cognitive-core: Skill for Claude Code

.claude/skills/python-patterns/SKILL.md

python-patterns is a skill for Claude Code from mindcockpit-ai/cognitive-core. It costs 41 tokens per session (2,202 once invoked), scanned A, original, no licence file.

A guide to writing modern Python 3.12 and newer code, including type hints, dataclasses, Pydantic v2, and asynchronous programming.

In plain words
What is it for?
Use it to choose suitable Python structures, improve type annotations, work with validation models, and write async code.
Why use it?
It helps avoid outdated Python patterns and common mistakes when designing or reviewing Python code.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

This is mindcockpit-ai/cognitive-core's own configuration. It tells Claude Code how to work on cognitive-core itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything cognitive-core configures →

Reuse

Borrowing it

Nothing to install: this file belongs to mindcockpit-ai/cognitive-core. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/mindcockpit-ai/cognitive-core/main/.claude/skills/python-patterns/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/mindcockpit-ai/cognitive-core

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for python-patterns

README.md
[![agentmods](https://agentmods.dev/badge/skills/mindcockpit-ai/cognitive-core/python-patterns/github.svg)](https://agentmods.dev/skills/mindcockpit-ai/cognitive-core/python-patterns)
Your own site
<a href="https://agentmods.dev/skills/mindcockpit-ai/cognitive-core/python-patterns"><img src="https://agentmods.dev/badge/skills/mindcockpit-ai/cognitive-core/python-patterns/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for python-patterns

Your own site · 80×15
<a href="https://agentmods.dev/skills/mindcockpit-ai/cognitive-core/python-patterns"><img src="https://agentmods.dev/badge/skills/mindcockpit-ai/cognitive-core/python-patterns.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 41 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,202 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe.
Origin unknown No closer match found 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 5.1 $0.00041 $0.02202
Opus 5.5 $0.00016 $0.00881
Sonnet 5.5 $0.00008 $0.00440
Haiku 4.5 $0.00004 $0.00220

Measured 1mo ago against content hash 5fba341d8d80, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

python-patterns scanned grade A with 1 finding 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 1mo ago.

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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

tasks = [tg.create_task(fetch(url)) for url in urls]
.claude/skills/python-patterns/SKILL.md · 321 lines

The source is not reproduced here

A licence we could not identify

The repository carries a LICENSE file, but it is custom or dual enough that GitHub cannot name it and neither can this catalogue. Unknown terms are not permission, so the body is not copied here. Read the licence at the source and decide for yourself.

Read it on GitHub

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. 1mo ago First seen · 321 lines · 41 tokens per session scan A 5fba341d8d80

Subscribe to this mod's changes

python-patterns is a skill published in the GitHub repository mindcockpit-ai/cognitive-core (11 stars, last pushed 3d ago), with no licence file. It adds 41 tokens to every session and 2,202 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

matlab

Builds, reviews, migrates, and plans MATLAB or GNU Octave numerical workflows. Use for arrays, tabular/time data, tests, projects, graphics, MAT files, and explicit Python interoperability.

K-Dense-AI/scientific-agent-skills · 44 tokens

pennylane

Builds and differentiates PennyLane quantum circuits, hybrid PyTorch or JAX models, molecular VQE and QAOA workflows. Use for variational quantum algorithms, quantum machine learning, simulator validation, and moving validated circuits to provider plugins. For hardware-specific compilation use qiskit or cirq; for…

K-Dense-AI/scientific-agent-skills · 74 tokens

rocm-kernels

Provides guidance for writing and benchmarking optimized Triton kernels for AMD GPUs (MI355X, R9700) on ROCm, targeting HuggingFace diffusers (LTX-Video, SD3, FLUX) and transformers. Core kernels: RMSNorm, RoPE 3D, GEGLU, AdaLN. Includes XCD swizzle, autotune, diffusers integration patterns, and LTX-Video pipeline…

huggingface/kernels · 93 tokens

holoscan-install-wheel

Install Holoscan SDK Python wheel via pip into a venv. Use for Python installs; not for native C++/apt or Conda installs.

NVIDIA/skills · 37 tokens

typing-exclusion-worker

Python typing exclusion worker: remove assigned mypy exclusion modules in small scoped batches, fix typing issues, run validation, and produce a structured completion summary. Use when running parallel typing-debt workers or when asked to remove modules from pyproject mypy exclusion overrides.

getsentry/skills · 57 tokens

python

Python development with ruff, mypy, pytest - TDD and type safety.

alinaqi/maggy · 18 tokens