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skyhook-skills

Composable AI dev-workflow and research commands for Claude Code, Codex, and Cursor Agent. An autonomous plan → implement → review → PR → converge loop, cross-model review, product/design/UX critique, and decision-focused competitive research.

Built by Skyhook for building Radar; generic enough to use anywhere.

What you get

The loop

  • /autodev [--auto] <task> — full autopilot: plan → implement → review → PR → converge, end-to-end, stopping only at real decisions. Default mode gates on the plan before coding; --auto makes product calls itself (logging assumptions) and stops only for an irreversible-action ceiling.
  • /plan-loop — draft a plan, cross-review it with the other model, triage the critique skeptically, iterate, gate.
  • /review-loop — proactively review the current code (self + cross-model), triage, fix, update the PR — loop until clean.

Review & critique (three altitudes — right thingearning its keepcorrect)

  • /product-review — questions what to build and how users perceive it: premise, top user journeys (ranked 0–10), UX shape, comprehension, states, AI-slop. Borrows forcing-function patterns from gstack and OneRedOak + a journey-ranking + non-expert-comprehension lens.
  • /review, /simple (anti-over-engineering), /triage-findings, /fix-findings.

External contributions

  • /external-pr-review <GitHub URL> [focus] — assesses an outside contribution's premise and implementation, then recommends the shortest safe path to merge. Classifies findings as author changes, maintainer fixes, follow-ups, deferred work, or findings to drop.
  • /external-issue-triage <GitHub URL> [focus] — drafts a timely acknowledgment, investigates a bug or feature request, and prepares a maintainer recommendation. Keeps public replies separate from private analysis.

Both default to review and recommendations; posting and contributor-branch changes need explicit authorization. They follow the project's documented scope rather than assuming a particular product policy.

Cross-model review

  • /cross-review — runs a review by the configured secondary model — Codex or Cursor — prints it verbatim, then triages it skeptically (never auto-accepts). Pick the reviewer via ~/.claude/skyhook-skills.json ({"reviewer":"codex|cursor","model":"…"}), the SKYHOOK_REVIEWER env var, or a consult cursor / consult codex directive. /codex-review forces Codex.

PR

  • /pr, /fix-pr, /fix-pr-loop (reacts to CI + bot reviewers until converged).

Hand it over

  • /review-packet [pr|set|design|research] [focus] — packages work for guided review: a document that leads with the decisions the reviewer has to make and puts the evidence for every claim right beside it. Claude publishes an artifact; Codex publishes through Sites. Ask for local-only output to get self-contained HTML with embedded evidence (no PDF). If publishing is unavailable, the skill hands over HTML and explains the gap. Cursor defaults to local HTML. Built for large PRs, PR sets, rendered UI, and design or research proposals — the cases where review otherwise means scrolling a diff and taking your word for it.

Research

  • /competitive-research [implementation|product|positioning|hybrid] [focus] — investigates how comparable products handle the active decision using primary evidence: OSS source and tests for implementation details, official product material for UX/features, or current first-party pages for positioning. Compares the tradeoffs with the current approach and recommends what to keep, adopt, hybridize, or defer.

Utilities

  • /housekeeping — read-only audit of a dev machine's disk, caches, stale tools, and services; triages findings into reclaimable / worth-reviewing / leave-alone and never mutates anything without explicit approval.

Cross-cutting: never auto-accept a reviewer (your own, the cross-model pass, or PR bots) — every finding is triaged with evidence; cross-review only when nontrivial; every loop caps and reports; review at altitude (a clean implementation of the wrong thing is still wrong).

Concepts

A few principles run through every command:

  • Review at altitude, intent before details. Before judging whether code is correct, judge whether it's the right thing to build and the right design — approach, architecture, UX, user journey. A clean implementation of the wrong thing is still wrong. /product-review is the dedicated pass for this.
  • Research at the task's altitude. Competitive work should answer the decision in front of you: source-level evidence for implementation semantics, product evidence for UX and features, market evidence for positioning. Prefer representative patterns over exhaustive feature grids.
  • Never auto-accept a reviewer. Every finding — your own, the cross-model pass, or a PR bot — is triaged against the real code, with evidence cited on every skip. Cross-model reviewers are often right about blind spots and often wrong about things already handled; you decide.
  • Compose, don't rebuild. The loops are thin conductors over small, single-purpose commands. Edit one (e.g. /triage-findings) and every loop that uses it inherits the change.
  • Scale ceremony to the task. Trivial changes skip the loop; nontrivial work gets cross-review + product critique. Steps are judgment calls, and you can steer them inline (/review-loop consult codex, /autodev no PR, quick, focus on auth).
  • Bring-your-own verification (/qa). The loops call /qa, but each repo defines what verification means there — type-check, tests, and optionally a /visual-test. The workflow stays repo-agnostic.

Example run-summary

Every loop narrates itself and closes with a scannable audit ledger:

📋 review-loop · feature/bulk-actions
 🔗 PR [#910](https://github.com/your-org/your-repo/pull/910) · OPEN · checks 4 ✓ · 2 pending (Backend, Bugbot)
 round 1
   🔎 self-review     6 findings
   🔵 codex review    8m · 13 findings
   ⚖️ triage          5 fix · 7 skip · 1 discuss
   🔧 fix             5 applied
   ✅ qa              tsc ✓ · test ✓ · visual-test skipped (no UI delta)
   📤 PR              pushed + body
 result: converged locally · 1 round · 5 fixed · 7 skipped · 1 open · CI pending
 open for you:
   • [discuss] <the one question that needs your call>

Install and update

Claude Code uses the plugin marketplace. Codex and Cursor Agent use the same Agent Skill adapters and canonical command bundle under ~/.codex/skills; Cursor discovers that directory for compatibility, so installing for both does not create two copies.

The Claude plugin exposes the full command catalog. Codex and Cursor expose the companion entry points autodev, plan-loop, review-loop, product-review, claude-review, competitive-research, review-packet, external-pr-review, and external-issue-triage; those skills use the shared canonical commands internally.

Agent Distribution Invoke a skill
Claude Code skyhook-skills marketplace plugin /skyhook-skills:competitive-research
Codex User-level Agent Skills $competitive-research
Cursor Agent The same Agent Skills as Codex /competitive-research

Claude Code

First install — run these inside Claude Code:

/plugin marketplace add skyhook-io/skyhook-skills
/plugin install skyhook-skills@skyhook-skills

Update — run these in a terminal:

claude plugin marketplace update skyhook-skills
claude plugin update skyhook-skills@skyhook-skills

Then apply the update to an already-running Claude Code session:

/reload-plugins

Use /plugin to browse installed commands or enable marketplace auto-update. Third-party marketplace auto-update may be disabled, so the explicit update commands above are the reliable path. See the Claude Code plugin documentation.

Codex

First install and every update use the same idempotent command:

curl -fsSL https://raw.githubusercontent.com/skyhook-io/skyhook-skills/main/scripts/install-codex.sh | bash

The installer fetches main, updates the Skyhook adapters and canonical commands, and leaves unrelated skills alone. Codex normally detects skill changes automatically; if the update does not appear, restart Codex. Verify with /skills, then invoke a skill with $competitive-research. See the OpenAI Agent Skills documentation.

If you prefer a checkout over piping from the network, clone this repository, git pull --ff-only for each update, then run bash scripts/install-codex.sh from the repository root.

Cursor Agent

Cursor Agent discovers ~/.codex/skills, so it uses the same install and update command as Codex:

curl -fsSL https://raw.githubusercontent.com/skyhook-io/skyhook-skills/main/scripts/install-codex.sh | bash

If you already ran that command for Codex, there is nothing else to install. Start a new Cursor Agent session (or restart Cursor) after an update. Verify under Customize → Skills or invoke /competitive-research in Agent chat. Updating the Cursor binary with cursor-agent update is separate and does not update these skills. See the Cursor Agent Skills documentation.

The /qa seam — bring your own verification

The loops call /qa to verify a change, but /qa is repo-provided: each repo defines what verification means there (type-check, tests, and optionally a /visual-test). Drop a .claude/commands/qa.md in your repo, e.g.:

---
description: Verify this change — type-check, tests, and visual-test when a UI change warrants it
---
# QA
- Code changed → run your type-check + tests (e.g. `make tsc` / `make test`, `npm run tsc`, `go test ./...`).
- UI changed → lean toward `/visual-test` for feature-scale rendered changes; skip for small/non-visual. Report status (ran → link the screenshot dir; skipped → why).

No /qa? The loops fall back to plain build/test detection.

Prerequisites & optional integrations

  • /cross-review reviewers (pick via ~/.claude/skyhook-skills.json, SKYHOOK_REVIEWER, or a consult <x> directive):
    • codex — needs the official codex plugin (/plugin marketplace add openai/codex-plugin-cc).
    • cursor — needs the Cursor CLI (cursor-agent) logged in, or CURSOR_API_KEY set; defaults to the gpt-5.6-high model. For a genuine second opinion when driving from Claude, keep it on a non-Claude model.
  • Codex → Claude (the claude-review Codex skill) needs the claude CLI. On macOS, run it un-sandboxed so it can read Keychain auth, and (if Codex's guardian blocks the export) add a narrow [auto_review] allowance in ~/.codex/config.toml. Long reviews should use streamed JSON and the final result field; plain claude -p can look idle while it is still reading/thinking.
  • /review --deep uses the pr-review-toolkit plugin if installed (optional).

License

MIT — see LICENSE.

About

Composable AI dev-workflow commands for Claude Code (+ Codex): autonomous plan→implement→review→PR→converge loop, cross-model review, and product/UX critique.

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