Maintainable code
SkillMediaShape and review production code for human legibility, maintainability, safe change, and performance-aware design. Use when writing, implementing, modifying, refactoring, or reviewing code; planning implementation structure; performing code-quality or architecture audits; or investigating code that is difficult to understand or change.
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
Account requirements not reviewed. Check the skill instructions before use; ahel provides instructions and does not run this skill.
Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
Then ask your AI: use the Maintainable code skill
What this skill tells your AI
The instructions your AI receives, as published by nickyfactz/plumbline in skills/maintainable-code/SKILL.md and read by ahel’s review.
Shape code for the cost and risk of its next change.
The code must serve two audiences:
- the runtime, which needs correct and appropriate behavior
- the human maintainer, who needs to understand and change that behavior safely
Do not optimize source code for model token economy, syntactic cleverness, or compliance with a style doctrine. Prefer code whose intent, control flow, ownership, and important tradeoffs are recoverable by a human reader.
Governing principles
Use these as defaults, not laws:
- Clarity: intent should be recoverable without reconstructing the author's entire mental model.
- Scanability: visual shape should reveal rough control flow and conceptual stages before every expression is decoded.
- Locality: a conceptual change should require edits near the concept that owns it.
- Depth: prefer stable interfaces that hide meaningful complexity over swarms of shallow wrappers.
- Cohesion: code that changes for the same reason should tend to live together.
- Information hiding: important design decisions and domain knowledge should have clear ownership.
- Explicitness: dependencies, state transitions, side effects, invariants, and failure behavior should be visible at the appropriate boundary.
- Evidence: preserve duplication, comments, larger functions, direct code, or specialized implementations when they are clearer or safer than the proposed abstraction.
- Behavior preservation: a refactor changes structure, not externally observable behavior, unless behavior change is explicitly in scope.
- Testability: difficult-to-test code is evidence about coupling, not permission to distort a good runtime design.
- Performance awareness: abstraction is not free; profile or benchmark when runtime cost is material.
- Repository fit: repository-local conventions and host-language idioms outrank generic style preferences.
Choose one work branch
Load only the branch that matches the current task:
- Writing or modifying production code: read
references/implementation.md. - Behavior-preserving structural refactor: read
references/refactoring-workflow.md. - Code review or larger quality/design audit: read
references/review-audit.md.
Do not load the other workflow branches unless the task genuinely crosses modes.
Shared anti-dogma rules
- Prefer one coherent operation over an arbitrary function-length limit.
- Prefer semantic whitespace and meaningful locals over compressing source for fewer lines or tokens.
- Prefer one behavioral scenario over a literal one-assertion-per-test rule.
- Prefer useful rationale and contract comments over a blanket "comments are failures" stance.
- Prefer stable abstractions discovered from pressure over eliminating every instance of duplication immediately.
- Prefer deep modules over splitting code until navigation itself becomes the complexity.
- Prefer language-native error, ownership, and composition models over importing one paradigm into every language.
- Prefer measured hot-path efficiency over stylistic purity when the two conflict.
- Prefer repository consistency over introducing a new personal formatting system.
Universal completion gate
No branch is complete until:
- required behavior is validated at a level proportionate to the change
- a reproducible formatter and useful baseline linter/static-analysis path exists for materially maintained languages, and their checks pass at the repository's agreed baseline
- materially changed code is human-scannable
- important state, side effects, and contracts are understandable
- no material design debt was introduced merely to finish the task
- intentionally retained complexity has a concrete reason
Signals
- GitHub stars
- 22
- Last commit
- Sep 2026
Advanced
- Item type
- skill
- Key
maintainable-code-nickyfactz- Source
- github.com/nickyfactz/plumbline
github.com/nickyfactz/plumbline