Code Review Skills

Provides code quality principles including SOLID, DRY, testing strategies, and best practices for implementation review. Use when reviewing code or applying quality standards.

Provides code quality principles including SOLID, DRY, testing strategies, and best practices for implementation review. Use when reviewing code or applying quality standards.

Reviews code implementations for correctness, security, maintainability with confidence-scored findings (converted from agent)

Provides code quality principles including SOLID, DRY, testing strategies, and best practices for implementation review. Use when reviewing code or applying quality standards.

Use when reviewing code changes — MR/PR review, local commits, or uncommitted changes. Reviews document compliance, content quality (architecture soundness, test completeness, observability coverage), and end-to-end consistency (User Story ↔ design ↔ code ↔ tests ↔ observability). Triggers on "review MR", "review this commit", "review my changes", "code review", "help me review".

Cross-platform code submission workflow - Lint check, non-destructive review, manual verification document, smart staging, clean commit, MR creation. Auto-detects project type (Android/iOS/backend) and adapts to the corresponding lint/build tools. Triggers when the user says "submit code", "prepare to submit", "submit", "start submission flow", or "code submit".

Git workflow best practices including commit messages, branching strategies, pull requests, and collaboration patterns. Use when working with Git version control.

Audit the architecture and code quality domain - module boundaries, abstraction layers, code organization, naming, documentation. Run as part of /audit Phase E.

Conduct a full technical due diligence audit of a vibe-coded codebase. Use when the user types `/audit`, asks for a "full audit," asks for a "due diligence review," asks "is this codebase ready to ship-", or asks for a comprehensive code review of an entire repository (not a single PR). Coordinates the 13 domain skills, the hard-stop hunt, the Tambon LLM-signature hunt, and the blind-spot walk. Produces a single dual-layer report (founder view + technical evidence).

Use when reviewing GitHub pull requests with gh CLI - creates pending reviews with code suggestions, batches comments, and chooses appropriate event types (COMMENT/APPROVE/REQUEST_CHANGES)

Review a Confluent agent skill in this repo against the Agent Skills spec (agentskills.io), Confluent conventions in CLAUDE.md, the PR template gates, and the evals-as-contract rule. Use this skill whenever the user asks to review, audit, validate, or lint a skill; opens or inspects a PR that adds or modifies anything under `skills/`; asks about spec conformance, lazy-loading, frontmatter shape, trigger overlap, or eval coverage; or wants a pre-merge sanity check on skill changes. Do NOT trigger for general code review of application code; security review; auditing schemas, producer/consumer configs, PII tagging, or Terraform generation for Schema Registry (handled by `kafka-schema-registry`); runtime/log analysis of skill behavior (use `tools/skill_review_dashboard.py`); or any changes that don't touch the `skills/` tree.

>- Independent re-derivation gate for proposed changes during autonomous execution. Evaluates a change (code diff, config edit, engine evolution, schema change) against the work's authority matrix and a 4-check narrowness, and regression risk. Returns structured JSON with pass/fail per check, an overall verdict (APPROVE / REQUEST_CHANGES / REJECT), and blockers. Profile-driven thresholds (strict for unattended runs, lenient for desk supervision). Use when an autonomous agent proposes an engine change, when reviewing a Claude Code-authored modification before merge, or when an unattended profile requires independent re-derivation. "is this change safe," "is this safe to merge," "should I let this land," "run the critic." Do NOT use for handoff-readiness checks (use rootnode-handoff-trigger-check), general code review, or design-time correctness. Authority matrix required.

>- Specialized software engineering prompt methodology for Claude. Use when building prompts for system design, code review, incident response, security analysis, API design, architecture decisions, RFCs, ADRs, review," "system design prompt," "SRE prompt," "security review prompt," "incident response prompt," "API design prompt," "architecture decision prompt," "RFC prompt," "runbook prompt." Provides 11 tested approaches across identity, reasoning, and output for engineering analysis. Do NOT use for general coding help, writing code, or debugging — this builds prompts that shape engineering analysis, not code itself. Do NOT use for evaluating existing prompts (use rootnode-prompt-validation if available).

Implement, refactor, or review iOS 26+ SwiftUI Liquid Glass features using native `glassEffect`, `GlassEffectContainer`, glass button styles, availability gates, and fallbacks.

Build or refactor iOS SwiftUI views/components: navigation, TabView, sheets, async state, responsive stacks/grids, state ownership, environment injection, previews, and performance-aware declarative UI.

Implement, refactor, or review modern macOS SwiftUI Liquid Glass UI: NavigationSplitView, toolbars, search, sheets, controls, system materials, `glassEffect`, `GlassEffectContainer`, and `glassEffectID`.

Refactor macOS SwiftUI views/scenes into small stable subviews, explicit scene roots, command/toolbar ownership, scene-aware state, and narrow AppKit bridges.

Build or refactor native macOS SwiftUI scenes and components: windows, commands, toolbars, settings, split views, inspectors, menu bar extras, keyboard workflows, and desktop layouts.

Refactor SwiftUI view files toward small dedicated subviews, MV-first data flow, stable view trees, explicit dependencies, extracted actions, and correct Observation usage.

Use when designing or reviewing safe Grok Build hooks for linting, tests, formatting, notifications, command guards, lifecycle automation, or project hook trust decisions.

Use when reviewing a diff, pull request, branch, or AI-generated code for correctness, security, regression, test, performance, and maintainability risks before merge.

Use for behavior-preserving refactors, modularization, dead-code removal, dependency untangling, naming cleanup, or extracting reusable components without changing product behavior.

Infer a player's underlying values and motivational priorities from behavior, then translate those into design implications. Use when designing personalization, segmentation, dynamic guidance, live-ops targeting, adaptive missions, re-engagement strategies, or feature prioritization; when behavior suggests that what players actually care about differs from what the design assumes; or when a team needs a behavior-first player profile rather than a demographic or archetype-only model.

Extract a structured list of rules from all markdown files at the top level of a skill directory. Use this skill whenever you need to parse rules out of a skill for conflict checking, merging, or diffing.

Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, reviewing, or refactoring code to avoid overcomplication, make surgical changes, surface assumptions, and define verifiable success criteria.

Use when the user says 'clean up my wordpress', 'what is bloating my wordpress', 'find orphaned shortcodes', or 'scan for unused plugins'. Audits orphaned shortcodes from deleted plugins, unused plugins, database bloat, unused media, and leftover data from inactive builders.

Devil's Advocate stress-testing for code, architecture, PRs, and decisions. Surfaces hidden flaws through structured adversarial analysis with metacognitive depth. Use for high-stakes review, stress-testing choices, or when the user wants problems found deliberately. NOT for routine code review. Triggers on "스트레스 테스트", "stress test", "devil's advocate", "반론", "이거 괜찮아", "문제 없을까", "깊은 리뷰", "critical review", "adversarial".

> Standalone skill for multi-perspective PLC code security and quality analysis. "code review", "check this code", "is this safe", "find issues" when combined with PLC, SCL, ST, LAD, FBD, Structured Text, or block context. Also triggers when the user pastes PLC code and asks for feedback, or uploads exported SimaticML XML files. This skill is independent of tia-openness-roadmap — it does not perform engineering automation. It analyzes code that has already been exported, pasted, or is accessible via the TIA Portal MCP server.

> Automatically triggered when setting up Python code quality tooling, configuring linters, adding type checking, improving code standards, running code quality checks, setting up ruff setup, mypy configuration, code formatting, linting rules, cyclomatic complexity, dead code detection, file length limits, pre-commit hooks, Makefile targets for quality, uv-based workflows, pyproject.toml configuration, or "check my code quality". "run quality checks", "set up pre-commit", "code smells", "clean up this code", "add code quality", "quality gate", "CI quality pipeline".

> Use when going beyond basic linting to enforce advanced Python code quality gates. import boundaries, dependency hygiene, test quality beyond coverage, mutation testing, docstring coverage, type coverage, AI-generated code detection, AI slop detection, complexipy, jscpd, import-linter, deptry, diff-cover, mutmut, interrogate, sloppylint, refurb, pylint design checks, wily, radon maintainability, pytestarch, griffe, "bulletproof Python", "tighten quality gates", "advanced quality checks", "beyond ruff and mypy", "catch AI-generated code issues", "code duplication", "architectural boundaries", "dependency drift", "test effectiveness". Complements the code-quality skill (ruff, mypy, xenon, vulture, pre-commit) with 20+ additional tools.

Executes OpenAI Codex CLI for code analysis, refactoring, and automated editing. Activates when users mention codex commands, code review requests, or automated code transformations requiring advanced reasoning models.

Use when the user wants to rename, extract, split, move, or restructure code safely. Examples: \"Rename this function\", \"Extract this into a module\", \"Refactor this class\", \"Move this to a separate file\

> SEO & GEO content linter — validates Markdown/MDX files for AI search visibility using 92 deterministic rules (35 GEO, 32 SEO, 14 content quality, 8 technical, fix them, re-lint until clean. Use when optimizing content for AI citations, auditing SEO compliance, checking GEO readiness, or running pre-publish content "content optimization", "AI search", "citation readiness".

Commit les changements, se synchronise avec main distant, push la branche courante et crée une Pull Request. Refuse de tourner directement sur main. Utilise sur /livre, ou quand l'utilisateur veut livrer/expédier son travail : \"commit et push\", \"ouvre une PR\", \"livre ça\", \"ship\", \"envoie la PR\", \"finalise et pousse\". Aval naturel de /branche.

> comments, and merge. Triggers on "open a PR", "make a PR", "merge this PR", "merge the MR", "read PR comments", "leave a comment on the PR", "respond to a comment", "ship this", or when a feature branch is ready for review.

Multi-agent code review with parallel specialized reviewers, architecture validation, and challenge validation. Use `rq` to request a review of diffs (defaults to main branch), `rs` to respond to review findings. Triggers on "review this", "review my code", "code review", "check for bugs", "audit this", when examining PRs, pull requests, branches, or diffs. Always asks user before applying fixes.

> Post-implementation completion workflow for Spec-backed Plans. Use after spec-implement completes to validate, review, create stacked commits, and open a PR via code-pull-request. Triggers only with an active Spec-backed Plan after spec-implement completes, including when the user says "finish", "done", or "complete" in that context.

> Application Security Engineer role bundle for security design, testing, and code review of applications. Orchestrates new application reviews, PR security reviews, API security assessments, and AI feature security reviews. Auto-invoked when the user needs help with application threat modeling, secure code review, API security testing, or evaluating the security of LLM-powered application features.

> Performs a structured security code review against OWASP ASVS 4.0.3 verification requirements and CWE Top 25. Auto-invoked on pull request reviews, when code touching authentication, authorization, cryptography, or input handling is shared. Produces findings mapped to ASVS controls and CWE identifiers with severity ratings and specific remediation guidance.

Анализ расширения конфигурации 1С (CFE) — состав, заимствованные объекты, перехватчики, проверка переноса. Используй когда нужно понять что содержит расширение или проверить перенесены ли вставки в конфигурацию

1C:Naparnik (1С:Напарник) MCP server tools - BSL code analysis, review, rewriting, ITS knowledge base, platform documentation search, configuration documentation. Use when checking BSL code quality, searching ITS standards, reading platform docs, comparing versions, or finding configuration-specific documentation.

Enforces automated quality checks before every deploy. Prevents production failures through a 5-stage Quality Gate System (Pre-Commit, PR-Check, Preview, E2E, Production). Activate on code changes, deployments, PR reviews, build failures.

Manufacturing-fokussierter Continuous Improvement Skill fuer fabrikIQ. Implementiert Lean Manufacturing Prinzipien (5 Whys, Ishikawa, PDCA) fuer systematische Problemloesung und Qualitaetsverbesserung. Aktivieren bei Bug-Analyse, Refactoring, Code Review, Production Incidents.

AI code review for PR or local changes. 280+ checks across security, architecture, performance, testing, and code quality. Posts findings as GitHub PR comments with confidence scores.

Receive and process code review feedback effectively. Applies suggestions, addresses comments, and iterates on implementation improvements.

Hand off code review to OpenAI Codex CLI. Use when asked to "review code with codex", "codex review", "get a second opinion on code", "review my changes", "review this PR", or when you want AI-powered code review from a different model perspective.

Expert logging guidance based on Boris Tane's loggingsucks.com philosophy. Use when implementing logging, adding observability, debugging production issues, or reviewing code that includes log statements. Covers wide events architecture, structured logging, smart sampling, and high-cardinality field design.

Expert product management guidance for day-to-day PM work. Use when creating roadmaps, prioritizing features, managing stakeholders, planning sprints, grooming backlogs, scoping features, planning releases, defining OKRs, managing technical debt, or coordinating go-to-market. Covers RICE, ICE, MoSCoW frameworks, cross-functional collaboration, and product metrics.