Turn rough project ideas, source-code summaries, or existing repositories into clear, professional GitHub documentation. GitHub Portfolio Builder AI helps students, developers, AI/ML engineers, and open-source contributors present their work more effectively. Generate structured README files, project overviews, installation guides, feature documentation, technology-stack sections, usage examples, and recruiter-friendly portfolio descriptions.
Paste a git diff and get a PR description, a changelog entry, and reviewer-risk callouts that name the file, what could break, and what to check. Only flags backed by the diff, and "no elevated-risk patterns found" when there are none. Built for AI-sized PRs.
Paste a git diff, get a review-ready pull request: a structured PR description (summary, what/why, test notes), risk callouts (migrations, API/contract changes, config, deletions), a reviewer attention map that surfaces the riskiest hunks first, and a self-review checklist tailored to the diff. For developers opening PRs with Claude Code, Codex, or any coding agent. Uses only the pasted diff; unknowns are [FILL IN]. No API key, no repo access, no personal data.
A senior-engineer-style code review assistant: severity-ranked findings, security smell detection, and constructive feedback across 8 language families.
Paste your staged changes, a diff, or a list of merged commits/PRs and get clean Conventional Commits messages, a grouped CHANGELOG entry in Keep a Changelog format, and a suggested Semantic Versioning bump (major/minor/patch) with the reason. Built for developers and coding agents (Claude Code, Codex) doing the everyday git loop and cutting releases. Uses only the pasted changes; unknowns are [FILL IN]. No API key, no repo access, no personal data.
Turn your GitHub project into a product-accurate tutorial or promo video, with a reviewable preview before rendering.
Read-only pre-merge check of your branches: conflicts, scope drift, leaked secrets and re-run tests, then a verdict per branch and a merge order.
I'm a full-stack engineer who's shipped and maintained Next.js (App Router), React, and TypeScript apps under real production load. I kept watching AI write code that looked done - then leaked NEXT_PUBLIC_ secrets, swallowed errors, and skipped every state but "success." Shipwright distills the senior-engineer checklist I reach for when things break at 2 a.m. - secrets, auth, input validation, caching, and the unhappy paths - so your AI ships production-grade code, not demos.