本文へ移動
cccskills
無料GitHub で公開日本語紹介

system-atlas

システムの構成やデータの流れを、クリックして詳しく読める立体的なHTMLマップに整理します。同じデータから説明文も生成し、設計上の判断や未解決の質問を管理します。

原文原文の説明を見る

Build explorable isometric architecture atlases as HTML.

インストール方法を見る

こんなときに便利

  • システム構成とデータの流れの説明
  • 新しい設計をチームで検討したいとき
  • レビュー中の未解決の質問の管理
  • 設計変更後に図と文書を更新したいとき

日本語での紹介

できること

システムの構成要素やデータの流れを、斜め上から見た立体的なHTMLマップにまとめます。構成要素をクリックして説明や内部の手順を読み、移動するデータの内容も確認できます。章ごとに少しずつ構成を表示するため、全体像を段階的に説明できます。元になるdata.mjsから、設計判断や質問一覧を含むSYSTEM.mdも生成します。

こんなときに便利

新しいシステムやエージェント、処理の流れを視覚的に説明し、複数回のレビューで設計を詰めたい場面に向いています。未解決の質問はIDと状態で追跡し、判断が変わった後も図と文章を同じデータから更新できます。

使い方の例

  • 「このシステムの構成とデータの流れを、クリックして読めるマップにしてください」
  • 「今回決まった設計を反映し、質問の状態と説明文も更新してください」

注意点

対応環境はLinuxとmacOSです。生成には最近のNode.js、動作確認には静的サーバーが必要です。表示用HTMLは単一ファイルですが、Google Fontsのスタイルシートを参照します。生成済みファイルは直接編集せず、元データから再生成します。

この紹介文は、公開されている SKILL.md をもとに AI(Claude Haiku)が作成しました。正確な仕様は下の原文を確認してください。

含まれるファイル(7)

  • SKILL.md8.7 KB
  • assets/build.mjs5.5 KB
  • assets/data.example.mjs5.8 KB
  • assets/template.html37.4 KB
  • LICENSE.txt1.0 KB
  • references/design-language.md4.7 KB
  • references/process-and-lessons.md5.2 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

System Atlas Skill

An atlas is one data file (data.mjs) that renders two views: an interactive isometric map (a single self-contained atlas.html — hover to read, click to pin, go inside for steps, moving data packets you can inspect, chapters that reveal the system a few structures at a time), and a generated text twin (SYSTEM.md) with the decisions table, every structure, the flows, and the open questions by ID. The data file is the only thing anyone edits; both views rebuild from it. It sits beside a hand-written glossary (CONTEXT.md) and ADRs.

Does: interactive architecture maps with progressive disclosure, question tracking across feedback rounds, a generated text twin, and a repeatable update loop. Doesn't: static one-off diagrams (use the architecture-diagram or excalidraw skill), finished systems that only need a README, or a single diagram for a PR.

When to Use

Use whenever someone wants to discuss, design, review, or explain an architecture visually — "make an atlas", "map the system", "make the architecture explorable", "visualize the codebase/agent/pipeline so we can talk about it", "a diagram I can click around", "walk me through how it fits together" — or when an architecture discussion is producing a pile of open questions that need tracking across feedback rounds. Also use it to update an existing atlas after decisions change. Best when the system is new enough that vocabulary, decisions, and questions are still moving and there will be more than one feedback round.

Prerequisites

  • Node.js (any recent version; the build uses only node:fs, node:path, node:url — no npm install needed).
  • A static server for verification (npx serve or python3 -m http.server).

How to Run

mkdir -p <atlas home>/atlas
cp <skill>/assets/{template.html,build.mjs} <atlas home>/atlas/
cp <skill>/assets/data.example.mjs <atlas home>/atlas/data.mjs   # then fill it in
node <atlas home>/atlas/build.mjs   # writes ../SYSTEM.md and ../atlas.html

Every field of the data file is documented in assets/data.example.mjs.

Quick Reference

FileRoleEdit it?
atlas/data.mjsSingle source of truth: structures, flows, chapters, decisions, questions, proseYes
atlas/template.html + atlas/build.mjsRenderer + generatorPresentation only
atlas.htmlBuilt atlas; republish at the same URL after every rebuildNo (generated)
SYSTEM.mdBuilt text twinNo (generated)
CONTEXT.mdGlossary, one line per nounBy hand
adr/Hard-to-reverse decisionsBy hand
research/Deep-dive evidenceAppend-only

Procedure

Follow the order — each step was earned by a correction the first time round.

  1. Read the inputs before drawing. The vision doc, the repo's existing surfaces, and whatever prior art the user allows (ask — they may forbid a branch or a source). If you will build on a framework, read its docs first; hand long docs to a subagent via delegate_task with your specific design questions and have it return a primer with gotchas and a "what it does not give us" list. Drawing before this produces boxes that don't map to anything real.
  2. Discuss before drawing. Propose the structure in chat, mapped to the runtime's real primitives, and ask only the questions you cannot derive from the repo. Take defaults for the rest and say which.
  3. First atlas — the whole system. Copy assets/ into the atlas home (rename data.example.mjs to data.mjs), fill the data, build with node, publish. Where the atlas home is depends on the repo's docs policy — ask before committing anything. Docs-friendly repos: docs/{system}/atlas/ in-tree. Repos that commit only ADRs and CONTEXT.md: put the atlas, SYSTEM.md, and research/ in a git-ignored scratch dir and attach SYSTEM.md + research to the spec issue when published. (Committing the whole set once produced a 3,900-line docs PR and four review rounds reconciling three restatements of one design.) Load the design-md or architecture-diagram skill via skill_view for HTML-artifact guidance if useful; read references/design-language.md for the visual rules either way.
  4. Progressive disclosure. A whole system at once reads as noise. Ten-ish chapters; each adds at most three structures and runs one small flow that only touches revealed structures; the last chapter shows everything with a flow picker. Unrevealed structures stay in the index, dimmed, with their chapter number. Panels are summary-first: one sentence, then Read more and Steps folded.
  5. Shapes and labels. Letters on boxes are not enough. Give each role a shape and put a readable name label on the canvas under every structure — see design-language.
  6. Text twin. CONTEXT.md is a glossary and nothing else (the nouns, one line each); ADRs only for decisions that are hard to reverse, surprising without context, and the result of a real trade-off — these two are the in-tree pieces. SYSTEM.md is generated and research/ holds evidence; both live with the atlas (scratch dir or docs/, per step 3). Don't open issues unless asked.
  7. Feedback by question ID. Every question is Q-<code><n> with a state: open (a string), resolved {q, r} (answer + date), or routed {q, to} (handed to a named next step). Record the user's words. If they call something "not a question", drop it; if they say "I don't get this", explain with a concrete example before resolving. After each round: rebuild, republish, update memory.
  8. Deep dives feed back. Research with subagents (delegate_task) against one shared brief (the interface we own, the requirements that separate candidates, a usage model for cost, a fixed deliverable shape). Write a synthesis with a normalized cost/fit grid. Fold resolutions into the data as {q, r: '… (from the deep dive, date)'}. If the user rejects a proposal, sweep every file and rewrite — a banner on top of a stale section is not enough.
  9. Keep it current. One source, rebuild and republish after every change, never hand-edit generated files, and leave a README.md in the docs folder explaining the set (table in references/process-and-lessons.md).

Publishing

atlas.html is one self-contained file — no build step, no external assets beyond a Google Fonts stylesheet. Serve the folder with any static server (npx serve, python3 -m http.server) and hand over the URL, or let the repo's pages host serve the committed file. One URL, republished after every data change, never a second copy. If you keep a stable published URL, put it in META.artifactUrl so SYSTEM.md links to it.

Pitfalls

  • Keep <!doctype html> first and <meta charset="utf-8"> immediately after — otherwise quirks mode and mojibake arrows.
  • The renderer rebuilds its whole scene on every draw: a stray render() in a hover handler detaches the element under the cursor and the browser stops synthesising clicks — the map looks perfect in a screenshot while nothing responds.
  • Some in-app browsers render file:// as a static snapshot; verify via a static server, not from disk.
  • Never delete a question — resolve or mark it dropped, so IDs stay stable.
  • After every decision, grep the outputs for stale words (pending, the old model name, the rejected design) — the person reads everything.
  • Large HTML/JS via shell heredocs is brittle; use write_file and keep the data block JSON-serializable.

Verification

  • node <atlas home>/atlas/build.mjs exits 0 and writes both SYSTEM.md and atlas.html.
  • Syntax-check the built script (new Function(js)), then open the served page in a real browser at ~1280×800; check a first chapter, a middle chapter, the last chapter, an inside view, and the light theme.
  • Click a structure and confirm the panel says pinned and offers Go inside; click a packet dot and confirm the payload opens.
  • Every structure has one, what, how, a short label, a role kind, and its questions; ghosts are marked; chapters exist with per-chapter flows; the last chapter is the whole system.
  • SYSTEM.md carries the decisions table, the question index with IDs and states, and the "how this file is maintained" footer.
  • Project memory records the atlas URL, docs paths, locked decisions with dates, what the user rejected and why, and the next step.

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

同じリポジトリのスキル

概要と使いどころ

1password

無料日本語概要

1Passwordに保存したパスワードやAPIキーを、コマンド実行や設定テンプレートで使うためのスキル。CLIの導入、認証、秘密情報の取得・受け渡しを案内します。

  • 1Password CLIの導入と設定
  • 保存済みAPIキーでコマンド実行
  • 設定テンプレートへの秘密情報の埋め込み
NousResearch/hermes-agent25.3万2026年10月13日 更新

3-statement-model

無料日本語概要

損益計算書・貸借対照表・キャッシュフロー計算書を数式で連動させるExcelモデルを作ります。実績と予測の入力、前提を変えた比較、財務三表の整合性確認を段階的に進めます。

  • 財務テンプレートへの実績入力
  • 財務三表が連動する予測の作成
  • 基本・上振れ・下振れシナリオの比較
NousResearch/hermes-agent25.3万2026年10月13日 更新

Run PyTorch training across GPUs with minimal changes.

日本語の概要は準備中です。原文の説明を表示しています。

NousResearch/hermes-agent25.3万2026年10月13日 更新

Set up Actual Computer (actual.inc) inference in Hermes.

日本語の概要は準備中です。原文の説明を表示しています。

NousResearch/hermes-agent25.3万2026年10月13日 更新

adversarial-ux-test

無料日本語概要

技術が苦手で不満を抱きやすい利用者になりきってアプリを試し、操作の分かりにくさや離脱の原因を発見。実際の改善課題と個人的な不満を分け、修正案をまとめます。

  • 公開やデモ前に使いやすさを確認したいとき
  • 新規ユーザーの体験を点検したいとき
  • 登録・課金でのつまずきを探したいとき
NousResearch/hermes-agent25.3万2026年10月13日 更新

agent-merge-conflict-arbiter

無料日本語概要

2つのエージェントが別々に加えた変更のGit競合を、双方の差分と意図から中立的に解決。競合箇所ごとの判断理由を記録し、ビルドやテストで統合結果を確認します。

  • 2つのエージェントのブランチ競合を解消
  • 並行したworktreeの変更を統合
  • 競合する設計判断の理由を確認したいとき
NousResearch/hermes-agent25.3万2026年10月13日 更新

NousResearch のスキルをすべて見る

このスキルの問題を報告する