AI Engineering Workflow Skills

Canonical source for engineering workflow, product, and productivity skills.

In plain terms: you tell your agent what stage of a software change you're in — scoping it, defining done, breaking it into issues, reviewing before merge, releasing, or handing off context — and it routes to the matching engineering-workflow skill instead of improvising its own process each time.

Install

Pick whichever fits how you work. All three end up in the same place: the skill files sitting where your agent looks for them.

1. Everything, via npx (recommended)

npx skills@latest add wakqasahmed/ai-engineering-workflow-skills

This installs every skill in the pack for whichever agent you're using (Claude Code, Cursor, Codex, and 70+ others — see the skills CLI). Add -g to install once for every project instead of per-project, or -a claude-code to target one agent specifically.

2. Just one skill

Don't need the whole pack? Install a single skill by its name (skill names match their folder, e.g. clarify-work):

npx skills@latest add wakqasahmed/ai-engineering-workflow-skills --skill clarify-work

Or point straight at one skill's folder on GitHub:

npx skills add https://github.com/wakqasahmed/ai-engineering-workflow-skills/tree/main/skills/engineering/clarify-work

3. No Node/npx available — manual zip install

  1. On this repo's GitHub page: Code → Download ZIP.
  2. Unzip it.
  3. Copy whichever skills/<category>/<name>/ folder(s) you want into your agent's own skills directory (for Claude Code, that's .claude/skills/ in your project, or ~/.claude/skills/ for a global install; other agents use their own equivalent path).

No installer, no dependency — just files your agent already knows how to read.

Use it — step by step

Start with workflow-router if you're not sure which skill applies — it routes a work request to the smallest applicable delivery workflow.

Skill What it covers
ai-agent-pr-metadata Add GitHub-visible AI agent and AI code-review metadata and exact agent labels without adding AI attribution to commits, and scope Alibaba/Open Code Review's review surface to control LLM token spend.
changesets-release Records release intent with Changesets and guides semver, changelog, CI, and artifact-version checks for independently distributed packages.
clarify-work Clarify non-trivial engineering work before implementation by resolving ambiguity, terminology, constraints, and the smallest viable path.
decompose-to-issues Break high-level work into independently executable GitHub issues using vertical slices.
define-done Define acceptance criteria, risk level, and verification before editing.
hitl-blocker Convert human-only blockers into visible GitHub issues.
open-code-review-setup Set up Alibaba Open Code Review (OCR) on a repository that lacks it, or audit and update an existing setup.
release-gate Check deployment, staging, rollback, and health verification before release.
review-gate Run an independent semantic review gate before merging non-trivial work, on top of (not duplicating) Alibaba Code Review and CI.
subagent-pipeline Run a cold-start implementer, reviewer, and fixer subagent chain for one issue, gated by CI, ending in a staging PR.
to-prd Synthesize the current conversation and repository context into a concise product and engineering spec, publish it to the project issue tracker, and gate agent readiness before decomposition.
workflow-router Routes a software-work request to the smallest applicable delivery workflow and records repository conventions once.
roast Use when someone asks to roast an idea, pressure-test or stress-test an idea, validate a business idea, "convene the council", get a brutal second opinion before building something, or says "/roast".
handover Compact the current conversation into a handover document a fresh agent can pick up and continue seamlessly.

Contents

The installable skills live in skills/engineering/, skills/filament/, skills/product/, and skills/productivity/.

Aggregate catalogue

Changes merged to this repository are automatically synchronized to wakqasahmed/skills. Treat this repository as the source of truth for engineering workflow skills.

Outcome-eval harness status

Several skills already have a deterministic eval layer (free, runs on every PR). The gated model-harness layer — real skill-enabled vs. disabled comparisons against a live model — is still open work for 8 skills: #57, #59–#65.

Fund the real harness runs

This skill's deterministic checks run free on every PR. Proving its outcome-eval harness with real, metered model calls costs money:

  • Bitcoin (BTC): bc1p5xqamscrz7nu0d8jdmj748rj75sk8khtyxypn3qvsdjms4t4uw2qsjn0he
  • Ethereum (ETH) / any ERC-20 including stablecoins: 0x59bc573e414D62d44461234dEf438247dfc3Cf6A

Double-check every character against this page before sending. Full portfolio picture and rationale: wakqasahmed/skills.