common-skills
Best practices for the Common utilities package in LlamaFarm. Covers HuggingFace Hub integration, GGUF model management, and shared utilities.
Best use case
common-skills is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Best practices for the Common utilities package in LlamaFarm. Covers HuggingFace Hub integration, GGUF model management, and shared utilities.
Teams using common-skills should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/common-skills/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How common-skills Compares
| Feature / Agent | common-skills | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Best practices for the Common utilities package in LlamaFarm. Covers HuggingFace Hub integration, GGUF model management, and shared utilities.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Common Skills for LlamaFarm
Best practices and code review checklists for the `common/` package - shared Python utilities used across all LlamaFarm services.
## Component Overview
| Attribute | Value |
|-----------|-------|
| Path | `common/` |
| Package | `llamafarm-common` |
| Python | 3.10+ |
| Key Dependencies | huggingface_hub, hf-transfer |
## Purpose
The `common/` package provides shared functionality that needs to be consistent across multiple Python services:
- Model file utilities (GGUF selection, quantization parsing)
- HuggingFace Hub integration (listing, downloading)
- Process management (PID files)
## Shared Python Skills
This skill inherits all patterns from the shared Python skills:
| Topic | File | Relevance |
|-------|------|-----------|
| Patterns | [../python-skills/patterns.md](../python-skills/patterns.md) | Dataclasses, type hints, comprehensions |
| Typing | [../python-skills/typing.md](../python-skills/typing.md) | Type annotations, modern syntax |
| Testing | [../python-skills/testing.md](../python-skills/testing.md) | Pytest fixtures, mocking HuggingFace APIs |
| Errors | [../python-skills/error-handling.md](../python-skills/error-handling.md) | Custom exceptions, logging |
| Security | [../python-skills/security.md](../python-skills/security.md) | Path validation, safe file handling |
## Framework-Specific Checklists
| Topic | File | Key Points |
|-------|------|------------|
| HuggingFace | [huggingface.md](huggingface.md) | Hub API, model download, caching, authentication |
## Module Structure
```
common/
├── pyproject.toml # UV-managed dependencies
├── llamafarm_common/
│ ├── __init__.py # Public API exports
│ ├── model_utils.py # GGUF file utilities
│ └── pidfile.py # PID file management
└── tests/
└── test_model_utils.py # Unit tests with mocking
```
## Public API
### Model Utilities
```python
from llamafarm_common import (
# Parse model:quantization syntax
parse_model_with_quantization,
# Extract quantization from filename
parse_quantization_from_filename,
# Select best GGUF file from list
select_gguf_file,
select_gguf_file_with_logging,
# List GGUF files in HF repo
list_gguf_files,
# Download and get path to GGUF file
get_gguf_file_path,
# Default quantization preference order
GGUF_QUANTIZATION_PREFERENCE_ORDER,
)
```
### PID File Management
```python
from llamafarm_common.pidfile import write_pid, get_pid_file
```
## Review Checklist Summary
When reviewing code in `common/`:
1. **HuggingFace Integration** (High priority)
- Proper error handling for network failures
- Authentication token passed correctly
- High-speed transfer enabled appropriately
2. **Model Selection** (Medium priority)
- Quantization preference order maintained
- Case-insensitive matching
- Graceful fallback when preferred not available
3. **Testing** (High priority)
- HuggingFace API calls mocked
- Network isolation in tests
- Edge cases covered (empty lists, missing files)
4. **Security** (Medium priority)
- No token exposure in logs
- Safe file path handling
- Environment variable protection
See [huggingface.md](huggingface.md) for detailed HuggingFace-specific checklists.Related Skills
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