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Python Pep Author

  • 67 installs
  • 191 repo stars
  • Updated July 24, 2026
  • pproenca/dot-skills

python-pep-author is a Claude Code skill for security. It helps solo builders move faster with AI-assisted coding.

Key points

  • python-pep-author
  • Security
  • AI-coding skill

Python Pep Author by the numbers

  • 67 all-time installs (skills.sh)
  • +5 installs in the week ending Aug 4, 2026 (Skillselion tracking)
  • Ranked #1,189 of 2,203 Security skills by installs in the Skillselion catalog
  • Data as of Aug 4, 2026 (Skillselion catalog sync)
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Listed on Skillselion
Installs67
repo stars191
Last updatedJuly 24, 2026
Repositorypproenca/dot-skills

How do I helps with security tasks during ai-assisted development?

Helps with security tasks during AI-assisted development.

Who is it for?

Best when you're working on security and need structured help with python-pep-author.

Skip if: Teams with no security needs, or anyone wanting a generic chat assistant without this specific workflow.

When should I use this skill?

When you need to helps with security tasks during ai-assisted development, or when python-pep-author is a claude code skill for security. it helps solo builders move faster with ai-assisted coding.

What you get

Structured output aligned to python-pep-author: python-pep-author; Security; AI-coding skill.

Files

SKILL.mdMarkdownGitHub ↗

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):

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.

5. Self-check the draft

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

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.

Related Skills

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

Related skills

FAQ

What does python-pep-author do?

python-pep-author is a Claude Code skill for security. It helps developers move faster with AI-assisted coding.

When should I use python-pep-author?

When you need to helps with security tasks during ai-assisted development, or when python-pep-author is a claude code skill for security. it helps developers move faster with ai-assisted coding.

What are the main capabilities?

python-pep-author; Security; AI-coding skill.

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