python-configuration

A guide for managing Python program settings through environment variables, which hold values outside the code, and typed settings, which check their format.

In plain words
What is it for?
Use it to define one central settings object, load configuration, validate required values, and provide safe local defaults.
Why use it?
It keeps environment-specific values such as URLs, secrets, and feature flags out of source code. It also catches missing or invalid settings when the program starts.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/jartan-llc/grimoire/python-configuration
Any agent
npx skills add Jartan-LLC/grimoire --skill python-configuration
Clone the repo
git clone --depth 1 https://github.com/Jartan-LLC/grimoire

Made for: Claude Code, Codex.

Per session 14 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,318 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 95% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00014 $0.01318
Opus 5 $0.00007 $0.00659
Sonnet 5 $0.00003 $0.00264
Haiku 4.5 $0.00001 $0.00132

Measured yesterday against content hash b0a99900f973, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

python-configuration scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

95% identical to python-configuration — 15 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

plugins/pythonica/skills/python-configuration/SKILL.md · 205 lines

How it starts

The opening of the file, as written. The whole thing — 205 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Python Configuration Management

Externalize configuration from code using environment variables and typed settings. Well-managed configuration enables the same code to run in any environment without modification.

Core Concepts

1. Externalized Configuration

All environment-specific values (URLs, secrets, feature flags) come from environment variables, not code.

2. Typed Settings

Parse and validate configuration into typed objects at startup, not scattered throughout code.

3. Fail Fast

Validate all required configuration at application boot. Missing config should crash immediately with a clear message.

4. Sensible Defaults

Provide reasonable defaults for local development while requiring explicit values for sensitive settings.

Quick Start

from pydantic_settings import BaseSettings
from pydantic import Field

class Settings(BaseSettings):
    database_url: str = Field(alias="DATABASE_URL")
    api_key: str = Field(alias="API_KEY")
    debug: bool = Field(default=False, alias="DEBUG")

settings = Settings()  # Loads from environment

Fundamental Patterns

Pattern 1: Typed Settings with Pydantic

Create a central settings class that loads and validates all configuration.

from pydantic_settings import BaseSettings
from pydantic import Field, PostgresDsn, ValidationError
import sys

class Settings(BaseSettings):
    """Application configuration loaded from environment variables."""

    # Database
    db_host: str = Field(alias="DB_HOST")
    db_port: int = Field(default=5432, alias="DB_PORT")
    db_name: str = Field(alias="DB_NAME")
    db_user: str = Field(alias="DB_USER")
    db_password: str = Field(alias="DB_PASSWORD")

    # Redis
    redis_url: str = Field(default="redis://localhost:6379", alias="REDIS_URL")

    # API Keys
    api_secret_key: str = Field(alias="API_SECRET_KEY")

    # Feature flags
    enable_new_feature: bool = Field(default=False, alias="ENABLE_NEW_FEATURE")

    model_config = {
        "env_file": ".env",
        "env_file_encoding": "utf-8",
    }

# Create singleton instance at module load
try:
    settings = Settings()
except ValidationError as e:
    print(f"Configuration error:\n{e}")
    sys.exit(1)

Read the full file on GitHub · 205 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 205 lines · 14 tokens per session scan A b0a99900f973

Subscribe to this mod's changes

python-configuration is a skill published in the GitHub repository Jartan-LLC/grimoire (2 stars, last pushed 14d ago), licensed MIT. It adds 14 tokens to every session and 1,318 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 95% identical to python-configuration, differing in 15 lines, and is treated as a copy.

Related

Other skills, from other repositories

goutoujunshi

恋爱军师与情绪支持 skill。用于心动、暧昧、追求、聊天记录或截图分析、约会、关系确认、多人选择、冲突、冷淡、投入失衡、分手、复合、出轨、婚姻或家庭问题;也用于分析关系信号、设计主动推进或退出策略、润色可直接发送的话术,以及把冷读、自然流、Blueprint、Mystery 等经典社交体系转译成真实、互惠、可退出的沟通能力。支持分析ChatLab已有数据和经同意可撤销的长期关系档案,不负责导出聊天软件数据。首次使用时为用户及一个或多个目标对象建立包含 MBTI、主观综合评分和关系背景的档案。.

shengjidaguai-china/goutoujunshi · 175 tokens

gpt-image

Use this skill whenever a user asks to generate, create, draw, render, or edit images with GPT Image 2 / gpt-image-2, text-to-image, reference-image editing, inpainting, posters, typography, Chinese text, UI mockups, diagrams, or gallery prompts. Analyze the user's prompt, search the bundled Reference Gallery/craft…

wuyoscar/GPT-Image2-Skill · 120 tokens

pixel2motion

Turn a raster logo (PNG/JPG/WebP/screenshot) into a clean minimal SVG with edge smoothness as the primary hard gate and IoU optimized as high as reasonably possible without a fixed global threshold, then into a choreographed logo animation delivered as standalone JS-rendered HTML, applying Disney's 12 animation…

nolangz/pixel2motion · 163 tokens

beautify-github-readme

Redesign GitHub README homepages or create project-native pure SVG, hybrid SVG-composed PNG/WebP, and opt-in animated GIF assets. Use when a user asks to beautify, redesign, rebrand, visually upgrade, simplify, or audit a GitHub README; create only a hero, section headers, diagrams, badges, motion graphics, showcase…

oil-oil/beautify-github-readme · 143 tokens

submit-product-directories-v2-quality

SPD V2 Quality. Discover, deeply qualify, submit, and audit truthful product listings across Windows, macOS, and Linux-capable environments on relevant product, software, startup, app, and AI-tool directories with audience-value screening, SEO quality gates, action-level authorization, privacy controls, and…

flaqai/backlink_skills · 125 tokens

codex-autoresearch

Run autonomous, measurable experiments in a Git repository: change one hypothesis, verify a numeric metric, keep improvements, and revert failures. Use when the user wants Codex to keep iterating toward a numeric target in the foreground or as a detached background run. Do not use for ordinary one-shot coding…

leo-lilinxiao/codex-autoresearch · 80 tokens