pip-boy 0.1.1

Personal assistant agent with persistent memory and configurable persona

Pip-Boy

A personal assistant agent with persistent memory and a configurable persona, providing a chat-based interface for workstation interaction. Built on Anthropic's Claude API, it supports multi-agent teamwork, task planning, git worktree isolation, and extensible skills.

Features

Core

• Conversational REPL — Interactive chat loop with readline history and UTF-8 support
• Persona System — Fixed lead persona ("Pip-Boy") with customizable teammate personas via Markdown files
• Web Search — Tavily integration with automatic DuckDuckGo fallback

Tools

• Filesystem — read, write, edit, glob (sandboxed to working directory)
• Shell — bash execution with optional background mode for long-running commands
• Web — web_search and web_fetch for real-time information retrieval
• Skills — load_skill dynamically loads built-in and user-defined skill guides (Markdown with YAML frontmatter)

Task Planning

• Story / Task DAG — Two-level planning: stories (epics) contain tasks with dependency tracking
• Kanban Board — task_board_overview, task_board_detail for status visualization
• State Machine — Tasks flow through pending → in_progress → in_review → completed / failed
• Persistent Storage — JSON files under .pip/tasks/ survive across sessions

Multi-Agent Team

• Teammate Spawning — team_spawn creates daemon threads with per-session model and turn limits
• Inbox Messaging — JSONL-based message bus (send, read_inbox) between lead and teammates
• Model Selection — Per-project .pip/models.json defines available models for teammate assignment
• Protocol Tracking — Structured shutdown and plan approval flows
• CLI Commands — /team for roster status, /inbox to peek the lead inbox

Git Worktree Isolation

• Isolated Branches — Each subagent works in its own git worktree (.pip/.worktrees/{name}/, branch wt/{name})
• Sync / Integrate / Cleanup — Worktree lifecycle management with merge conflict detection
• Task Submission — task_submit syncs work and transitions task status automatically

Context Management

• Micro-Compaction — Old tool results replaced with placeholders, keeping the last N rounds intact
• Auto-Compaction — When token count exceeds threshold, full transcript is saved and replaced with an LLM-generated summary
• Transcript Persistence — Timestamped JSON transcripts stored under .pip/transcripts/

Skills (Built-in)

Skill	Purpose
task-planning	Structured planning with story/task breakdown
agent-team	Multi-agent coordination and delegation
git	Git operations and workflow guidance
code-review	Code review methodology
create-skill	Authoring new custom skills

Workspace Scaffold

On first run in a new project, the agent automatically creates:

• .pip/ directory structure (tasks, transcripts, team, skills)
• .pip/models.json with default model catalog
• .pip/agents/pip-boy.md default agent persona
• .env from template (if missing)
• .gitignore entries for .pip/ and related paths
• .pip/.scaffold_manifest.json for tracking scaffold file versions

Scaffold files are version-tracked: unmodified files are auto-updated when a new version ships changes; locally modified files are left untouched with a warning.

Installation

Prerequisites: Python >= 3.11

pip install pip-boy

Development (from source)

git clone https://github.com/ByeDream/Pip-Boy.git
cd Pip-Boy
pip install -e .

Usage

# Navigate to your target project and run
cd /path/to/your/project
pip-boy

# Or use python -m
python -m pip_agent

# CLI-only mode (no WeChat/WeCom channels)
pip-boy --cli

# Force WeChat QR login
pip-boy --scan

# Show version
pip-boy --version

On first launch, the scaffold automatically creates .pip/ directory structure, .env (from template), and .gitignore entries in the target project. Edit the generated .env to fill in your ANTHROPIC_API_KEY, then run again.

The agent uses Path.cwd() as its working directory — always run it from the project you want to interact with.

Updating

From within a running session:

/update

Or manually:

pip install --upgrade pip-boy

Configuration

All configuration is done via environment variables or .env file.

Variable	Required	Default	Description
ANTHROPIC_API_KEY	Yes	—	Anthropic API key
ANTHROPIC_BASE_URL	No	(api.anthropic.com)	Custom API endpoint (proxy support)
MODEL	No	claude-sonnet-4-6	Default model for the lead agent
MAX_TOKENS	No	8096	Max response tokens
SEARCH_API_KEY	No	—	Tavily API key; falls back to DuckDuckGo
COMPACT_THRESHOLD	No	50000	Token estimate to trigger auto-compaction
COMPACT_MICRO_AGE	No	3	Micro-compaction: rounds of tool results to preserve
VERBOSE	No	true	Verbose output
PROFILER_ENABLED	No	false	Enable performance profiling

Project-Level Files

File	Location	Purpose
models.json	.pip/	Model catalog for teammate spawning
*.md	.pip/team/	Teammate persona definitions (YAML frontmatter + body)
_meta.json + *.json	.pip/tasks/{story}/	Task board state
*.md	.pip/skills/	User-defined skills

Dependencies

• anthropic — Claude API client
• pydantic-settings — Configuration management
• tavily-python — Web search API
• ddgs — DuckDuckGo fallback search
• pyyaml — YAML parsing for skills and team files
• httpx — HTTP client for channel communication
• qrcode — Terminal QR code rendering for WeChat login
• pyreadline3 — Readline for Windows

License

This project is licensed under the MIT License. See LICENSE for details.