, and `keep`. The log supports manual auditing; a recovery flow can rebuild the current set from `git worktree list`.
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### run_git: Returns Success/Failure
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```python
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def run_git(args: list[str]) -> tuple[bool, str]:
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r = subprocess.run(["git"] + args, cwd=WORKDIR, ...)
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return r.returncode == 0, output
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```
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`create_worktree` and `remove_worktree` only write event logs after successful git commands, ensuring logs reflect actual state.
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---
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## Changes from s16
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| Component | Before (s16) | After (s17) |
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|-----------|-------------|-------------|
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| Working directory | All agents share WORKDIR | Each task can bind to a git worktree |
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| Task data | id/subject/status/owner/blockedBy | + worktree field |
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| Teammate tool cwd | Always WORKDIR | Auto-switches when claiming worktree-bound task |
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| New functions | — | create_worktree, bind_task_to_worktree, remove_worktree, keep_worktree, validate_worktree_name |
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| Worktree safety | None | Name validation + refuse removal with changes |
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| Event log | None | events.jsonl lifecycle auditing |
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| Lead tools | Team and task tools | + create_worktree, remove_worktree, keep_worktree |
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| Teammate tools | Task and file tools | Same tools; bash/read/write use the claimed worktree cwd |
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---
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## Try It
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```sh
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cd learn-claude-code
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python s17_worktree_isolation/code.py
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```
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Try this prompt:
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`Refactor the authentication module and the login page in parallel without letting the changes interfere with each other.`
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What to observe: Do both worktrees show different branches in `git status`? After claiming a worktree-bound task, does the teammate's bash run in the worktree directory? Does `remove_worktree` refuse when there are changes? Is task status still `pending` after binding?
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---
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## What's Next
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Agent teams can now self-organize in isolated workspaces. But Agent capabilities are limited to the tools we wrote — bash, read, write, task...
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What if users already have their own tools? Like an internal Jira API, or a custom deployment system?
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s18 MCP Plugin → Give Agent a plugin system. External tools connect via standard protocol; Agent doesn't need to know who wrote them.
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<!-- translation-sync: zh@v1, en@v1, ja@v0 -->
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