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Code Review & Quality
Code review, refactoring, debugging, maintainability, and engineering quality
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Showing 11,257–11,280 of 15,957 skills
- Writing PlansUse when design is complete and you need detailed implementation tasks - creates tracked MCP issues with exact file paths, complete code examples, and verification steps. Optional reference plan file for architecture overview.Votes: 0GitHub stars: 4
- Using WranglerUse when starting any conversation - establishes mandatory workflows for finding and using skills, including using Skill tool before announcing usage, following brainstorming before coding, and creating TodoWrite todos for checklistsVotes: 0GitHub stars: 4
- Reviewing CodeConducts systematic code review with quality checks, architectural verification, and actionable feedback. Use when reviewing pull requests, code changes, or ensuring code quality standards.Votes: 0GitHub stars: 4
- Requesting Code ReviewUse when completing tasks, implementing major features, or before merging to verify work meets requirements - dispatches reviewing-code subagent to review implementation against plan or requirements before proceedingVotes: 0GitHub stars: 4
- Practicing TddUse when implementing any feature or bugfix, before writing implementation code - write the test first, watch it fail, write minimal code to pass; ensures tests actually verify behavior by requiring failure firstVotes: 0GitHub stars: 4
- Dispatching Parallel AgentsUse when facing 3+ logically independent failures (different features, different root causes) that can be investigated concurrently - dispatches multiple agents to investigate in parallel; requires either parallel-safe test infrastructure OR sequential fix implementationVotes: 0GitHub stars: 4
- Analyzing Research DocumentsExtracts key insights, patterns, and actionable findings from research documents and papers. Use when reviewing documentation, research, or technical materials requiring systematic analysis.Votes: 0GitHub stars: 4
- Reviewing Implementation ProgressTracks implementation progress against specs or plans with completion percentages. Use when monitoring multi-step implementations, reporting status, or identifying blockers.Votes: 0GitHub stars: 4
- Dependency Opportunity ScannerScan codebase to identify opportunities to replace custom implementations with well-maintained open source libraries. Creates worktree, implements changes, and submits PR for review. Multi-phase workflow with parallel analysis agents.Votes: 0GitHub stars: 4
- Debugging SystematicallyUse when encountering any bug, test failure, or unexpected behavior, before proposing fixes - four-phase framework (root cause investigation, pattern analysis, hypothesis testing, implementation) that ensures understanding before attempting solutionsVotes: 0GitHub stars: 4
- BrainstormingUse when creating or developing anything, before writing code or implementation plans - refines rough ideas into fully-formed designs through structured Socratic questioning, alternative exploration, and incremental validationVotes: 0GitHub stars: 4
- Analyzing ImplementationsAnalyzes implementation quality, technical debt, and architectural patterns in existing codebases. Use when conducting code audits, planning refactors, or evaluating technical decisions.Votes: 0GitHub stars: 4
- Code ReviewReview a diff, branch, path, or PR for correctness bugs, gaps against the change's stated goals, security vulnerabilities, and reuse/simplification/efficiency cleanups, using a verify-before-reporting pass so findings are checked against the actual code rather than pattern-matched. Portable across agent platforms (Claude Code, pi, Copilot, OpenCode) — needs only `git diff` and a rubric, no MCP or witan dependency. Use this skill when asked to "review this diff", "review my branch", "code revi...Votes: 0GitHub stars: 5
- Wizardlm Empowering Large Language Models To Follow Complex Instructions Arxiv 2304 12244v2Use this skill when you want to progressively increase instruction complexity through evolution prompts (deepening, widening, adding constraints). Avoid it when you need simple instructions or cannot afford iterative evolution.Votes: 0GitHub stars: 9
- Shikra Unleashing Multimodal Llms Referential Dialogue Magic Arxiv 2306 15195v2Use this skill when you want to create referential dialogue data where the VLM and user exchange spatial references (bounding boxes) naturally within conversation. Avoid it when you do not need spatial references in conversation.Votes: 0GitHub stars: 9
- Segment Everything Everywhere All At Once Arxiv 2304 06718v2Use this skill when you want a unified segmentation model trained on diverse segmentation data types (semantic, instance, panoptic, interactive) for VLM grounding. Avoid it when you only need one segmentation type.Votes: 0GitHub stars: 9
- Otter A Multi Modal Model With In Context Instruction Tuning Arxiv 2305 03726v2Use this skill when you want to create instruction data that includes in-context examples for multi-modal in-context learning. Avoid it when you do not need in-context learning capability in your VLM.Votes: 0GitHub stars: 9
- Mantis Interleaved Multi Image Instruction Tuning Arxiv 2405 01483v2Use this skill when you want to create instruction data for multi-image understanding tasks like comparison, reasoning across images, and temporal understanding. Avoid it when you only need single-image instruction data.Votes: 0GitHub stars: 9
- Llava Video Unified Video Understanding With Video Representation Learning Arxiv 2501 00599v1Use this skill when you want to scale video instruction data for training a unified video understanding VLM with diverse temporal reasoning tasks. Avoid it when you only need image understanding or have limited video data.Votes: 0GitHub stars: 9
- Lisa Reasoning Segmentation Via Large Language Model Arxiv 2308 00692v2Use this skill when you want to create training data for a VLM that outputs segmentation masks through language-based reasoning. Avoid it when you do not need segmentation output or can use standard segmentation datasets.Votes: 0GitHub stars: 9
- Donut Document Understanding Transformer Without Ocr Arxiv 2111 15664v2Use this skill when you want to pre-train a document understanding model on synthetic document images without OCR using a vision encoder-decoder. Avoid it when you have good OCR and only need text extraction without visual understanding.Votes: 0GitHub stars: 9
- Dolphins Multimodal Language Model For Driving Arxiv 2312 00438v2Use this skill when you want to create instruction data for an autonomous driving VLM using BDD-X driving dataset with explanations. Avoid it when you do not work with autonomous driving.Votes: 0GitHub stars: 9
- Contrastive Language Image Pre Training With Knowledge Graphs Arxiv 2210 08901v2Use this skill when you want to augment CLIP training data with knowledge graph information for improved conceptual understanding. Avoid it when you do not have access to knowledge graphs or standard CLIP training is sufficient.Votes: 0GitHub stars: 9
- Clevr A Diagnostic Dataset For Compositional Language And Elementary Visual Reasoning Arxiv 1612 06890v1Use this skill when you want to generate diagnostic visual reasoning data with programmatic scene and question generation for compositional reasoning evaluation. Avoid it when you need real-world images rather than synthetic scenes.Votes: 0GitHub stars: 9