design

design is a command for Claude Code from DauQuangThanh/hanoi-rainbow. It costs 14 tokens per session (1,054 once invoked), scanned A, original, MIT.

A command that turns a feature specification into implementation-planning documents such as design notes, research, data models, and interface contracts.

In plain words
What is it for?
Use it to plan a feature in a repository, align the design with existing architecture, and produce the documents needed to guide coding.
Why use it?
It gives developers a structured plan and highlights technical details that are still unknown before implementation.

Command for Claude Code

Written for Claude Code: $ARGUMENTS substitution.

Good fit Use it to plan a feature in a repository, align the design with existing architecture, and produce the documents needed to guide coding.

Compare 6 commands from other repositories ↓
Install with agentmods
npx agentmods add commands/dauquangthanh/hanoi-rainbow/design
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.

Clone the repo
git clone --depth 1 https://github.com/DauQuangThanh/hanoi-rainbow

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for design

README.md
[![agentmods](https://agentmods.dev/badge/commands/dauquangthanh/hanoi-rainbow/design/github.svg)](https://agentmods.dev/commands/dauquangthanh/hanoi-rainbow/design)
Your own site
<a href="https://agentmods.dev/commands/dauquangthanh/hanoi-rainbow/design"><img src="https://agentmods.dev/badge/commands/dauquangthanh/hanoi-rainbow/design/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for design

Your own site · 80×15
<a href="https://agentmods.dev/commands/dauquangthanh/hanoi-rainbow/design"><img src="https://agentmods.dev/badge/commands/dauquangthanh/hanoi-rainbow/design.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 14 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,054 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00014 $0.01054
Opus 5 $0.00007 $0.00527
Sonnet 5 $0.00003 $0.00211
Haiku 4.5 $0.00001 $0.00105

Measured 10d ago against content hash 6da9c0d9cb22, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

design 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 10d 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

commands/design.md · 110 lines

How it starts

The opening of the file, as written. The whole thing — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.

User Input

$ARGUMENTS

You MUST consider the user input before proceeding (if not empty).

Outline

IMPORTANT: Automatically generate a 'docs:' prefixed git commit message (e.g., 'docs: add implementation plan for feature-name') and commit design.md, research.md, data-model.md, and contracts/ upon completion.

  1. Setup: Run {SCRIPT} from repo root and parse JSON for FEATURE_SPEC, FEATURE_DESIGN, SPECS_DIR, BRANCH. For single quotes in args like "I'm Groot", use escape syntax: e.g 'I'''m Groot' (or double-quote if possible: "I'm Groot").

  2. Load context: Read FEATURE_SPEC, memory/ground-rules.md, and docs/architecture.md (if it exists). Load FEATURE_DESIGN template (already copied). Adhere to the principles for maximizing system clarity, structural simplicity, and long-term maintainability.

  3. Execute plan workflow: Follow the structure in FEATURE_DESIGN template to:

    • Fill Technical Context (mark unknowns as "NEEDS CLARIFICATION")
    • Fill Ground-rules Check section from ground-rules
    • Align with architecture decisions from architecture.md (if available)
    • Evaluate gates (ERROR if violations unjustified)
    • Phase 0: Generate research.md (resolve all NEEDS CLARIFICATION)
    • Phase 1: Generate data-model.md, contracts/, quickstart.md
    • Phase 1: Update agent context by running the agent script
    • Re-evaluate Ground-rules Check post-design
  4. Stop and report: Command ends after Phase 2 planning. Report branch, FEATURE_DESIGN path, and generated artifacts.

Phases

Phase 0: Outline & Research

  1. Extract unknowns from Technical Context above:

    • For each NEEDS CLARIFICATION → research task
    • For each dependency → best practices task
    • For each integration → patterns task
    • Review architecture.md (if exists) for relevant architectural decisions and patterns
  2. Generate and dispatch research agents:

    For each unknown in Technical Context:
      Task: "Research {unknown} for {feature context}"
    For each technology choice:
      Task: "Find best practices for {tech} in {domain}"
    If architecture.md exists:
      Review: Architectural patterns, ADRs, and quality strategies relevant to this feature
    

Read the full file on GitHub · 110 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. 10d ago First seen · 110 lines · 14 tokens per session scan A 6da9c0d9cb22

Subscribe to this mod's changes

design is a command published in the GitHub repository DauQuangThanh/hanoi-rainbow (16 stars, last pushed 7mo ago), licensed MIT. It adds 14 tokens to every session and 1,054 once invoked, about $0.0001 per session on Opus 5. 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 2026-08-31.