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Engineering standard skills

Skill Ewanjohndennis/engineering-standard-skills

Claude Skills that hold AI-generated and AI-reviewed code to a rigorous, production-grade engineering bar — automatically.

Install
npx -y skills add Ewanjohndennis/engineering-standard-skills

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One thing to look at

  • 1 stars1 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Apply rigorous engineering standards when writing, refactoring, debugging, or reviewing Python, Java, or C code. Loads calibration and language-specific guidance automatically.

SKILL.md

3.0 KB, as published. Nobody here has run it

Engineering Standards

Inspired by Google's Engineering Practices documentation (CC-BY 3.0) and general production engineering norms. Not affiliated with or endorsed by Google. See README for attribution details.

This skill bundles several layers of engineering guidance. Don't apply everything blindly — read in only the reference files relevant to the current task, then apply them silently. Never narrate which files you're reading or that you're "loading a skill."

How to route

Step 1 — Is this worth calibrating?

If the task is non-trivial (a real feature, a refactor, a full review, a design question) — not a ten-line fix or a quick question — read references/calibration.md first and ask its one calibration question before producing anything. Skip this for small tasks or when the user has already given context (e.g. "this is a quick prototype," "this is going to prod").

Step 2 — Generation or review?

  • If the user wants code written, built, refactored, or debugged: read references/code-generation.md and apply it.
  • If the user wants existing code, a diff, or a PR reviewed or critiqued: read references/code-review.md and apply it.
  • If the task involves both (e.g. "write this, then review it"), read both.

Step 3 — Which language?

Detect the language from the code, the file extension, or the user's request. Read the matching reference file and apply it on top of the generation/review standards:

  • Python → references/python-standards.md
  • Java → references/java-standards.md
  • C → references/c-standards.md

If the language isn't one of these three, just apply the generic generation/review standards — they're language-agnostic by design and already defer to whatever conventions the codebase uses.

If a single task spans multiple languages (e.g. a Python backend with embedded SQL, or a C extension called from Python), read the reference files for each language actually present.

Priority order across all layers

When guidance from different reference files conflicts, resolve it in this order:

  1. Correctness
  2. Security
  3. Existing codebase conventions
  4. Maintainability
  5. Readability
  6. Performance
  7. Style preferences

A language-specific idiom never overrides a higher-priority concern from the generic standards. Existing codebase conventions outrank every default in every reference file here.

Output behavior

Apply all loaded guidance silently — no preamble like "Based on the engineering-standards skill, I will..." Just produce the code, the review, or the calibration question, as appropriate. If the user pushes back on feedback, handle it the way references/code-review.md describes.

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.