Getting Started with cursor-kenji
August 4, 2026 · View on GitHub
A plain-language guide for non-technical users and Cursor beginners.
What is this?
cursor-kenji is a collection of "skills" for Cursor — the AI-powered code editor.
Think of skills like apps on a phone. You install them once and they're there when you need them. When you type something in Cursor chat — like "audit my security" or "make this page look better" — the matching skill activates and tells the AI exactly how to do that job properly.
Without skills, the AI does its best. With skills, it follows a documented step-by-step workflow.
Step 1: Install Cursor
If you don't have Cursor yet: download it at cursor.com. It's free and it's basically VS Code with AI chat built in.
Step 2: Install cursor-kenji
Open a terminal (on Mac: press Cmd+Space, type "Terminal", press Enter) and paste:
npx skills add kensaurus/cursor-kenji
If you get "command not found", run npm install -g skills first, then try again.
Alternative — no npm:
git clone https://github.com/kensaurus/cursor-kenji.git
cd cursor-kenji
./install.sh
Or with npx directly:
npx @kensaurus/cursor-kenji
Step 3: Restart Cursor
Close and reopen Cursor. That's all — the skills are now active.
Step 4: Use a skill
Open Cursor, open a project, and type in the chat. You don't have to remember skill names. Just describe what you want.
Bundled workflows (do the most work with one phrase)
These chain multiple skills into a single tracked loop:
| Type this in chat… | What happens |
|---|---|
build a feature: user notifications | Spec → TDD → implement → smoke test → PR — the whole loop |
fix this Sentry error and ship it | Triage → reproduce → fix → verify → PR → resolve issue |
is this ready to ship? | Adversarial test + security + bundle + perf → go/no-go verdict |
prepare the app for launch | SEO + PWA + bundle + quality gate + deploy smoke → launch checklist |
I'm new to this repo, orient me | Reads the codebase and produces a 5-minute briefing |
Individual skills
| Type this in chat… | What happens |
|---|---|
grill me about this plan | The AI interviews you — one question at a time — until you're both sure what to build |
pin down our terminology | Builds a project glossary (CONTEXT.md) so the AI stops using the wrong words |
resolve the merge conflicts | Traces each conflict back to why the code was written, resolves with intent, re-runs checks |
audit my app's security | Scans for OWASP vulnerabilities, checks auth, flags secrets in code |
make this page look better | Improves layout, spacing, hierarchy — like a designer would |
commit my changes | Writes a proper conventional commit message for you |
audit my database schema | Checks naming, indexes, RLS policies, data types |
deploy my npm package | Walks through Changesets → CI → publish, step by step |
write a PR | Creates the pull request with a proper title and description |
red team this app | Adversarial sweep — UX, data pipeline, security, performance |
make the app feel alive with motion | Adds coherent, accessible animations that match your design system |
improve this form | Accessible labels, real validation, error/success states, multi-step flows |
clean up our design system | Consolidates drifted colors/components into one source of truth |
set up guardrails so AI doesn't break things | Installs pre-commit + CI checks against secrets, bugs, and risky ops |
is my app production-ready? | Checks timeouts, retries, idempotency — the reliability the happy path skips |
The AI picks the right skill automatically based on what you typed.
A typical session, start to finish
The single biggest cause of bad AI output isn't bad code — it's the AI building the wrong thing. This loop prevents that:
1. Get oriented (new repo only)
I'm new to this repo, orient me
The AI reads the codebase and gives you a 5-minute briefing.
2. Get grilled before any code
/grill-me I want to add a referral program
Instead of guessing, the AI interviews you — one question at a time, each with a recommended answer so you can just say "yes" or push back:
"Should a referral reward fire on signup or on first payment? I'd recommend first payment — it prevents signup-farming. Agree?"
It looks up facts in your codebase itself and only asks you the decisions. Nothing is built until you confirm. The session ends with a decision log.
3. Build from the decisions
build the feature from those decisions
The workflow-build-feature loop takes over: spec → failing test → code →
smoke test → PR. Because you were grilled first, the spec matches what you
actually meant.
4. Hand off when you stop
Long session? Context getting full? Type:
/handoff finish the referral UI tomorrow
You get a compact handoff document (what's done, what's verified, exact next steps, which skills to invoke) saved outside your repo. Tomorrow, paste its path into a fresh chat and continue where you left off — no re-explaining.
The rhythm: orient → grill → build → prove → hand off. Skip the grilling and you're back to the AI guessing.
Updating
To get the latest skills:
npx skills add kensaurus/cursor-kenji
Running the same command again overwrites with the latest version.
Frequently asked questions
Do I need to configure anything? No, for most skills. Some skills use external services (Sentry, Supabase, Langfuse) — those need API keys in your environment. The skills tell you when that's needed.
Will this slow down Cursor? No. Skills are just text files. They're loaded by the AI only when relevant.
Can I delete skills I don't need?
Yes — delete any folder from ~/.cursor/skills/. The skill is gone.
Can I add my own skills? Yes. See CONTRIBUTING.md for the template.
Does this work with Claude, GPT, etc.? cursor-kenji is built for Cursor's agent system. Skills are text files, so the format is readable by any model Cursor supports.
Is it free? Yes, MIT licensed.
Planning skills — audit first, fix after you approve
17 plan-* skills run before you change code. They produce burndowns and phased roadmaps. You approve each phase, then run the matching execution skills.
Full guide: PLAN-LOOPS.md — grouped loops (not one mega-chain):
| Loop | When to run |
|---|---|
| Six-skill loop | UI/IA hardening on an inherited codebase |
| Pre-launch hardening | Security spine + dependency provenance |
| Observability & spend | Sentry/Langfuse gaps, LLM cost caps |
| Mobile gate | Capacitor native security, then App Store / Play paperwork |
| Growth gate | Answer-engine (AEO) visibility |
| Authenticity | plan-antislop — prose/visual/code slop pass |
Quick start (six-skill loop only):
plan-uiux-unification— UI/UX + design systemplan-stub-checker— dead buttons, fake data, unwired handlersplan-test-coverage— user stories → test matrix, fake-green gapsplan-perf-audit+plan-security-audit— performance + security (parallel)plan-docs-sync— docs match reality (last)
Say in Cursor:
Run the six-skill plan loop — plan only, no fixes until I approve each phase.
For security or launch prep, see the other loop prompts in PLAN-LOOPS.md.
Get help
- PLAN-LOOPS.md — how to chain the 17 planning skills
- AGENTS.template.md — project constitution for your app repo
- GitHub Issues — bug reports, feature requests
- GitHub Discussions — questions, ideas
- CATALOG.md — full list of skills and their trigger phrases
More from @kensaurus
Other free apps and tools from the same studio — all built with these skills. Full list with descriptions → README § Also by @kensaurus.
Mushi Mushi — know when users hit a bug your monitoring missed
npx mushi-mushi
Shake-to-report widget → AI-classified bug reports → optional AI draft PR fix. Free tier 1,000 reports/month, MIT SDK.
- kensaur.us/mushi-mushi — live demo
- github.com/kensaurus/mushi-mushi — source + issues