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- Kingkongshot
- Pensieve
- Taste Check
taste-check_skill
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GitHub Stars
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Bundled Files
2 months ago
Catalog Refreshed
4 months ago
First Indexed
Readme & install
Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.
Installation
Preview and clipboard use veilstrat where the catalogue uses aiagentskills.
npx veilstrat add skill kingkongshot/pensieve --skill taste-check- SKILL.md4.7 KB
Overview
This skill reviews code using Linus Torvalds' "good taste" philosophy to find defensive patterns, special cases, deep nesting, and other code smells. It provides a compact taste score, highlights fatal issues, lists code smells, and gives concrete refactor suggestions with before/after examples. Use it to harden code quality, simplify logic, and prioritize refactors.
How this skill works
I inspect the provided files, diffs, or pasted snippets and run a checklist based on ten taste principles: trust upstream data, eliminate special cases, avoid post-return mutation, ban ad-hoc string concatenation, enforce single responsibility, limit nesting, extract pure functions, validate early, fail fast, and delete dead code. The output is a structured review with a taste score, top problems, detailed code-smell checklist, prioritized fixes, and concrete code examples for remediation.
When to use it
- Code review for quality and maintainability
- Refactoring candidate assessment
- Checking PR diffs for new code smells
- Validating architecture and data flow assumptions
- Teaching teams a stricter taste-driven standard
Best practices
- Trust upstream data; validate once at the boundary and avoid downstream defensive defaults
- Prefer early return and small pure functions to keep nesting shallow
- Return fully-formed results; avoid modifying returned objects after the fact
- Assemble strings/CSS in one place; avoid incremental concatenation across code paths
- Keep functions focused (ideally <50 lines); split responsibilities into testable pure functions
- Fail fast on invalid data instead of hiding issues with fallbacks or try-catch
Example use cases
- Review a single file or module for multiple code smells and get exact refactor steps
- Analyze a git diff to decide whether recent changes introduced defensive code or special-case hacks
- Inspect pasted code snippets to produce quick before/after rewrites and a taste score
- Prioritize technical debt: produce a short ranked list of refactors for immediate action
- Audit string-building or CSS generation logic to centralize and eliminate concatenation
FAQ
Specify a file path, paste a code snippet, or provide a git diff. I will analyze the chosen scope and report findings.
Will it auto-apply fixes?
No. It provides concrete before/after examples and prioritized refactor steps for you to apply manually or script into your tooling.