Results for “code-review”

Break a work-items.md file (produced by /plan-work-items) into independently-grabbable GitHub issues, one per slice, in each slice's target repo. Use when you want to turn a work-items file into GitHub issues, publish work items as issue tickets, or create implementation tickets that can be worked on and tracked on GitHub. Does not produce the work-items file itself — use plan-work-items to break a plan into work items first. Does not review code or post pull request comments — use post-code-review-to-pr for that.

Conduct a design interview, generate 5 distinct UI variations in a temporary route, collect real click-to-comment feedback on the live rendered variants via human-review, and produce an implementation plan. Use when the user wants to explore UI design options, redesign an existing component/page, or create new UI with multiple genuinely different approaches to compare — before writing production code or committing to a direction. For a lighter, single-component variant picker with no interview, use `prototype` instead. For reviewing a UI that's already real (not exploring new directions), use `visual-review`. Source: adapted from github.com/0xdesign/design-plugin's design-lab skill (interview + 5-variant structure), with feedback collection replaced by this repo's own `visual-review` skill (human-review) instead of a bespoke overlay component.

Runs a six-phase security audit covering attack-surface mapping, STRIDE/PASTA threat modeling, technical checklists, red/blue team exercises, and a final verdict, plus incident-response and monitoring guidance.

Runs a structured security audit across six phases: attack-surface mapping, STRIDE/PASTA threat modeling, technical checklists, red/blue team analysis, and a final verdict, with optional Python automation scripts.

Enforces an algorithm-first discipline: state Big-O, data structure, and algorithm family before writing loops, queries, or recursion, catching O(n^2), N+1, and brute-force defaults.

Use when writing or editing a code comment or a documentation block, and when reviewing the comments and documentation in a diff before presenting it. Decides what stays in the source, what moves to reference documentation, and what gets deleted.

Practical technical debt scanning and prioritization for Nick's projects. Use during maintenance reviews, when a codebase feels slow to work in, or when checking what debt is actually hurting development velocity. Focus on high-impact debt, not style nitpicks.

Perform a static audit of an AL workspace for Business Central against the project's copilot-instructions.md contract. Reports findings by class (Compliance, Code quality, Test coverage, Permissions) and severity (Blocker, Major, Minor, Nit) with file:line citations. Never modifies code. Never invents rules. Use when asked to audit a workspace, run a compliance check, review before PR, or diagnose contract drift.

Designs the contract for an API change inside one codebase — a component's props, a function surface, URL or query parameters, an event payload, or a module boundary — through a discovery pass, an options document with one recommendation, a question round, and an adversarial validation round, with every element of the contract justified from one stated goal. Use when you want to design, shape, decide, or nail down an interface, contract, signature, or API change for a capability you can already describe, sized for roughly one pull request. Produces a design document and changes no code. Does not specify what a feature should do — use plan-a-feature. Does not plan delivery or sequencing — use plan-implementation. Does not assess the architecture of existing code — use architectural-analysis. Does not write the code — use tdd. Does not restructure existing code — use refactor. Runs its rounds without pausing for review; to review each round as it lands, use pairing.

Prevents AI-introduced regressions with sandbox-mode API testing, automated bug-check workflows, and patterns that catch blind spots where the same model writes and reviews code.

Runs a structured 6-phase security audit covering attack-surface mapping, STRIDE/PASTA threat modeling, technical checklists, red/blue team exercises, and a final verdict, plus incident-response and monitoring playbooks.

Survey a codebase's animation and motion code as a senior motion advisor, then produce a prioritized audit and self-contained implementation plans for other agents (or cheaper models) to execute. Read-only on source code — it plans improvements, it does not apply them. Use when the user asks to "improve the animations", "audit the motion", "make this app feel better", or wants a roadmap of animation fixes rather than a review of a single diff. Source: github.com/emilkowalski/skills.

Autonomous iterative experimentation loop for any programming task. Guides the user through defining goals, measurable metrics, and scope constraints, then runs an autonomous loop of code changes, testing, measuring, and keeping/discarding results. Inspired by Karpathy's autoresearch. USE FOR: autonomous improvement, iterative optimization, experiment loop, auto research, performance tuning, automated experimentation, hill climbing, try things automatically, optimize code, run experiments, autonomous coding loop. DO NOT USE FOR: one-shot tasks, simple bug fixes, code review, or tasks without a measurable metric.

Authoritative guidance for building Claude Code skills, agents, and plugins, plus init and update steps that install and refresh the plugin-building skills in the current repository. Use when you need the rules or best practices for a skill, agent, hook, or plugin — designing, reviewing, hardening, or checking one against the guidance. Run with `init` to vendor the guidance, skill-builder, and agent-builder skills into the current repository (so they run with no dependency on this plugin) plus a path-scoped rule index, or `update` to refresh an already-vendored copy. Does not run an interview to build a new skill or agent from scratch — use skill-builder or agent-builder. Does not write feature code, review application code, or build non-plugin features.

Guides a coding agent through the full GitHub pull request lifecycle: branch, commit, open PR, monitor CI, fix failures, merge, and clean up, using either the gh CLI or git plus curl.

Use for creating, splitting, reviewing, or debugging GitHub Copilot custom instructions in Visual Studio Code, including .github/copilot-instructions.md, .github/instructions/*.instructions.md, and AGENTS.md. Do not use for slash commands, Agent Skills, custom agents, hooks, or ordinary project documentation.

Detects and eliminates AI writing tropes that make text sound artificial or formulaic. Use when generating text content, writing documentation, creating code comments, or reviewing writing style. Supports four-tier JSON preferences (global/project x shared/local office.json) read via load-preferences.sh.

Multi-agent autonomous startup system for Claude Code. Triggers on "Loki Mode". Orchestrates 100+ specialized agents across engineering, QA, DevOps, security, data/ML, business operations, marketing, HR, and customer success. Takes PRD to fully deployed, revenue-generating product with zero human intervention. Features Task tool for subagent dispatch, parallel code review with 3 specialized reviewers, severity-based issue triage, distributed task queue with dead letter handling, automatic deployment to cloud providers, A/B testing, customer feedback loops, incident response, circuit breakers, and self-healing. Handles rate limits via distributed state checkpoints and auto-resume with exponential backoff. Requires --dangerously-skip-permissions flag.

Multi-agent autonomous startup system for Claude Code. Triggers on "Loki Mode". Orchestrates 100+ specialized agents across engineering, QA, DevOps, security, data/ML, business operations, marketing, HR, and customer success. Takes PRD to fully deployed, revenue-generating product with zero human intervention. Features Task tool for subagent dispatch, parallel code review with 3 specialized reviewers, severity-based issue triage, distributed task queue with dead letter handling, automatic deployment to cloud providers, A/B testing, customer feedback loops, incident response, circuit breakers, and self-healing. Handles rate limits via distributed state checkpoints and auto-resume with exponential backoff. Requires --dangerously-skip-permissions flag.

Multi-agent autonomous startup system for Claude Code. Triggers on "Loki Mode". Orchestrates 100+ specialized agents across engineering, QA, DevOps, security, data/ML, business operations, marketing, HR, and customer success. Takes PRD to fully deployed, revenue-generating product with zero human intervention. Features Task tool for subagent dispatch, parallel code review with 3 specialized reviewers, severity-based issue triage, distributed task queue with dead letter handling, automatic deployment to cloud providers, A/B testing, customer feedback loops, incident response, circuit breakers, and self-healing. Handles rate limits via distributed state checkpoints and auto-resume with exponential backoff. Requires --dangerously-skip-permissions flag.

Route LangSmith work into one workflow packet before touching SDK code. Use when the user needs LangSmith tracing, offline evals, annotation/review queues, prompt-registry decisions, audit/gap review, or cross-service trace propagation for an LLM app or agent workflow. Choose one packet: trace-debug, eval, review, prompt-registry, propagation, or audit. Triggers on: LangSmith, LangChain tracing, `@traceable` / `traceable`, `wrap_openai` / `wrapOpenAI`, datasets, experiments, annotation queues, feedback criteria, Prompt Hub, run trees, trace IDs, or production confidence for an AI feature. Not for generic SLO/alert design, non-LangSmith deployment orchestration, or runtime guardrails outside LangSmith.

Audits codebases for GDPR and CCPA/CPRA compliance by inventorying PII fields, mapping data collection points, reviewing consent mechanisms, verifying data subject rights, tracing third-party data sharing, and checking retention policies.

Explains MariaDB explicit table locking (LOCK TABLES/UNLOCK TABLES) and named user-level locks (GET_LOCK family), covering alias traps, implicit commits, and multi-lock semantics for writing or reviewing locking code.

General GitHub workflow — branching, commits, pull requests, code review, secrets hygiene, submodules, and git worktrees. Use when the user wants to save changes, push to GitHub, open a PR, work with a submodule, set up a worktree, or perform any git/GitHub operation.

Use for creating, reviewing, debugging, or testing GitHub Copilot agent hooks in Visual Studio Code, including .github/hooks JSON, lifecycle events, Python handlers, permissions, and structured stdin/stdout. Do not use for advisory instructions, one-off commands, CI workflows, or shell profile hooks.

Redux-Saga (generator-based) middleware for async side effects — yields declarative effects (call/put/select/takeLatest/delay) instead of imperative async code, watcher-per-slice composition, optimistic updates with rollback. Use when authoring per-slice operations.js, the rootSagas composer, or reviewing saga workers.

Workflow 1.5: Bridge between idea discovery and auto review. Reads EXPERIMENT_PLAN.md, implements experiment code, deploys to GPU, collects initial results. Use when user says "实现实验", "implement experiments", "bridge", "从计划到跑实验", "deploy the plan", or has an experiment plan ready to execute.

Applies Han's shared Human-Readable Output Standard to a target you already have — a file on disk, text pasted into the prompt, or a draft already produced in the conversation — by dispatching the readability-editor to rewrite its prose so the main point comes first, headings are descriptive, each paragraph carries one idea, and sentences stay short and active, while preserving every fact. Use when you want to make a document or draft readable, edit or polish prose for readability, clean up writing, tighten wording, or re-apply the readability standard to something already written. Rewrites prose only, leaving code, diagrams, and citation identifiers unchanged. Does not write new feature or system documentation — use project-documentation. Does not restructure code or review it — use refactor to restructure code and code-review to audit it. Does not judge the underlying work or raise findings; it only rewrites the writing.

Ship workflow: detect + merge base branch, run tests, review diff, bump VERSION, update CHANGELOG, commit, push, create PR. Use when asked to "ship", "deploy", "push to main", "create a PR", "merge and push", or "get it deployed". Proactively invoke this skill (do NOT push/PR directly) when the user says code is ready, asks about deploying, wants to push code up, or asks to create a PR. (gstack)

Diagnoses structural problems in an existing test suite—brittleness, mock overuse, and other decay risks—drawing on twelve classic engineering books including xUnit Test Patterns and Working Effectively with Legacy Code.

Explains MariaDB Connector/Node.js specifics: Promise vs Callback API, placeholders, BigInt handling, batch inserts, query streams, pooling, transactions, and prepared statements, for writing or reviewing Node.js code that uses the `mariadb` package.

Explains MariaDB Connector/Python's DB API 2.0 behavior, including qmark placeholders, autocommit, prepared statements, buffered cursors, connection pooling, and error handling, for writing and reviewing Python code that uses the mariadb module.

Use when a paper is complete or near-complete and a holistic pre-submission audit is needed. Cross-cuts text, code, tables, figures, results, citations, and reproducibility in a single pass and produces a persistent audit report. Works standalone on papers written outside the plugin.

React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.

Discover, find, compare, audit, repair, adapt, craft, run, debrief, and prepare repeatable AI-agent loops for publication. Use when a user asks to analyze code or coding threads for recurring work, find a published loop, interview them to turn a goal into a bounded loop, review a loop...

React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.