Agent skill

Python Pep Author

by pproenca in pproenca/dot-skills

Drafting Python Enhancement Proposals (PEPs) — proposing a Python language feature, a standard library change, an interoperability standard, or an informational/process document for the Python…

MITAuto-check passedDevelopment

Install Python Pep Author

skills CLI
$ npx skills add pproenca/dot-skills --skill python-pep-author -a claude-code

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

GitHub CLI
$ gh skill install pproenca/dot-skills python-pep-author --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/pproenca/dot-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/.experimental/python-pep-author .claude/skills/python-pep-author && 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
python-pep-author
GitHub stars
214
Token cost
~2.1k tokens
SKILL.md length
854 words
Files
11 (incl. scripts, references, assets)
Skills in repo
182
Repo updated
First seen
Licence
MIT

At a glance

Drafting Python Enhancement Proposals (PEPs) — proposing a Python language feature, a standard library change, an interoperability standard, or an informational/process document for the Python…

  • Works in 7 steps: Vet the idea (before writing anything) → Choose the PEP type → Scaffold the file → …
  • Propose a Python feature
  • SKILL.md covers When to Apply, Prerequisites, Workflow Overview and Reference Files, plus 3 more sections
  • Runs Shell scripts from its folder

What it does

Python Pep Author is an agent skill from pproenca/dot-skills. Drafting Python Enhancement Proposals (PEPs) — proposing a Python language feature, a standard library change, an interoperability standard, or an informational/process document for the Python community. Covers all three PEP types (Standards Track, Informational, Process): choosing the right type, scaffolding a valid reStructuredText pep-NNNN file, filling each required section to the acceptance bar, linting the headers, and navigating the sponsor / submission / Steering Council review process. Trigger on "write…

Its SKILL.md is about 2.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 14 other files, including scripts, reference files and assets (for example `gotchas.md`, `metadata.json` and `references/header-fields.md`).

It sits in Development, covering Proposals and quotes, Linting and formatting and Project scaffolding. It works with Python. The repository describes itself as: A collection of AI agent skills following the Agent Skills open format. The licence is MIT.

When your agent uses it

  • Propose a Python feature
  • Create a Python Enhancement Proposal
  • Someone is preparing a proposal for the Python Discourse

Example prompts

  • “write a PEP”
  • “draft a PEP”
  • “propose a Python feature”
  • “/python-pep-author”

Requirements

  • Python 3
  • A Bash shell

Workflow steps

7 steps, taken from the step headings in SKILL.md.

  1. Vet the idea (before writing anything)
  2. Choose the PEP type
  3. Scaffold the file
  4. Draft each section
  5. Self-check the draft
  6. Submit
  7. Review & resolution

What it can do on your machine

Read from SKILL.md and the folder at commit cf93c57. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 2 files in scripts/ (Shell), which the agent can run.

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

  • Network

    Links to these hosts (documentation or services it may open):

    • github.com
    • peps.python.org
    • discuss.python.org

    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

Python Pep Author loads about 2.1k tokens when it runs, and up to ~7.3k if it reads all its reference files. Until then it costs about 219 tokens; SKILL.md has 854 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~219
When it runs · the whole SKILL.md, loaded when a task matches
~2.1k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~7.3k

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); the scripts in this folder are not scanned.

SKILL.md

The full file from pproenca/dot-skills at commit cf93c57, republished under its MIT licence (© pproenca). 854 words, ~2,089 tokens.

Download SKILL.mdSave it as .claude/skills/python-pep-author/SKILL.md (or your agent's skills folder). This skill also uses 10 other files; get the full folder from GitHub.
name
python-pep-author
description
Drafting Python Enhancement Proposals (PEPs) — proposing a Python language feature, a standard library change, an interoperability standard, or an informational/process document for the Python community. Covers all three PEP types (Standards Track, Informational, Process): choosing the right type, scaffolding a valid reStructuredText pep-NNNN file, filling each required section to the acceptance bar, linting the headers, and navigating the sponsor / submission / Steering Council review process. Trigger on "write a PEP", "draft a PEP", "propose a Python feature", "create a Python Enhancement Proposal", "PEP template", or when someone is preparing a proposal for the Python Discourse or python-dev. Use it even if the user only says "PEP" or doesn't mention reStructuredText — the headers, sections, and process are exactly what trips PEP authors up.

Write a Python Enhancement Proposal (PEP)

A PEP is the design document the Python community uses to propose a new language feature, a stdlib change, an interoperability standard, or a process/informational guideline. This skill takes an author from a rough idea to a correctly-formatted, process-compliant draft ready for submission to the python/peps repository.

The hard parts of a PEP are not the prose — they are getting the type right, the header preamble valid, the sections complete to the acceptance bar, and following the process (vetting, sponsorship, review). This skill bundles two scripts for the deterministic parts and reference docs for the judgement calls.

When to Apply

  • The user asks to write / draft / structure a PEP or a "Python Enhancement Proposal".
  • The user wants to propose a Python language or standard-library feature and needs it written up formally.
  • The user has an idea they've been discussing on the Python Discourse and wants to turn it into a PEP draft.
  • The user needs the PEP template, header fields, or section structure explained or generated.
  • The user is revising an existing PEP (changing status, adding a Resolution, addressing review feedback).

Do not use this skill for internal company RFCs / design docs (use dev-rfc) — a PEP is specifically a proposal to the upstream CPython / Python community governed by PEP 1.

Prerequisites

  • Bash + coreutils (awk, sed, grep, date) for the two scripts — present by default on macOS/Linux.
  • A clone of, or a fork of, github.com/python/peps only when you're ready to submit (Step 6). Drafting needs no repo.
  • No Python runtime is required to draft or lint; the reference implementation (if any) is the author's separate codebase.

Workflow Overview

1. Vet the idea ────► 2. Choose the type ────► 3. Scaffold the file
   (is it PEP-able?)     (Standards/Info/Process)   (scripts/new-pep.sh)
                                                          │
   6. Submit ◄──── 5. Self-check ◄──── 4. Draft each section
   (sponsor, PR)      (scripts/check-pep.sh)   (to the acceptance bar)
        │
        ▼
   7. Review & resolution ──► update Status + Resolution header
1. Vet the idea (before writing anything)

A PEP that duplicates prior work or isn't community-wide in scope will be rejected on sight. Post the idea to the Ideas category of the Python Discourse first (or the Typing / Packaging category if specialised). Confirm it's original, applicable to the whole community, and not already settled by a past discussion. See references/workflow.md for venues and what to check.

2. Choose the PEP type

There are exactly three: Standards Track, Informational, Process. The type determines required headers (e.g. Python-Version, Resolution) and the bar for acceptance. Pick with references/pep-types.md.

3. Scaffold the file

Generate a valid, correctly-headed reStructuredText file rather than hand-typing the preamble (the field set and ordering are exact):

bash
scripts/new-pep.sh \
  --title "A short descriptive title" \
  --author "Random J. User <random@example.com>" \
  --type "Standards Track" \
  --python-version 3.15            # Standards Track only; omit otherwise

This writes pep-9999.rst (9999 = placeholder; PEP editors assign the real number), sets Status: Draft and today's Created date, and enforces the 44-character title limit. Run scripts/new-pep.sh with no args for full usage.

4. Draft each section

Fill the body sections in the canonical PEP 12 order: Abstract → Motivation → Specification → Rationale → Backwards Compatibility → Security Implications → How to Teach This → Reference Implementation → Rejected Ideas → Open Issues → Acknowledgements → Footnotes → Change History → Copyright. Each section has a specific job and a quality bar — read references/sections.md before drafting, and consult references/header-fields.md for any header you need to fill in (Sponsor, Discussions-To, Requires, etc.).

The acceptance bar (from PEP 1): the proposal must be a clear and complete description, represent a net improvement, have a solid implementation that doesn't unduly complicate the interpreter, and be "pythonic". Write to that bar.

Show full SKILL.md (330 more words)Show less
5. Self-check the draft

Lint the headers and required structure before showing it to anyone:

bash
scripts/check-pep.sh pep-9999.rst

It verifies the required headers are present, the title length, valid Status/Type values, the Created date format, the mandatory CC0 copyright notice, and an Abstract section — reporting PASS / WARN / FAIL and exiting non-zero on any FAIL. Fix every FAIL.

6. Submit

If no co-author is a CPython core developer, you must first find a sponsor (a core developer who shepherds the PEP). Then fork python/peps, add pep-NNNN.rst, list authors/sponsors in .github/CODEOWNERS, and open a pull request. PEP editors review for format and soundness and assign the number. Full steps and the role definitions are in references/workflow.md.

7. Review & resolution

When the authors (and sponsor) judge it ready, content review and the accept/reject decision rest with the Steering Council (or an appointed PEP-Delegate). On a decision, update the Status and add a Resolution header linking to the pronouncement. The full status lifecycle and valid transitions are in references/status-lifecycle.md.

Reference Files

FileRead it when
references/workflow.mdVetting, finding a sponsor, submitting, the review process, the roles, transferring ownership
references/pep-types.mdChoosing between Standards Track / Informational / Process
references/header-fields.mdFilling any preamble field — formats, required vs optional, examples
references/status-lifecycle.mdSetting or changing Status, understanding valid transitions, the Resolution header
references/sections.mdDrafting the body — what each section must contain, RST conventions, the acceptance bar

Scripts

ScriptWhat it does
scripts/new-pep.shScaffolds a valid pep-NNNN.rst from the template, substituting the header fields and enforcing the title-length limit
scripts/check-pep.shLints a PEP draft against PEP 1 / PEP 12 rules (headers, status/type, date format, copyright, abstract)

The template the scripts use lives at assets/templates/pep-template.rst — copy it directly if you'd rather fill the headers by hand.

Gotchas

See gotchas.md. The most common early mistakes: skipping the Discourse vetting step, choosing Standards Track for what is really a Process PEP, omitting the mandatory CC0 copyright notice, and a title over 44 characters.

  • dev-rfc — internal/company RFCs, design docs, and architecture docs (not upstream Python proposals).

© pproenca, MIT. 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 10 other files (scripts, references, assets) in skills/.experimental/python-pep-author of pproenca/dot-skills.

  • SKILL.md
  • assets/templates/pep-template.rst
  • gotchas.md
  • metadata.json
  • references/header-fields.md
  • references/pep-types.md
  • references/sections.md
  • references/status-lifecycle.md
  • references/workflow.md
  • scripts/check-pep.sh
  • scripts/new-pep.sh

Open the folder on GitHubat commit cf93c57

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Works with

Questions about Python Pep Author

What does Python Pep Author do?

Drafting Python Enhancement Proposals (PEPs) — proposing a Python language feature, a standard library change, an interoperability standard, or an informational/process document for the Python…. Python Pep Author is an agent skill from pproenca/dot-skills. Drafting Python Enhancement Proposals (PEPs) — proposing a Python language feature, a standard library change, an interoperability standard, or an informational/process document for the Python community.

When should I use Python Pep Author?

Python Pep Author fits situations like: propose a Python feature; create a Python Enhancement Proposal; someone is preparing a proposal for the Python Discourse.

How do I install Python Pep Author in Claude Code?

Run `npx skills add pproenca/dot-skills --skill python-pep-author -a claude-code`. Or copy the skill folder (skills/.experimental/python-pep-author in pproenca/dot-skills) into .claude/skills/python-pep-author in your project. Claude Code loads it when a task matches its description.

How do I install Python Pep Author in Codex?

Run `npx skills add pproenca/dot-skills --skill python-pep-author -a codex`. Or copy the skill folder (skills/.experimental/python-pep-author in pproenca/dot-skills) into .agents/skills/python-pep-author in your project. Codex loads it when a task matches its description.

Can I use Python Pep Author 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 pproenca/dot-skills --skill python-pep-author -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/python-pep-author, .gemini/skills/python-pep-author, .github/skills/python-pep-author and .opencode/skills/python-pep-author in your project.

What does Python Pep Author need to run?

Going by SKILL.md and its folder, Python Pep Author needs a shell for the scripts in its folder. Our summary lists: Python 3; A Bash shell.

Does Python Pep Author access the network?

SKILL.md names 3 domains. As links in the text: github.com, peps.python.org and discuss.python.org. This is read from the text; nothing was executed.

Is Python Pep Author 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Python Pep Author use?

Python Pep Author is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Python Pep Author use?

About 2.1k tokens (SKILL.md is roughly 8.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 5.2k tokens, read only when the agent opens those files.

What are the alternatives to Python Pep Author?

Skills that share tags, products or a category with Python Pep Author: Modern Python Toolchain (XiaomiMiMo/MiMo-Code, 14k stars), Modern Python Tooling (trailofbits/skills, 7.4k stars), Plugin Forge (s0912758806p/agentic-sop-to-work, 209 stars) and Scaffold Python (SpecterOps/skills, 702 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Python Pep Author?

pproenca (a GitHub user) maintains it in pproenca/dot-skills, which has 214 GitHub stars. The repository holds 182 skills in this directory. The repository was last updated on August 15, 2026.

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