architecture-decision

architecture-decision is a skill for Claude Code from visionTw/godot-ai-harness. It costs 36 tokens per session (4,506 once invoked), scanned A, a copy of architecture-decision, MIT.

A written record of an important technical choice, including its background, alternatives, and likely results. It is commonly called an Architecture Decision Record (ADR).

In plain words
What is it for?
Documenting major technical choices and updating existing ADRs with missing sections such as status, dependencies, compatibility, and requirements addressed.
Why use it?
It prevents important decisions from being forgotten or repeated, and makes the reasons behind them clear to future contributors.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: names the AskUserQuestion tool; mentions Claude Code.

Good fit Documenting major technical choices and updating existing ADRs with missing sections such as status, dependencies, compatibility, and requirements addressed.

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Install with agentmods
npx agentmods add skills/visiontw/godot-ai-harness/architecture-decision
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.

Any agent
npx skills add visionTw/godot-ai-harness --skill architecture-decision
Clone the repo
git clone --depth 1 https://github.com/visionTw/godot-ai-harness

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 architecture-decision

README.md
[![agentmods](https://agentmods.dev/badge/skills/visiontw/godot-ai-harness/architecture-decision/github.svg)](https://agentmods.dev/skills/visiontw/godot-ai-harness/architecture-decision)
Your own site
<a href="https://agentmods.dev/skills/visiontw/godot-ai-harness/architecture-decision"><img src="https://agentmods.dev/badge/skills/visiontw/godot-ai-harness/architecture-decision/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 architecture-decision

Your own site · 80×15
<a href="https://agentmods.dev/skills/visiontw/godot-ai-harness/architecture-decision"><img src="https://agentmods.dev/badge/skills/visiontw/godot-ai-harness/architecture-decision.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 36 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,506 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 95% copy Near-identical to another mod 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 $0.00036 $0.04506
Opus 5 $0.00018 $0.02253
Sonnet 5 $0.00007 $0.00901
Haiku 4.5 $0.00004 $0.00451

Measured 11d ago against content hash 25328cfe4e3b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

architecture-decision 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 11d 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

This is a copy

95% identical to architecture-decision — 37 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

core/skills/architecture-decision/SKILL.md · 456 lines

How it starts

The opening of the file, as written. The whole thing — 456 lines — stays where its author put it; the contents beside it link to each section on GitHub.

When this skill is invoked:

0. Parse Arguments — Detect Retrofit Mode

Resolve the review mode (once, store for all gate spawns this run):

  1. If --review [full|lean|solo] was passed → use that
  2. Else read production/review-mode.txt → use that value
  3. Else → default to lean

See .claude/docs/director-gates.md for the full check pattern.

If the argument starts with retrofit followed by a file path (e.g., /architecture-decision retrofit docs/architecture/adr-0001-event-system.md):

Enter retrofit mode:

  1. Read the existing ADR file completely.
  2. Identify which template sections are present by scanning headings:
    • ## StatusBLOCKING if missing: /story-readiness cannot check ADR acceptance
    • ## ADR Dependencies — HIGH if missing: dependency ordering breaks
    • ## Engine Compatibility — HIGH if missing: post-cutoff risk unknown
    • ## GDD Requirements Addressed — MEDIUM if missing: traceability lost
  3. Present to the user:
    ## Retrofit: [ADR title]
    File: [path]
    
    Sections already present (will not be touched):
    ✓ Status: [current value, or "MISSING — will add"]
    ✓ [section]
    
    Missing sections to add:
    ✗ Status — BLOCKING (stories cannot validate ADR acceptance without this)
    ✗ ADR Dependencies — HIGH
    ✗ Engine Compatibility — HIGH
    
  4. Ask: "Shall I add the [N] missing sections? I will not modify any existing content."
  5. If yes:
    • For Status: ask the user — "What is the current status of this decision?" Options: "Proposed", "Accepted", "Deprecated", "Superseded by ADR-XXXX"
    • For ADR Dependencies: ask — "Does this decision depend on any other ADR? Does it enable or block any other ADR or epic?" Accept "None" for each field.
    • For Engine Compatibility: read the engine reference docs (same as Step 0 below) and ask the user to confirm the domain. Then generate the table with verified data.
    • For GDD Requirements Addressed: ask — "Which GDD systems motivated this decision? What specific requirement in each GDD does this ADR address?"
    • Append each missing section to the ADR file using the Edit tool.
    • Never modify any existing section. Only append or fill absent sections.
  6. After adding all missing sections, update the ADR's ## Date field if it is absent.
  7. Suggest: "Run /architecture-review to re-validate coverage now that this ADR has its Status and Dependencies fields."

If NOT in retrofit mode, proceed to Step 0 below (normal ADR authoring).

No-argument guard: If no argument was provided (title is empty), ask before running Phase 0:

"What technical decision are you documenting? Please provide a short title (e.g., event-system-architecture, physics-engine-choice)."

Use the user's response as the title, then proceed to Step 0.


Read the full file on GitHub · 456 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. 11d ago First seen · 456 lines · 36 tokens per session scan A 25328cfe4e3b

Subscribe to this mod's changes

architecture-decision is a skill published in the GitHub repository visionTw/godot-ai-harness (2 stars, last pushed 24d ago), licensed MIT. It adds 36 tokens to every session and 4,506 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 95% identical to architecture-decision, differing in 37 lines, and is treated as a copy.

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