Waza

Engineering habits you already know, turned into skills AI agents can run.

Why

Waza (技, わざ) is a Japanese martial arts term for technique: a move practiced until it becomes instinct.

A good engineer does not just write code. They think through requirements, review their own work, debug systematically, design interfaces that feel intentional, and read primary sources. They write clearly, and learn new domains by producing output, not consuming content.

AI is more capable than most engineers at raw output. But without structure, that capability drifts into generic, imprecise work. Waza channels it into precision: eight skills that set clear goals and constraints, then let the model do what it does best.

Part of a trilogy: Kaku (書く) writes code, Waza (技) drills habits, Kami (紙) ships documents. Think of them as a family: Kaku is the dad, Waza the big sister, Kami the little sister.

Skills

Each engineering habit gets an installed skill. In Claude Code, type the slash command. In Codex, invoke the installed skill by name and follow the same playbook.

Skill	When	What it does
`/think`	Before building anything new	Challenges the problem, pressure-tests the design, and produces a decision-complete plan another agent can implement.
`/design`	Building frontend interfaces	Produces distinctive UI, including screenshot-driven aesthetic iteration, with a committed direction rather than generic defaults.
`/check`	After a task, before merging or release	Reviews the diff, extracts project-specific constraints, handles approved release/publish/push/reaction follow-through, and verifies with evidence.
`/hunt`	Any bug, regression, or unexpected behavior	Systematic debugging. Root cause confirmed before any fix is applied, especially when something used to work.
`/write`	Writing or editing prose	Rewrites prose to sound natural in Chinese and English. Cuts stiff, formulaic phrasing.
`/learn`	Diving into an unfamiliar domain	Six-phase research workflow: collect, digest, outline, fill in, refine, then self-review and publish.
`/read`	Any URL or PDF	Fetches content as clean Markdown with platform-specific routing. Special handling for GitHub, PDFs, WeChat, and Feishu.
`/health`	Auditing Agent Health	Checks Codex, Claude Code, project instructions, verifier output, and AI maintainability with a budget-aware summary pass before deep inspection.

Each skill is a folder with reference docs, helper scripts, and gotchas from real failures.

Install and Update

Most users should install Waza globally, so the same skills are available in every project.

Claude Code

npx skills add tw93/Waza -a claude-code -g -y

This installs /think, /design, /check, /hunt, /write, /learn, /read, and /health. Install just one with npx skills add tw93/Waza --skill think -a claude-code -g -y.

Codex

npx skills add tw93/Waza -a codex -g -y

Install just one with npx skills add tw93/Waza --skill think -a codex -g -y. Codex sessions can invoke installed skills by name or link to the installed SKILL.md path shown by npx skills path tw93/Waza.

Claude Code plugin marketplace

/plugin marketplace add tw93/Waza
/plugin install waza@waza

Use the bundle for now. Per-skill marketplace entries like waza-think@waza are temporarily affected by a Claude Code v2.1.136+ path-validation regression; until upstream fixes it, install one skill with the npx skills add ... --skill path above.

Claude Desktop

Download waza.zip, open Customize > Skills > “+” > Create skill, and upload the ZIP.

Update

npx skills update -g -y

Marketplace installs use claude plugin update <skill>. Claude Desktop users can replace the old skill with the latest waza.zip.

Compatibility

/health now supports Agent Health for both Claude Code and Codex. It understands AGENTS.md, CLAUDE.md, Copilot/Gemini instruction files, Codex config summaries, Claude hooks/MCP when present, verifier logs, and AI maintainability signals. It defaults to summary mode and only deepens when you ask for a deep/full audit or when the summary pass cannot classify the risk.

Project Context

Waza keeps the generic programmer habits inside the public skill. /check becomes project-aware by reading the target repository’s public context and the user’s task constraints.

Project commands come from README files, package manifests, Makefiles, CI workflows, and explicit user instructions.
Project hard stops include generated artifacts, protected files, version synchronization, release assets, and domain-specific safety risks.
Public docs and examples must not include credentials, certificate paths, private key filenames, tokens, or personal machine details.

See skills/check/references/project-context.md for the review context template.

Chaining Skills

Skills are designed to be chained together, but transitions are manual. Each skill stops after completing its task and waits for you to decide the next step.

Common workflows:

Design a feature: /think → approve → say “implement X” → /check → merge
Ship a fix: /hunt → fix → /check → release/publish/push/issue follow-through
Research and write: /read (fetch sources) → /learn (synthesize) → /write (polish)
Debug and verify: /hunt (find root cause) → fix → /check (review changes)

Each arrow represents a manual user action. Skills don’t automatically trigger each other.

Extras

Statusline

A minimal statusline for Claude Code: context window, 5-hour quota, and 7-day quota.

Color coding: green below 70%, yellow at 70-85%, red above 85% for context; blue, magenta, red for quota thresholds. No progress bars, no noise.

curl -sL https://raw.githubusercontent.com/tw93/Waza/main/scripts/setup-statusline.sh | bash

English Coaching

Optional rule for English practice. When your prompt contains an English mistake, the agent appends a short 😇 correction; Chinese-only prompts stay untouched.

# Claude Code
curl -sL https://raw.githubusercontent.com/tw93/Waza/main/scripts/setup-english-coaching.sh | bash -s -- claude-code

# Codex
curl -sL https://raw.githubusercontent.com/tw93/Waza/main/scripts/setup-english-coaching.sh | bash -s -- codex

Anti-Patterns

Optional always-on guardrails for cross-skill behaviors: stop acting before reading, no hallucinated paths, no scope creep, no unsolicited summaries. Skill-agnostic, applies in every session.

curl -sL https://raw.githubusercontent.com/tw93/Waza/main/scripts/setup-anti-patterns.sh | bash -s -- claude-code

Use codex instead of claude-code for Codex.

Uninstall

npx skills remove tw93/Waza -g
rm -f ~/.claude/statusline.sh
rm -f ~/.claude/rules/english.md
rm -f ~/.claude/rules/anti-patterns.md

For Claude Desktop, delete Waza from Customize > Skills. For Codex rule installs, remove the marked Waza block from ~/.codex/AGENTS.md.

Background

Tools like Superpowers and gstack are impressive, but they are heavy. Too many skills, too much configuration, too steep a learning curve for engineers who just want to get things done.

There’s also a subtler problem. Every rule the author writes becomes a ceiling. The model can only do what the instructions say and can’t go further. Waza goes the other direction. Each skill sets a clear goal and the constraints that matter, then steps back. As models improve, that restraint pays compound interest.

Eight skills for the habits that actually matter. Each does one thing, has a clear trigger, and stays out of the way. Not complete by design, just the right amount done well.

Built from patterns across real projects, refined through actual use. Every gotcha traces to a real failure: a wrong code path that took four rounds to find, a release posted before artifacts were uploaded, a server restarted eight times without reading the error. 30 days, 300+ sessions, 7 projects, 500 hours.

The /health skill grew from the six-layer Claude Code framework described in this post, and now extends it into Agent Health for Codex, Claude Code, verifier surfaces, and AI maintainability.

Support

If Waza helped you, share it with friends or give it a star.
Got ideas or bugs? Open an issue or PR, feel free to contribute your best AI model.
I have two cats, TangYuan and Coke. If you think Waza delights your life, you can feed them canned food 🥩.

License

MIT License. Feel free to use Waza and contribute.