heyimcarlos/agent-skills

principle-minimize-reader-load

Apply when reviewing or shaping code that's hard to trace.

ソースを見る

使い方

  1. インストールコマンドをコピーし、自分の環境へ導入する前にソースを確認します。
  2. 必要なツール、認証情報、対応環境を原文で確認します。
  3. 入力と成果物を指定し、出力を資料と照合します。
npx skills add https://github.com/heyimcarlos/agent-skills --skill principle-minimize-reader-load

開始前の確認

  • 導入にはモデル契約、API枠、ファイルへのアクセス許可は含まれません。
  • スター数や導入数は活動の指標であり、独立した品質・安全性試験ではありません。
リポジトリの原文

見出し、例、コード、表、リンク、参照画像を含む原文を表示しています。

Minimize Reader Load

Maintainability is the work a reader must do to understand code. Track two axes:

  1. Layers to trace. How many indirections sit between the question and the answer.
  2. State to hold. How much hidden or mutable context the reader must keep in their head.

Why: Code is read far more than it is written. LOC, cyclomatic complexity, and "clean architecture" are proxies. Reader load is the thing that matters. The two axes are independent. A flat file with 50 globals can be as hard to reason about as a 6-layer adapter stack. Guard both. This is the human analog of Guard the Context Window: working memory is finite for readers too.

The pattern:

  • Collapse layers that do not earn their keep: wrappers with one caller, adapters with no second implementation, indirection introduced for a future that never came. Inline them.
  • Make adjacent layers change the abstraction. A layer that repeats the same methods and arguments adds reader load without compression. Collapse pass-through layers.
  • Demand interface compression. A broad interface that hides little complexity makes readers learn both the surface and the implementation. Prefer boundaries that hide meaningful decisions.
  • Shrink state scope: prefer pure functions (returns over mutations), locals over fields, fields over module state, and module state over globals. Derive instead of sync.
  • Name the invariant at the boundary, not in every consumer, so the reader learns it once.
  • Before adding a layer or a piece of state, ask: does this reduce reader load somewhere else by at least as much?

The test: Can a new reader answer "where does X come from?" and "what can change X?" in under 30 seconds? If not, cut layers or cut state.

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