feat: Add new tools and configurations for Castle platform
- Introduced `uv.lock` for dependency management with various packages including `pytest`, `colorama`, and `pluggy`. - Added `pyrightconfig.json` for Python type checking configuration. - Expanded `recommendations.md` with detailed scaling recommendations and project management strategies. - Created shared `ruff.toml` for consistent linting across projects. - Developed `Castle Tools` with various utilities including Android backup, browser automation, document conversion, and search tools. - Implemented `backup-collect` and `schedule` tools for system administration tasks. - Enhanced `search` functionality with indexing and querying capabilities using Tantivy. - Added comprehensive documentation for each tool, including usage examples and installation instructions.
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docs/python-tools.md
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# Python Tools in Castle
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How to build CLI tools following Unix philosophy. Based on the patterns in the
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[toolkit](https://github.com/payneio/toolkit) project.
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## Principles
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- Each tool does one thing well
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- Read from stdin or file argument, write to stdout
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- Compose via pipes: `pdf2md doc.pdf | gpt "summarize this"`
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- Status messages go to stderr (don't interfere with piping)
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- Exit 0 on success, 1 on error
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## Stack
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| Layer | Choice |
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|-------|--------|
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| **CLI** | argparse |
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| **Package manager** | uv (never pip) |
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| **Build** | hatchling |
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| **Testing** | unittest + mocking |
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| **Linting** | ruff |
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| **Type checking** | pyright |
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## Project layout
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Tools live inside a single package with categories:
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```
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toolkit/
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├── tools/
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│ ├── document/
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│ │ ├── pdf2md.py # Implementation
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│ │ ├── pdf2md.md # Docs + YAML frontmatter (single source of truth)
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│ │ └── test_pdf2md.py # Tests alongside tool
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│ ├── search/
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│ │ ├── search.py
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│ │ ├── search.md
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│ │ └── test_search.py
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│ ├── system/
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│ │ ├── schedule.py
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│ │ └── schedule.md
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│ └── toolkit/
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│ ├── toolkit.py # Meta-tool for discovery/scaffolding
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│ └── toolkit.md
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├── pyproject.toml
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├── Makefile
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└── README.md
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```
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Each tool is a `.py` + `.md` pair. The `.md` file has YAML frontmatter for
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metadata — no separate config files needed.
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## YAML frontmatter (.md file)
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```yaml
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---
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command: pdf2md
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script: document/pdf2md.py
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description: Convert PDF files to Markdown
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version: 1.0.0
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category: document
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system_dependencies:
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- pandoc
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- poppler-utils
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---
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# pdf2md
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Converts PDF files to Markdown format...
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```
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The toolkit management command discovers tools by scanning for these `.md` files.
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## pyproject.toml
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```toml
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[project]
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name = "toolkit"
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version = "0.1.0"
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requires-python = ">=3.11"
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dependencies = [
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"requests>=2.28.0",
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"pyyaml>=6.0.0",
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]
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[project.scripts]
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pdf2md = "tools.document.pdf2md:main"
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docx2md = "tools.document.docx2md:main"
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search = "tools.search.search:main"
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toolkit = "tools.toolkit.toolkit:main"
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[build-system]
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requires = ["hatchling"]
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build-backend = "hatchling.build"
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[tool.hatch.build.targets.wheel]
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packages = ["tools"]
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```
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Entry points follow `command = "tools.<category>.<tool>:main"`. After
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`uv tool install --editable .`, all commands are in PATH.
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## Tool implementation patterns
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### Simple tool: stdin/stdout
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The most common pattern. Read from a file argument or stdin, process, write
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to stdout.
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```python
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#!/usr/bin/env python3
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"""
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my-tool: Brief description
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Detailed usage docs here.
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Usage:
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my-tool [options] [FILE]
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cat input.txt | my-tool
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Examples:
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my-tool input.txt
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my-tool input.txt -o output.txt
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cat input.txt | my-tool > output.txt
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"""
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import argparse
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import sys
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def process(data: str) -> str:
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"""Core logic — pure function, easy to test."""
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return data.upper()
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def main() -> int:
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parser = argparse.ArgumentParser(
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description="Brief description",
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formatter_class=argparse.RawDescriptionHelpFormatter,
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)
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parser.add_argument("input", nargs="?", help="Input file (default: stdin)")
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parser.add_argument("-o", "--output", help="Output file (default: stdout)")
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parser.add_argument("--version", action="version", version="my-tool 1.0.0")
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args = parser.parse_args()
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# Read
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if args.input:
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with open(args.input) as f:
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data = f.read()
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else:
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data = sys.stdin.read()
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# Process
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result = process(data)
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# Write
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if args.output:
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with open(args.output, "w") as f:
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f.write(result)
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print(f"Wrote to {args.output}", file=sys.stderr)
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else:
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print(result, end="")
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return 0
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if __name__ == "__main__":
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sys.exit(main())
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```
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### Tool with subcommands
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For complex tools with multiple operations:
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```python
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def cmd_init(args: argparse.Namespace) -> int:
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"""Initialize a collection."""
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directory = args.directory or "."
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# ...
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print(f"Initialized in {directory}")
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return 0
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def cmd_query(args: argparse.Namespace) -> int:
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"""Search a collection."""
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# ...
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return 0
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def main() -> int:
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parser = argparse.ArgumentParser(description="Manage collections")
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parser.add_argument("--version", action="version", version="1.0.0")
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subparsers = parser.add_subparsers(dest="command")
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init_p = subparsers.add_parser("init", help="Initialize")
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init_p.add_argument("directory", nargs="?")
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init_p.add_argument("--name", help="Collection name")
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init_p.add_argument("--force", action="store_true")
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query_p = subparsers.add_parser("query", help="Search")
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query_p.add_argument("query", help="Search query")
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query_p.add_argument("--limit", type=int, default=20)
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args = parser.parse_args()
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if args.command == "init":
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return cmd_init(args)
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elif args.command == "query":
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return cmd_query(args)
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else:
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parser.print_help()
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return 1
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```
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### Tool with external processes
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When wrapping system commands:
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```python
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import subprocess
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import sys
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def convert(input_file: str, output_file: str) -> int:
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try:
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result = subprocess.run(
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["pandoc", input_file, "-o", output_file],
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check=True,
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capture_output=True,
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text=True,
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)
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return 0
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except subprocess.CalledProcessError as e:
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print(f"Error: {e}", file=sys.stderr)
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if e.stderr:
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print(e.stderr, file=sys.stderr)
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return 1
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except FileNotFoundError:
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print("Error: pandoc not found. Install with: apt install pandoc",
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file=sys.stderr)
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return 1
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```
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Always use `check=True` and `capture_output=True` with subprocess. Handle
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`FileNotFoundError` for missing system dependencies.
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### Tool with optional dependencies
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```python
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tantivy_available = False
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try:
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import tantivy
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tantivy_available = True
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except ImportError:
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tantivy = None
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def check_tantivy() -> None:
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if not tantivy_available:
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print("Error: tantivy not found. Install with: uv add tantivy",
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file=sys.stderr)
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sys.exit(1)
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```
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## Error handling
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```python
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def main() -> int:
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try:
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result = do_work()
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print(result)
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return 0
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except SpecificError as e:
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print(f"Error: {e}", file=sys.stderr)
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return 1
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except FileNotFoundError as e:
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print(f"Error: file not found: {e}", file=sys.stderr)
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return 1
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```
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Rules:
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- Normal output goes to **stdout** (enables piping)
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- Error messages go to **stderr**
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- Status/progress messages go to **stderr**
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- Return **0** for success, **1** for error
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- Entry point: `sys.exit(main())`
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## Piping
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Tools compose naturally via Unix pipes:
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```bash
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# Convert and summarize
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pdf2md paper.pdf | gpt "summarize this"
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# Process a batch
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for f in *.pdf; do pdf2md "$f" > "${f%.pdf}.md"; done
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# Chain extractors
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cat doc.txt | text-extractor | jq .content
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```
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When a tool writes to both a file and stdout, status messages must go to
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stderr so they don't contaminate the pipe:
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```python
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with open(output_file, "w") as f:
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f.write(result)
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print(result) # stdout (for piping)
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print(f"Wrote to {output_file}", file=sys.stderr) # stderr (status)
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```
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## Testing
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Tests live alongside the tool implementation, using unittest with mocking:
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```python
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# tools/gpt/test_gpt.py
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import unittest
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from unittest.mock import patch, MagicMock
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from io import StringIO
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from tools.gpt import gpt
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class TestGPT(unittest.TestCase):
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@patch("tools.gpt.gpt.get_api_key")
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@patch("openai.OpenAI")
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def test_generate(self, mock_openai, mock_key):
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mock_key.return_value = "fake-key"
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mock_client = MagicMock()
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mock_openai.return_value = mock_client
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mock_client.chat.completions.create.return_value = MagicMock(
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choices=[MagicMock(message=MagicMock(content="response"))]
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)
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result = gpt.generate_text("prompt", "gpt-4", 0.7, 500)
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self.assertEqual(result, "response")
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@patch("tools.gpt.gpt.generate_text")
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def test_cli(self, mock_gen):
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mock_gen.return_value = "output"
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with patch("sys.argv", ["gpt", "prompt"]):
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with patch("sys.stdout", new=StringIO()) as out:
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gpt.main()
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self.assertEqual(out.getvalue().strip(), "output")
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```
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Pattern: mock external dependencies (APIs, file I/O, subprocesses), test the
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CLI by patching `sys.argv`.
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## Build and install
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```makefile
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# Makefile
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all: build install
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build:
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uv sync
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install:
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uv tool install --editable .
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check:
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uv run ruff format .
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uv run ruff check . --fix
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uv run pyright
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test:
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uv run pytest -v
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clean:
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find . -type d -name "__pycache__" -exec rm -rf {} + 2>/dev/null || true
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```
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```bash
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make all # Sync deps + install to PATH
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make check # Format, lint, type-check
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make test # Run tests
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```
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## Creating a new tool
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Use the toolkit management command:
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```bash
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toolkit create my-tool --description "Does something" --category document
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```
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This creates the `.py` template, `.md` with frontmatter, and updates
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`pyproject.toml` with the entry point.
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Or manually:
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1. Create `tools/<category>/my_tool.py` with the argparse pattern above
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2. Create `tools/<category>/my_tool.md` with YAML frontmatter
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3. Add entry to `pyproject.toml` under `[project.scripts]`:
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```toml
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my-tool = "tools.category.my_tool:main"
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```
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4. Run `make install` to register in PATH
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## Registering in castle
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```yaml
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# castle.yaml
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components:
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toolkit:
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description: Personal utility scripts
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run:
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runner: command
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argv: ["toolkit"]
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cwd: toolkit
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install:
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path: { alias: toolkit }
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```
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Tools with `install.path` get the `tool` role. They don't need `expose`,
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`proxy`, or `manage` blocks.
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