By doodledood
Automate Git PR workflows: rebase branches, rewrite history into review-ready commits, address comments, resolve blockers, and babysit to merge. Clean AI-generated slop like useless comments and abstractions from code or diffs. Explore codebases with prioritized file maps. Research web topics via structured multi-agent synthesis. Update CLAUDE.md docs.
Context-gathering agent for finding files to read (not analysis). Maps codebase structure; main agent reads files and reasons. Returns overview + prioritized file list with line ranges. Thoroughness: quick for "where is X?" lookups | medium for specific bugs/features | thorough for multi-area features | very-thorough for architecture/security audits. Auto-selects if not specified: single entity → quick; single subsystem → medium; multi-area → thorough; "comprehensive"/"all"/"architecture" → very-thorough. <example> prompt: "quick - where is the main entry point?" returns: Key files only, no research file </example> <example> prompt: "find files for payment timeout bug" returns: Payment architecture overview + prioritized files </example> <example> prompt: "very thorough exploration of authentication" returns: Dense auth flow overview covering all aspects </example>
Use this agent when you need to find and remove AI-generated code slop, including useless comments, verbose patterns, unnecessary abstractions, and filler phrases. This agent is ideal for cleaning up code after AI-assisted coding sessions, during code review to catch AI patterns, or when refactoring to improve code clarity. Examples: <example> Context: User just finished implementing a feature with AI assistance and wants to clean it up. user: "I just finished implementing the user authentication module, can you clean up any AI slop?" assistant: "I'll use the slop-cleaner agent to analyze and clean up AI-generated patterns in your authentication module." <Task tool call to slop-cleaner agent> </example> <example> Context: User wants to review recent changes for AI patterns before committing. user: "Check my recent changes for AI slop" assistant: "I'll launch the slop-cleaner agent to analyze the git diff between your branch and main to identify and remove any AI-generated patterns." <Task tool call to slop-cleaner agent> </example> <example> Context: User notices verbose comments in a specific file. user: "The utils.ts file has too many obvious comments, clean it up" assistant: "I'll use the slop-cleaner agent to remove useless comments and verbose patterns from utils.ts." <Task tool call to slop-cleaner agent with 'utils.ts' argument> </example>
Use this agent when you need to research external topics via web search - technology comparisons, best practices, industry trends, library evaluations, API documentation, or any question requiring current information from the web. The agent uses structured hypothesis tracking to systematically gather and synthesize web-based evidence. <example> Context: User needs to evaluate technology options. user: "What are the best options for real-time sync between mobile and backend in 2025?" assistant: "I'll use the web-researcher agent to systematically research and compare current real-time sync approaches." </example> <example> Context: User needs current best practices. user: "What's the recommended way to handle authentication in Next.js 15?" assistant: "Let me launch the web-researcher agent to gather current best practices and official recommendations." </example> <example> Context: User needs market/industry research. user: "What are the leading alternatives to Stripe for payment processing?" assistant: "I'll use the web-researcher agent to research and compare payment processing options." </example>
Build a personalized PR review skill by mining GitHub review history. Extracts review patterns, communication style, priorities, and blind spots — generates a calibrated review-as-me skill that posts inline comments on PRs. Use for onboarding, cloning review style, or creating a reviewer persona.
Find and remove AI-generated slop (useless comments, verbose patterns, unnecessary abstractions).
Find all files relevant to a query with orthogonal exploration for comprehensive coverage. Returns topic-specific overview + file list with line ranges. Uses parallel agents for thorough+ levels to ensure nothing is missed.
Autonomously bring a PR to mergeable state. Resolves merge conflicts, fixes CI failures, addresses review comments, syncs PR description, and requests re-review. Designed for unattended cron execution via loop skill. Use when: "prep pr for merge", "make pr mergeable", "fix pr blockers", "autonomous pr maintenance".
Update main/master from origin, rebase current branch on it, resolve conflicts, and push.
Uses power tools
Uses Bash, Write, or Edit tools
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Verify ownership to unlock analytics, metadata editing, and a verified badge. GitHub access is read-only (username + org membership).
Sign in to claimBased on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
First-principles workflows for Claude Code. Built by developers who understand LLM limitations.
Experienced developers frustrated by hype-driven AI coding tools. If you're tired of chasing the latest "game-changing" prompt that produces code you spend hours debugging, these plugins offer a grounded alternative.
Our approach:
Add the marketplace:
/plugin marketplace add https://github.com/doodledood/claude-code-plugins
Browse and install:
/plugin list
/plugin install vibe-extras@claude-code-plugins-marketplace
Multi-provider LLM consultations via Python/LiteLLM. Get perspectives from different models (OpenAI, Anthropic, Google, local models) without leaving Claude Code.
/review - PR review with severity-tagged findings/analyze-code - Architectural and security analysis/investigate-bug - Root cause analysis via external model/ask - Single-model consultation/ask-council - Multi-model ensemble (3 models in parallel)Requires Python 3.9+ and uv. Supports any provider via LiteLLM.
Standalone utilities for codebase exploration, web research, git operations, and code maintenance.
Research & exploration:
/explore-codebase - Structural overview with prioritized file list (quick/medium/thorough/very-thorough)/research-web - Deep web research with parallel investigators and multi-wave synthesisGit utilities:
/rebase-on-main - Safe rebasing with conflict resolution guidance/rewrite-history - Restructure commits for clean, reviewer-friendly PRsCode maintenance:
/clean-slop - Remove AI-generated noise (redundant comments, verbose patterns)/update-claude-md - Create or maintain CLAUDE.md project instructionsCode review:
/build-review-persona - Mine GitHub review history to generate a calibrated review-as-me skill/address-pr-comments - Triage and fix PR review comments with false positive detection/pr-merge-prep - Autonomously bring a PR to mergeable state (conflicts, CI, comments, description sync, re-review)/babysit-pr - Loop pr-merge-prep until PR is merge-ready, then ask before mergingSee also: manifest-dev for manifest-driven development—define acceptance criteria, let the verify-fix loop handle the rest.
Foundational documents for solo developers and small teams. Define once, reference consistently.
Customer & brand:
define-customer-profile - Create CUSTOMER.md (foundation for all other decisions)define-brand-guidelines - Communication style and voicedefine-design-guidelines - UI/UX patterns for your audiencedefine-seo-strategy - Traditional SEO + AI citation optimizationOther:
/audit-ux - Check UI changes against your design guidelinesCraft, analyze, and optimize prompts from first principles.
/prompt-engineering - Craft or update prompts from first principles (WHAT/WHY not HOW)/review-prompt - Analyze against 10-Layer Architecture framework (read-only)/optimize-prompt-token-efficiency - Iteratively optimize for token efficiency/compress-prompt - Compress into single dense paragraph for context injectionFrontend design patterns for distinctive, non-generic UI experiences.
scrollytelling - Scroll-driven storytelling with pinned sections, progressive reveals, and parallax effectsPersonal decision-making advisor. Understands your situation first, then researches and recommends.
/decide - Situation discovery → targeted research → decision framework → ranked recommendationAll writing skills in one place. Research-backed anti-AI prose, author voice capture, and voice-matched generation.
human-writing - Base knowledge with vocabulary kill-list, four-layer editing, craft fundamentals (auto-invoked for prose)/write - Full workflow: gather context → write → review → auto-fix → loop until cleancraft-author-voice - Capture your writing style into AUTHOR_VOICE.md/write-as-me - Generate content in your voice (requires AUTHOR_VOICE.md)Value-first promotion on social platforms. Finds high-signal posts and crafts replies that genuinely help conversations while naturally referencing your product.
/promote-on-x - Browse X feed, find relevant posts, craft structurally varied replies with writing review, post after approvalRequires Claude in Chrome extension and the writing plugin.
npx claudepluginhub doodledood/claude-code-plugins --plugin vibe-extrasManifest-driven workflows for structured task execution with verification gates.
Post-processing utilities for manifest workflows. ADR synthesis from session transcripts.
Tools for crafting, reviewing, analyzing, refining, and optimizing LLM prompts for clarity, precision, goal effectiveness, and token efficiency
Frontend design patterns and implementation skills for distinctive, non-generic UI experiences
Personal decision-making and life workflow support
Tools for crafting, reviewing, analyzing, refining, and optimizing LLM prompts for clarity, precision, goal effectiveness, and token efficiency
GitHub and Git workflow tools: commit-creator, pr-creator, pr-reviewer, and pr-comment-resolver agents, slash commands for commits, PRs, and review comment resolution, plus skills for PR/commit workflows.
Ultra-compressed communication mode. Cuts ~75% of tokens while keeping full technical accuracy by speaking like a caveman.
Comprehensive UI/UX design plugin for mobile (iOS, Android, React Native) and web applications with design systems, accessibility, and modern patterns
Upstash Context7 MCP server for up-to-date documentation lookup. Pull version-specific documentation and code examples directly from source repositories into your LLM context.
Multi-model consensus engine integrating OpenAI Codex CLI, Gemini CLI, and Claude CLI for collaborative code review and problem-solving.