A pull-request workflow that runs the project's pre-push checks and opens a pull request when validation passes.

Use it when work is ready for review and you need to validate tests, recheck reported results, and create a pull request.

It reduces the risk of asking others to review code that has already failed local tests or contains stale test results.

pr — Skill for Claude Code by SteveGJones

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.

Any agent

npx skills add SteveGJones/ai-first-sdlc-practices --skill pr

Clone the repo

git clone --depth 1 https://github.com/SteveGJones/ai-first-sdlc-practices

Made for: Claude Code.

Or install sdlc-core, the plugin that ships this one along with the rest of its 10 skills, 5 agents, 2 hooks.

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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/stevegjones/ai-first-sdlc-practices/pr/github.svg)](https://agentmods.dev/skills/stevegjones/ai-first-sdlc-practices/pr)

Your own site

<a href="https://agentmods.dev/skills/stevegjones/ai-first-sdlc-practices/pr"><img src="https://agentmods.dev/badge/skills/stevegjones/ai-first-sdlc-practices/pr/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/stevegjones/ai-first-sdlc-practices/pr"><img src="https://agentmods.dev/badge/skills/stevegjones/ai-first-sdlc-practices/pr.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 19 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 685 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits

NVIDIA SkillSpector pass 7 Sept 2026

How audits are shown

Origin original 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 5.1	$0.00019	$0.00685
Opus 5	$0.00010	$0.00342
Sonnet 5	$0.00004	$0.00137
Haiku 4.5	$0.00002	$0.00068

Measured 9d ago against content hash b0d19d3d58a1, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

pr 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 9d 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.

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.

plugins/sdlc-core/skills/pr/SKILL.md · 80 lines

How it starts

The opening of the file, as written. The whole thing — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Create Pull Request

Run full validation, then create a PR if clean.

Steps

Run pre-push validation

/sdlc-core:validate --pre-push

If validation fails, report the issues and stop. Do NOT push or create PR.
Re-verify any test counts cited in the PR body.

--pre-push runs the pytest suite only. If the draft PR body cites results from integration smokes, E2E suites, soak tests, container tests, or any other harness outside local-validation.py, re-run those exact suites in this session and update the counts in the body to match the fresh run.

Example: a PR body saying "266 unit tests, 20/20 container smoke, 8/8 sequential E2E, 18/18 fresh-user-flow" requires pytest tests/ -q, bash tests/integration/workforce-smoke/run-containers.sh, bash tests/integration/workforce-smoke/run-e2e.sh, and bash tests/integration/workforce-smoke/run-fresh-user-flow.sh to all run this session before the PR is opened.

Session memory of test counts goes stale fast — fixtures grow, assertions drift, environments change. Only numbers you have just observed this session belong in the body. If a suite cannot run in this environment (missing binary, no Docker, etc.), delete the number from the body and say so explicitly rather than leaving a stale figure that cites another machine's result.

If the PR already exists and counts have drifted post-creation, update the body in place rather than closing and recreating:
```
gh pr edit <number> --body-file <updated-body.md>
```
Verify required artifacts exist:
- Feature proposal in docs/feature-proposals/
- Retrospective in retrospectives/
- If either is missing, warn the user and ask whether to proceed.
If validation passes, proceed:
- Check if the branch tracks a remote: git branch -vv
- Push to remote with tracking: git push -u origin <branch>
- Base branch defaults to main unless $ARGUMENTS specifies otherwise

Read the full file on GitHub · 80 lines

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.

9d ago First seen · 80 lines · 19 tokens per session scan A b0d19d3d58a1

Subscribe to this mod's changes

pr is a skill published in the GitHub repository SteveGJones/ai-first-sdlc-practices (41 stars, last pushed 1mo ago), licensed MIT. It adds 19 tokens to every session and 685 once invoked, about $0.0001 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.

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