boundary-bbcr-fallback
Execute automatic BBCR (Collapse-Rebirth Correction) when knowledge boundaries are exceeded or reasoning fails.
Structured workflow to transform vague todos into implemented features using git worktrees and VS Code handoff. Supports task isolation, resumption, and clean commit history.
$ npx -y skills add qdhenry/Claude-Command-Suite --agent claude-codeHow it fires
How this command gets triggered: by you, by Claude, or both.
/todo-worktreeContext preview
What this command does when you run it.
Structured workflow to transform vague todos into implemented features using git worktrees and VS Code handoff. Supports task isolation, resumption, and clean commit history.
Structured workflow to transform vague todos into implemented features using git worktrees and VS Code handoff. Supports task isolation, resumption, and clean commit history.
**CRITICAL**
1. Check for task resume: If `task.md` exists in current directory:
2. Add `/todos/worktrees/` to .gitignore: `rg -q "/todos/worktrees/" .gitignore || echo -e "\n/todos/worktrees/" >> .gitignore` 3. Read `todos/project-description.md` in full
# Project: [Name]
[Concise description]
## Features
[List of key features and purpose]
## Tech Stack
[Languages, frameworks, build tools, etc.]
## Structure
[Key directories, entry points, important files]
## Architecture
[How components interact, main modules]
## Commands
- Build: [command]
- Test: [command]
- Lint: [command]
- Dev/Run: [command if applicable]
## Testing
[How to create and run tests]
## Editor
- Open folder: [command]4. Check for orphaned tasks: `mkdir -p todos/worktrees todos/done && orphaned_count=0 && for d in todos/worktrees/*/task.md; do [ -f "$d" ] || continue; pid=$(grep "^**Agent PID:" "$d" | cut -d' ' -f3); [ -n "$pid" ] && ps -p "$pid" >/dev/null 2>&1 && continue; orphaned_count=$((orphaned_count + 1)); task_name=$(basename $(dirname "$d")); task_title=$(head -1 "$d" | sed 's/^# //'); echo "$orphaned_count. $task_name: $task_title"; done`
1. Read `todos/todos.md` in full 2. Present numbered list of todos with one line summaries 3. STOP → "Which todo would you like to work on? (enter number)" 4. Remove selected todo from `todos/todos.md` and commit: `git commit -am "Remove todo: [task-title]"` 5. Create git worktree with branch: `git worktree add -b [task-title-slug] todos/worktrees/$(date +%Y-%m-%d-%H-%M-%S)-[task-title-slug]/ HEAD` 6. Change CWD to worktree: `cd todos/worktrees/[timestamp]-[task-title-slug]/` 7. Initialize `task.md` from template in worktree root:
# [Task Title] **Status:** Refining **Agent PID:** [Bash(echo $PPID)] ## Original Todo [raw todo text from todos/todos.md] ## Description [what we're building] *Read [analysis.md](./analysis.md) in full for detailed codebase research and context* ## Implementation Plan [how we are building it] - [ ] Code change with location(s) if applicable (src/file.ts:45-93) - [ ] Automated test: ... - [ ] User test: ... ## Notes [Implementation notes]
8. Commit and push initial task setup: `git add . && git commit -m "[task-title]: Initialization" && git push -u origin [task-title-slug]`
1. Research codebase with parallel Task agents:
2. Append analysis by agents verbatim to `analysis.md` 3. Draft description → STOP → "Use this description? (y/n)" 4. Draft implementation plan → STOP → "Use this implementation plan? (y/n)" 5. Update `task.md` with fully refined content and set `**Status**: InProgress` 6. Commit refined plan: `git add -A && git commit -m "[task-title]: Refined plan"` 7. Open editor at worktree: `[editor-command] /absolute/path/to/todos/worktrees/[timestamp]-[task-title-slug]/` 8. STOP → "Editor opened at worktree. Run `claude "/todo"` in worktree to start implementation"
1. Execute the implementation plan checkbox by checkbox:
A comprehensive development toolkit designed following Anthropic's Claude Code Best Practices for AI-assisted software development.
Repo: qdhenry/Claude-Command-Suite
Execute automatic BBCR (Collapse-Rebirth Correction) when knowledge boundaries are exceeded or reasoning fails.
Analyze semantic position relative to knowledge boundaries to prevent hallucination and identify uncertainty zones.
Generate a visual heatmap of knowledge boundaries showing safe zones, risk areas, and semantic coverage.
Evaluate the current risk level and provide detailed analysis of potential hallucination or reasoning failure.
Find and construct semantic bridges to safely navigate from current position to target concept without crossing dangerous boundaries.
Takes an input prompt and returns ONLY a token-optimized version that preserves meaning while minimizing token count. Based on LLM tokenization principles:…