What is pythonic-code?

A set of guidelines for writing and reviewing clear Python code. Python is a programming language; the guidance focuses on explicit behavior, useful types, simple reasoning, and appropriate data models.

Use it when creating, refactoring, simplifying, or reviewing nontrivial Python code and deciding whether its structure and behavior are clear and idiomatic.

It helps make Python easier to understand, test, and maintain. It also identifies unnecessary abstractions and overly complicated helper or object structures.

pythonic-code — Skill by basicmachines-co

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/basicmachines-co/basic-memory/pythonic-code

Any agent

npx skills add basicmachines-co/basic-memory --skill pythonic-code

Clone the repo

git clone --depth 1 https://github.com/basicmachines-co/basic-memory

Made for: Claude Code, Codex.

Per session 72 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,634 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. Scan, not verified.

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.

Model	Per session	Once invoked
Fable 5	$0.00072	$0.01634
Opus 5	$0.00036	$0.00817
Sonnet 5	$0.00014	$0.00327
Haiku 4.5	$0.00007	$0.00163

Measured 2d ago against content hash 04c25a2f0c03, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

pythonic-code 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 2d ago.

The scan reads SKILL.md. This mod also ships 5 executable files (evals/files/accepted_preparation.py, evals/files/accepted_snapshot.py, evals/files/test_accepted_preparation.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

.agents/skills/pythonic-code/SKILL.md · 154 lines

The source is not reproduced here

Licensed AGPL-3.0

The repository is licensed AGPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.

Read it on GitHub

Files

What ships with it

11 files 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.

2d ago First seen · 154 lines · 72 tokens per session scan A 04c25a2f0c03

Subscribe to this mod's changes

pythonic-code is a skill published in the GitHub repository basicmachines-co/basic-memory (3,804 stars, last pushed 2d ago), licensed AGPL-3.0. It adds 72 tokens to every session and 1,634 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Code review Data and AI LLM Writing and docs ai claude mcp open-source python

review-pr

Review a Dograh pull request, branch diff, or pasted patch for repo-specific security and correctness risks that are not obvious from generic FastAPI, Next.js, or Python conventions. Use when the user asks to review a PR, audit a diff, check whether changes are safe to merge, review their own changes, or asks what to…

dograh-hq/dograh · 109 tokens

review-agents-md

Audit Dograh AGENTS.md files for drift against the live repo and for bad scope boundaries between parent and child docs. Use when the user asks to review existing AGENTS files, identify stale guidance, decide whether a subtree needs its own AGENTS.md, or update the AGENTS.md hierarchy under the repo root, api/, or ui/.

dograh-hq/dograh · 82 tokens

merge-pipecat-upstream

Merge the latest upstream pipecat-ai/pipecat tag into the pipecat submodule fork (dograh-hq/pipecat) and bump the dograh repo to it. Use whenever the user asks to bump, upgrade, sync, or merge pipecat, resolve pipecat merge conflicts, audit whether upstream changes break or supersede Dograh's in-fork patches, or…

dograh-hq/dograh · 102 tokens

pythonic-code