Agent skill

Config Skills

by llama-farm in llama-farm/llamafarm

Configuration module patterns for LlamaFarm. An agent skill from llama-farm/llamafarm.

Apache-2.0Auto-check passed

Install Config Skills

skills CLI
$ npx skills add llama-farm/llamafarm --skill config-skills -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install llama-farm/llamafarm config-skills --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/llama-farm/llamafarm.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/config-skills .claude/skills/config-skills && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
config-skills
GitHub stars
836
Token cost
~1.3k tokens
SKILL.md length
243 words
Files
3
Skills in repo
19
Repo updated
First seen
Licence
Apache-2.0

At a glance

Configuration module patterns for LlamaFarm. An agent skill from llama-farm/llamafarm.

  • Works in 4 steps: Edit schema.yaml (or referenced schemas… → Run nx run generate-types to compile and… → Update validators.py if new cross-field… → …
  • SKILL.md covers Module Overview, Links to Shared Skills, Framework-Specific Checklists and Tech Stack, plus 4 more sections
  • Calls uv, nx and ruff

What it does

Config Skills is an agent skill from llama-farm/llamafarm. Configuration module patterns for LlamaFarm. Covers Pydantic v2 models, JSONSchema generation, YAML processing, and validation.

Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `jsonschema.md` and `pydantic.md`).

It works with Pydantic and Python. The repository describes itself as: Deploy any AI model, agent, database, RAG, and pipeline locally or remotely in minutes. The licence is Apache-2.0.

Example prompts

  • “/config-skills”

Requirements

  • Python 3
  • Pre-approved tools (allowed-tools): Read, Grep, Glob

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. Edit schema.yaml (or referenced schemas like ../rag/schema.yaml)
  2. Run nx run generate-types to compile and generate types
  3. Update validators.py if new cross-field constraints are needed
  4. Test with uv run pytest config/tests/

What it can do on your machine

Read from SKILL.md and the folder at commit 6244d46. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Grep
    • Glob

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • uv
    • nx
    • ruff

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use uv, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Config Skills loads about 1.3k tokens when it runs. Until then it costs about 35 tokens; SKILL.md has 243 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~35
When it runs · the whole SKILL.md, loaded when a task matches
~1.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from llama-farm/llamafarm at commit 6244d46, republished under its Apache-2.0 licence (© llama-farm). 243 words, ~1,278 tokens.

Download SKILL.mdSave it as .claude/skills/config-skills/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
config-skills
description
Configuration module patterns for LlamaFarm. Covers Pydantic v2 models, JSONSchema generation, YAML processing, and validation.
allowed-tools
Read, Grep, Glob
user-invocable
false

Config Skills for LlamaFarm

Specialized patterns and best practices for the LlamaFarm configuration module (config/).

Module Overview

The config module provides YAML/TOML/JSON configuration loading with JSONSchema validation:

FilePurpose
datamodel.pyGenerated Pydantic v2 models from JSONSchema
schema.yamlSource JSONSchema with $ref references
compile_schema.pyDereferences $ref to create schema.deref.yaml
generate_types.pyGenerates Python types via datamodel-codegen
validators.pyCustom validators beyond JSONSchema capabilities
helpers/loader.pyConfig loading, saving, and format detection
helpers/generator.pyTemplate-based config generation

This module follows Python conventions from the shared skills:

TopicLinkKey Relevance
Patternspython-skills/patterns.mdPydantic v2, dataclasses
Typingpython-skills/typing.mdType hints, constrained types
Testingpython-skills/testing.mdPytest fixtures, temp files
Errorspython-skills/error-handling.mdCustom exceptions
Securitypython-skills/security.mdPath traversal prevention

Framework-Specific Checklists

ChecklistDescription
pydantic.mdPydantic v2 configuration patterns, nested models, constraints
jsonschema.mdJSONSchema generation, dereferencing, validation

Tech Stack

  • Python: 3.11+
  • Pydantic: v2 with ConfigDict, Field, constrained types
  • JSONSchema: Draft-07 with $ref dereferencing via jsonref
  • YAML: ruamel.yaml for comment-preserving read/write
  • Code Generation: datamodel-codegen for schema-to-Pydantic

Key Patterns

Generated Pydantic Models

The datamodel.py file is auto-generated from JSONSchema:

python
# Generated by datamodel-codegen from schema.deref.yaml
from pydantic import BaseModel, ConfigDict, Field, conint, constr

class Database(BaseModel):
    model_config = ConfigDict(extra="forbid")
    name: constr(pattern=r"^[a-z][a-z0-9_]*$", min_length=1, max_length=50)
    type: Type
    config: dict[str, Any] | None = Field(None, description="Database-specific configuration")
Custom Validators for Cross-Field Constraints

JSONSchema draft-07 cannot express all constraints. Custom validators extend validation:

python
def validate_llamafarm_config(config_dict: dict[str, Any]) -> None:
    """Validate constraints beyond JSONSchema (uniqueness, references)."""
    # Check for duplicate prompt names
    prompt_names = [p.get("name") for p in config_dict.get("prompts", [])]
    duplicates = [name for name in prompt_names if prompt_names.count(name) > 1]
    if duplicates:
        raise ValueError(f"Duplicate prompt set names: {', '.join(set(duplicates))}")
Comment-Preserving YAML with ruamel.yaml

Configuration files preserve user comments when modified:

python
from ruamel.yaml import YAML
from ruamel.yaml.comments import CommentedMap

def _get_ruamel_yaml() -> YAML:
    yaml_instance = YAML()
    yaml_instance.preserve_quotes = True
    yaml_instance.indent(mapping=2, sequence=4, offset=2)
    return yaml_instance

Directory Structure

config/
├── pyproject.toml       # UV-managed dependencies
├── schema.yaml          # Source JSONSchema with $ref
├── schema.deref.yaml    # Dereferenced schema (generated)
├── datamodel.py         # Pydantic models (generated)
├── compile_schema.py    # Schema compilation script
├── generate_types.py    # Type generation script
├── validators.py        # Custom validation beyond JSONSchema
├── validate_config.py   # CLI validation wrapper
├── __init__.py          # Public API exports
├── helpers/
│   ├── loader.py        # Config loading/saving
│   └── generator.py     # Template-based generation
├── templates/
│   └── default.yaml     # Default config template
└── tests/
    ├── conftest.py      # Shared fixtures
    └── test_*.py        # Test modules

Workflow: Schema Changes

When modifying the configuration schema:

  1. Edit schema.yaml (or referenced schemas like ../rag/schema.yaml)
  2. Run nx run generate-types to compile and generate types
  3. Update validators.py if new cross-field constraints are needed
  4. Test with uv run pytest config/tests/

Common Commands

bash
# Generate types from schema
nx run generate-types

# Validate a config file
uv run python config/validate_config.py path/to/llamafarm.yaml --verbose

# Run tests
uv run pytest config/tests/ -v

# Lint and format
ruff check config/ --fix
ruff format config/

© llama-farm, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files in .claude/skills/config-skills of llama-farm/llamafarm.

  • SKILL.md
  • jsonschema.md
  • pydantic.md

Open the folder on GitHubat commit 6244d46

Compare with similar skills

Config Skills next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Config Skills compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Config Skills this skillllama-farm/llamafarm836—~1.3kAutomated safety check: PassApache-2.0
Building Pydantic AI Agentsdocling-project/docling69k—~2.8kAutomated safety check: PassMIT
Fastcrudbenavlabs/fastcrud1.6k—~5kAutomated safety check: PassMIT
Prompt Engineering Patternswshobson/agents40k—~1.3kAutomated safety check: PassMIT
A2ui Generate Pydantic Modelsa2ui-project/a2ui17k—~2.3kAutomated safety check: PassApache-2.0
Migrating Agno To Pydantic AIpydantic/pydantic-ai21k—~1.8kAutomated safety check: PassMIT

Similar skills

  • Building Pydantic AI Agents

    docling-project/docling

    Patterns and tested examples for building agents with Pydantic AI: tools, capabilities, structured output, dependency injection, hooks, YAML specs, streaming and testing.

    69k GitHub stars~2.8k tokensUpdated today
    AI & LLM EngineeringAuto-check passed
  • Fastcrud

    benavlabs/fastcrud

    A skill your agent uses when building or modifying CRUD endpoints with FastCRUD (the fastcrud PyPI package) in a FastAPI project — covers FastCRUD, crudrouter, EndpointCreator, FilterConfig…

    1.6k GitHub stars~5k tokensUpdated today
    Backend & APIsAuto-check passed
  • Reference for designing and tuning production LLM prompts: few-shot examples, chain-of-thought, structured outputs, templates and system prompts.

    40k GitHub stars~1.3k tokensUpdated 6 days ago
    AI & LLM EngineeringAuto-check passed
  • Automated generator for strongly typed Pydantic v2 data models and basic catalogs across any A2UI protocol version (v0.8, v0.9, v0.9.1, v1.0, etc.).

    17k GitHub stars~2.3k tokensUpdated yesterday
    DevelopmentAuto-check passed
  • Migrating Agno To Pydantic AI

    pydantic/pydantic-ai

    Official

    Migrate Python Agno applications to Pydantic AI and, only when needed, Pydantic AI Harness.

    21k GitHub stars~1.8k tokensUpdated today
    AI & LLM EngineeringAuto-check passed
  • MCP Scaffold

    timothywarner-org/claude-code

    Scaffold production-ready Python MCP servers using FastMCP. An agent skill from timothywarner-org/claude-code.

    224 GitHub stars~940 tokensUpdated 2 mo ago
    Agent WorkflowsAuto-check passed

More from llama-farm/llamafarm

All 19 skills in this repo
  • Reflect

    llama-farm/llamafarm

    Analyze the current session and propose improvements to skills.

    836 GitHub stars~1.5k tokensUpdated 4 mo ago
    Auto-check: notes
  • Temp Files

    llama-farm/llamafarm

    Guidelines for creating temporary files in system temp directory.

    836 GitHub stars~515 tokensUpdated 4 mo ago
    Auto-check: notes
  • CLI Skills

    llama-farm/llamafarm

    CLI best practices for LlamaFarm. An agent skill from llama-farm/llamafarm.

    836 GitHub stars~1.2k tokensUpdated 4 mo ago
    Auto-check passed
  • Code Review

    llama-farm/llamafarm

    Comprehensive code review for diffs. An agent skill from llama-farm/llamafarm.

    836 GitHub stars~2.3k tokensUpdated 4 mo ago
    Auto-check: notes
  • Commit Push PR

    llama-farm/llamafarm

    Commit changes, push to GitHub, and open a PR. An agent skill from llama-farm/llamafarm.

    836 GitHub stars~2.3k tokensUpdated 4 mo ago
    Auto-check: notes
  • Common Skills

    llama-farm/llamafarm

    Best practices for the Common utilities package in LlamaFarm.

    836 GitHub stars~885 tokensUpdated 4 mo ago
    Auto-check passed

Works with

Questions about Config Skills

What does Config Skills do?

Configuration module patterns for LlamaFarm. An agent skill from llama-farm/llamafarm. Config Skills is an agent skill from llama-farm/llamafarm. Configuration module patterns for LlamaFarm.

How do I install Config Skills in Claude Code?

Run `npx skills add llama-farm/llamafarm --skill config-skills -a claude-code`. Or copy the skill folder (.claude/skills/config-skills in llama-farm/llamafarm) into .claude/skills/config-skills in your project. Claude Code loads it when a task matches its description.

How do I install Config Skills in Codex?

Run `npx skills add llama-farm/llamafarm --skill config-skills -a codex`. Or copy the skill folder (.claude/skills/config-skills in llama-farm/llamafarm) into .agents/skills/config-skills in your project. Codex loads it when a task matches its description.

Can I use Config Skills in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add llama-farm/llamafarm --skill config-skills -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/config-skills, .gemini/skills/config-skills, .github/skills/config-skills and .opencode/skills/config-skills in your project.

What does Config Skills need to run?

Going by SKILL.md and its folder, Config Skills needs the command-line tools its instructions call (uv, nx and ruff). Our summary lists: Python 3. Its frontmatter pre-approves these tools: Read, Grep, Glob.

Does Config Skills access the network?

SKILL.md contains no URLs. Its commands use uv, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Config Skills safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Config Skills use?

Config Skills is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Config Skills use?

About 1.3k tokens (SKILL.md is roughly 5.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Config Skills?

Skills that share tags, products or a category with Config Skills: Building Pydantic AI Agents (docling-project/docling, 69k stars), Fastcrud (benavlabs/fastcrud, 1.6k stars), Prompt Engineering Patterns (wshobson/agents, 40k stars) and A2ui Generate Pydantic Models (a2ui-project/a2ui, 17k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Config Skills?

llama-farm (a GitHub organization) maintains it in llama-farm/llamafarm, which has 836 GitHub stars. The repository holds 19 skills in this directory. The repository was last updated on June 10, 2026.

Source: llama-farm/llamafarm on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.