principle-minimize-reader-load
Apply when reviewing or shaping code that's hard to trace. Count layers between question and answer, and hidden state in the reader's head; collapse one-caller wrappers and shrink mutable scope.
- License 许可
- MIT
- 最近更新
- 2026-10-15
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01 前言 Front Matter
- name
- principle-minimize-reader-load
- description
- Apply when reviewing or shaping code that's hard to trace. Count layers between question and answer, and hidden state in the reader's head; collapse one-caller wrappers and shrink mutable scope.
02 资源文件 2
- 参考文档agents/openai.yaml43 B
- 许可证LICENSE1.0 KB
03 SKILL.md 正文
Minimize Reader Load
Maintainability is the work a reader must do to understand code. Track two axes: layers to trace (indirections between the question and the answer) and state to hold (hidden or mutable context the reader must keep in their head). 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.
- Collapse layers that cost more than they save: wrappers with one caller, adapters with no second implementation, speculative indirection that was never needed. 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 it reduce reader load elsewhere 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.
04 同仓库更多 Skills
why
Use for 'why does X work this way', 'why we picked Y', design rationale, regressions, postmortems, or data-backed thresholds. Discovers available MCPs and queries each evidence category (source control, issue tracker, long-form docs, real-time chat, infrastructure observability, error tracking, product analytics warehouse) in parallel, then returns a cited read on decisions and tradeoffs. Use how for runtime behavior.
verify-this
Verify a claim with fresh local evidence: restate it falsifiably, capture baseline and treatment, compare artifacts, and return VERIFIED, NOT VERIFIED, or INCONCLUSIVE.
unslop
Cut AI tells from any writing.
typescript-best-practices
TypeScript best practices. Use when reading or editing any .ts or .tsx file.
technical-writing
Layered technical-writing standard: Diátaxis structure, Google developer style sentences, STE instruction rules, Global English syntax. Use for /technical-writing or when writing or reviewing docs, RFCs, readmes, PR descriptions, or commit messages.
tdd
Use only when the user explicitly asks for TDD, a failing test, or a regression test, OR when the bug has an obvious cheap local test target. Skip when the test path is unclear, expensive, integration-heavy, or not requested.