「code quality」の検索結果

Use when adversarially reviewing a document that makes formal or technical claims — math derivations, physics papers, statistical analyses, benchmark reports, whitepapers. Inventories every equation and quantitative claim, verifies each AS NAMED in the text (never a paraphrase or a neighboring statement), and classifies VERIFIED / REFUTED / UNVERIFIABLE / VACUOUS. Triggers on "check this paper", "verify these claims", "is this derivation right", "review this proof", "audit this benchmark", "does the math hold up". For source-code review see code-review-and-quality; for skill/agent library audits see skill-library-review; for content quality scoring see content-ops.

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Improve or review ordinary dygo code changes for simplicity, focused scope, canonical ownership, clear boundaries, and verifiable behavior. Use for normal implementation and refactoring quality; use dygo-thermonuclear-review only for an explicitly severe audit.

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Perform comprehensive technical reviews of Ruby on Rails applications. Runs automated analysis tools (RubyCritic, Brakeman, bundler-audit, Gitleaks, Debride, linters, SimpleCov, Rails stats, Rails ERD), analyzes code for architecture, security, authorization (Pundit/CanCanCan), dead code, and design issues, and produces a structured markdown report with prioritized findings and a 0-10 score. Use when the user requests a tech review, code audit, project assessment, or quality analysis of a Rails application.

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Enforces KISS/DRY/YAGNI during authoring and ad-hoc quality reviews. Pragmatic standards: concise, direct, no unnecessary comments. NOT for post-hoc diff/PR review (see mk:review); NOT for behavior-preserving simplification passes (see mk:simplify).

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Convert between sequence file formats (FASTA, FASTQ, GenBank, EMBL, Stockholm) and re-encode FASTQ quality offsets using Biopython Bio.SeqIO. Use when changing a file format for a downstream tool, fixing FASTQ quality encoding (Phred+33 vs Phred+64 vs Solexa), or when a conversion risks silently dropping annotations or quality scores.

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ATAC-seq library quality control -- TSS enrichment, FRiP, fragment-size periodicity, library complexity (NRF/PBC1/PBC2), mitochondrial fraction, and ENCODE 4 thresholds. Use when assessing whether an ATAC-seq library passes ENCODE acceptance criteria, diagnosing transposition artefacts, comparing Omni-ATAC vs standard prep quality, or selecting which replicates to drop before peak calling.

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Review changed code for YAGNI, removable over-complexity, reuse, code quality, and efficiency, then apply worthwhile simplifications. Use when the user asks to simplify, clean up, tighten, de-hack recent changes, identify logic that can be dropped, or review whether added safeguards and edge-case handling are actually needed.

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Scan the codebase for common security issues: hardcoded secrets, SQL injection vectors, XSS, unvalidated inputs, and insecure defaults. Use before deploying, as part of code quality review, or when asked to check for security issues.

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Find overly complex code: files over 300 lines, functions over 50 lines, deeply nested conditions (4+ levels), and magic numbers. Use for code quality reviews, pre-release checks, or when asked to assess code maintainability.

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Use when a diff needs a readability review — naming, single-responsibility, DRY, dead code, mismatch with codebase conventions — dispatched by /review-changes, /do-and-judge, /judge.

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[Code Quality] Use when you need to run quality gate checklist.

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[Code Quality] Use when the user asks to enhance documentation, add code comments, create API docs, improve technical documentation, document code, or update README files.

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[Code Quality] Use when you need to simplify and refine code for clarity, consistency, and maintainability while preserving all functionality.

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Use when reviewing a pull request in the deepseek-harness repo — orients the reviewer to this codebase's standards (AGENTS.md conventions, defensive patterns, ADRs, quality gates) and the review-specific checks that code alone can't show

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Use when work produces a deliverable, factual claim, dataset, code change, decision, publication, deployment, automation, or irreversible action whose failure would matter; when the user asks for a quality gate, acceptance criteria, QA, completeness, validation, audit, evidence, preflight, release readiness, or a definition of done; or before claiming completion on medium- or high-risk work. Automatically decide whether a formal gate is warranted, derive task-specific pass/fail criteria, gather evidence, and block unsupported completion. Make sure to use this skill even when the user does not say "quality gate" if consequential work needs acceptance criteria or completion evidence. Skip formal gating for trivial, reversible, low-impact requests.

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Core technical, safety, and maintainability rules for codebase edits. Trigger when: - Writing code, refactoring, modifying files, or creating unit tests. - Proposing commits, reviewing git history, or auditing code quality. - Modifying files in any programming language (e.g. *.go, *.rs, *.py, *.ts, *.js, *.c, *.cpp). - Prompt contains keywords: refactor, build, compile, lint, test, git, commit, rule priority, type safety, error handling, defensive programming.

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Comprehensive code review for commits and pull requests. Covers security, TDD, code quality, and documentation standards.

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Use before completion, PR, deploy, handoff, or when verifying code changes. Runs advisory or blocking checks and reports evidence.

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Quality audit of a whole repo: bugs, security holes, what breaks under real load, risky code without tests, slow paths, and what to delete, merge or split. Ranked, each finding explained in plain English. One-shot report, changes nothing. Use for "audit this codebase", "review the whole repo", "find bloat", "what can I delete", /ponytail-audit.

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Audit code quality focusing on deep modules, naming, model hygiene, and architectural clarity. Use after a burst of development, when codebase structure needs assessment, or to make code more agent-navigable.

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Checks common code quality and maintainability risks.

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Reviews mobile code for production bugs across Flutter, native Android, native iOS, React Native and Kotlin Multiplatform, including KMP source-set and host API contracts. Covers lifecycle, concurrency, UI state and native boundaries with file:line evidence. Use for a code review, PR, project audit, quality check or /reis-mobile:review.

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Applies principles from Robert C. Martin's 'Clean Code'. Use this skill when writing, reviewing, or refactoring code to ensure high quality, readability, and maintainability. Covers naming, functio...

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Run all available tests and linters, check for anti-patterns, and generate a comprehensive code quality report

日本語の概要は準備中です。原文の説明を表示しています。