heyimcarlos/agent-skills

principle-minimize-reader-load

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

Voir la source

Mode d’emploi

  1. Copiez la commande et examinez le paquet avant de l’installer dans votre environnement agent.
  2. Consultez le document original pour les outils, identifiants et environnements requis.
  3. Décrivez les entrées et le livrable souhaité ; comparez la sortie aux sources.
npx skills add https://github.com/heyimcarlos/agent-skills --skill principle-minimize-reader-load

Avant de commencer

  • L’installation n’inclut ni abonnement au modèle, ni quota API, ni accès aux fichiers.
  • Étoiles et installations reflètent l’activité, pas un test indépendant de qualité ou de sécurité.
Document Skill original

Rendu depuis le dépôt source en conservant titres, exemples, code, tableaux, liens et images.

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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