uw-cmd-implement-feature

A guided workflow for building a complete game feature. It covers confirming the feature, asking design questions, implementing it with TDD—writing tests to guide development—and documenting the result.

In plain words
What is it for?
Use it to plan and implement Unity gameplay features such as movement mechanics, including their behavior, feel, tests, and documentation.
Why use it?
It helps prevent features from being treated as finished when they only compile but have not been tested, polished, or explained.

Command for Claude Code

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add commands/devdavv/unity-ai-workflow/uw-cmd-implement-feature
Clone the repo
git clone --depth 1 https://github.com/devdavv/unity-ai-workflow

Made for: Claude Code.

Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,549 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00000 $0.01549
Opus 5 $0.00000 $0.00775
Sonnet 5 $0.00000 $0.00310
Haiku 4.5 $0.00000 $0.00155

Measured 2d ago against content hash f63911f45f23, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

uw-cmd-implement-feature scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.claude/commands/uw-cmd-implement-feature.md · 137 lines

How it starts

The opening of the file, as written. The whole thing — 137 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/uw-cmd-implement-feature — Feature Development Loop

Build a feature complete: interrogation -> TDD implementation -> game feel -> documentation — all in one pass.

Skills

Load uw-game-feel-integrator from .claude/skills/uw-game-feel-integrator/SKILL.md.

Why One Loop?

Polish is not Phase 5. Every feature ships complete: code + feel + documentation. A feature is only "done" when it plays well, not just when it compiles. "Too much juice is easier to fix than too little."


Steps

1. Feature Brief

State the feature in one sentence. Get user confirmation before interrogating.

Example: "We're implementing the double-jump mechanic. The player can jump a second time while airborne."

2. Deep Interrogation

Ask the user these questions. Don't skip them — answers shape implementation and feel.

Structure your answers with TCREI for best results:

  • T — Task: What exactly should this feature do?
  • C — Context: Constraints, current systems it touches, scope
  • R — References: Games, repos, tutorials that do this well
  • E — Evaluate: After first pass, what's right/wrong/missing?
  • I — Iterate: Refine from there

Reference games:

"Name 1-3 games that do this mechanic well. What do you like about how they handle it?"

Code references:

"Do you know of any GitHub repos, Unity packages, or tutorials that implement this? I can use them as a starting point."

Behavior & edge cases:

"What should happen at the limits?"

Scope:

"Is this prototype/spike quality, or production-ready?"

Visual sketch (optional):

If the feature involves new UI or complex flows, offer visual communication tools. Reference docs/ASSET_RESOURCES.md -> Visual Communication Tools.

3. Game Feel Questions (per-feature GFD pass)

Ask upfront. Don't defer. These answers update the GFD before a line of code is written.

"Let's lock in the feel for this feature now. Answer roughly — we'll tune values during implementation."

Read the full file on GitHub · 137 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 137 lines · 0 tokens per session scan A f63911f45f23

Subscribe to this mod's changes

uw-cmd-implement-feature is a command published in the GitHub repository devdavv/unity-ai-workflow (41 stars, last pushed 5mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,549 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.