.claude/skills/using-git-worktrees/SKILL.md
Use when starting feature work that needs isolation from current workspace or before executing implementation plans - creates isolated git worktrees with smart directory selection and safety verification
npx skillsauth add enuno/claude-command-and-control using-git-worktreesInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
Git worktrees create isolated workspaces sharing the same repository, allowing work on multiple branches simultaneously without switching.
Core principle: Systematic directory selection + safety verification = reliable isolation.
Announce at start: "I'm using the using-git-worktrees skill to set up an isolated workspace."
Follow this priority order:
# Check in priority order
ls -d .worktrees 2>/dev/null # Preferred (hidden)
ls -d worktrees 2>/dev/null # Alternative
If found: Use that directory. If both exist, .worktrees wins.
grep -i "worktree.*director" CLAUDE.md 2>/dev/null
If preference specified: Use it without asking.
If no directory exists and no CLAUDE.md preference:
No worktree directory found. Where should I create worktrees?
1. .worktrees/ (project-local, hidden)
2. ~/.config/superpowers/worktrees/<project-name>/ (global location)
Which would you prefer?
MUST verify .gitignore before creating worktree:
# Check if directory pattern in .gitignore
grep -q "^\.worktrees/$" .gitignore || grep -q "^worktrees/$" .gitignore
If NOT in .gitignore:
Per Jesse's rule "Fix broken things immediately":
Why critical: Prevents accidentally committing worktree contents to repository.
No .gitignore verification needed - outside project entirely.
project=$(basename "$(git rev-parse --show-toplevel)")
# Determine full path
case $LOCATION in
.worktrees|worktrees)
path="$LOCATION/$BRANCH_NAME"
;;
~/.config/superpowers/worktrees/*)
path="~/.config/superpowers/worktrees/$project/$BRANCH_NAME"
;;
esac
# Create worktree with new branch
git worktree add "$path" -b "$BRANCH_NAME"
cd "$path"
Auto-detect and run appropriate setup:
# Node.js
if [ -f package.json ]; then npm install; fi
# Rust
if [ -f Cargo.toml ]; then cargo build; fi
# Python
if [ -f requirements.txt ]; then pip install -r requirements.txt; fi
if [ -f pyproject.toml ]; then poetry install; fi
# Go
if [ -f go.mod ]; then go mod download; fi
Run tests to ensure worktree starts clean:
# Examples - use project-appropriate command
npm test
cargo test
pytest
go test ./...
If tests fail: Report failures, ask whether to proceed or investigate.
If tests pass: Report ready.
Worktree ready at <full-path>
Tests passing (<N> tests, 0 failures)
Ready to implement <feature-name>
| Situation | Action |
|-----------|--------|
| .worktrees/ exists | Use it (verify .gitignore) |
| worktrees/ exists | Use it (verify .gitignore) |
| Both exist | Use .worktrees/ |
| Neither exists | Check CLAUDE.md → Ask user |
| Directory not in .gitignore | Add it immediately + commit |
| Tests fail during baseline | Report failures + ask |
| No package.json/Cargo.toml | Skip dependency install |
Skipping .gitignore verification
Assuming directory location
Proceeding with failing tests
Hardcoding setup commands
You: I'm using the using-git-worktrees skill to set up an isolated workspace.
[Check .worktrees/ - exists]
[Verify .gitignore - contains .worktrees/]
[Create worktree: git worktree add .worktrees/auth -b feature/auth]
[Run npm install]
[Run npm test - 47 passing]
Worktree ready at /Users/jesse/myproject/.worktrees/auth
Tests passing (47 tests, 0 failures)
Ready to implement auth feature
Never:
Always:
Called by:
Pairs with:
tools
MemPalace local-first AI memory system. Use when setting up persistent memory for Claude Code sessions, mining project files or conversation transcripts, querying past context, configuring MCP tools, managing the knowledge graph, or troubleshooting palace operations.
tools
LangSmith Python SDK — trace, evaluate, and monitor LLM applications. Covers @traceable decorator, trace context manager, Client API, evaluate() / aevaluate(), comparative evaluation, custom evaluators, dataset management, prompt caching, ASGI middleware, and pytest plugin.
development
LangGraph (Python) — build stateful, controllable agent graphs with checkpointing, streaming, persistence, interrupts, fault tolerance, and durable execution. Covers both Graph API (StateGraph) and Functional API (@entrypoint/@task).
development
LangGraph Graph API (Python) — build explicit DAG agent workflows with StateGraph, typed state, nodes, edges, Command routing, Send fan-out, checkpointers, interrupts, and streaming. Use when you need explicit control flow and graph topology.