
Custom skill for testing-anti-patterns
Automated code review using official Claude Code plugin with parallel agents. Integrates ralph-security for OWASP validation and ralph-frontend for accessibility checks. Uses LSP for efficient code navigation.
Learn patterns from a specific GitHub repository. Clones, analyzes code structure, extracts patterns, populates procedural memory AND syncs to Obsidian vault for Graph View visualization. Use for: targeted learning from known quality repos, quick knowledge acquisition, specific pattern extraction. Triggers: /repo-learn, /curator-repo-learn, 'learn from repo'.
Performance optimization skill. Core Web Vitals via Lighthouse, bundle size analysis, metrics tracking over time. Use when: (1) optimizing frontend performance, (2) analyzing bundle size, (3) tracking metrics regression. Triggers: /perf, 'performance audit', 'core web vitals', 'bundle size'.
Plan-State Management for Ralph. Create, track, and manage implementation plans with LSA verification. Coordinates with 6 ralph-* teammates including ralph-frontend and ralph-security.
Product Requirements Document generation and management with INVEST-compliant user stories
When the user wants to create or update a README.md file for a project. Also use when the user says "write readme," "create readme," "document this project," "project documentation," or asks for help with README.md. This skill creates absurdly thorough documentation covering local setup, architecture, and deployment.
Comprehensive research skill using Zai MCP web search and native Claude Code tools
Pre-launch shipping checklist orchestrating /gates, /security, /browser-test, /perf. Ensures nothing ships without passing all quality checks. Use when: (1) before deploying, (2) before merging to main, (3) before release. Triggers: /ship, 'ship it', 'ready to deploy', 'pre-launch check'.
Security audit with Codex + MiniMax second opinion. Integrates ralph-security agent (6 quality pillars, OWASP A01-A10). Uses LSP for code navigation during analysis. Use when: (1) /security is invoked, (2) task relates to security functionality.
Autonomous batch task execution with PRD parsing, task decomposition, and continuous execution until all tasks complete. Uses /orchestrator internally. Stops only for major failures (no internet, token limit, system crash). Use when: (1) processing task lists autonomously, (2) PRD-driven development, (3) batch feature implementation. Triggers: /task-batch, 'batch tasks', 'process PRD', 'run task queue'.
Bug hunting with Codex CLI Use when: (1) /bugs is invoked, (2) task relates to bugs functionality.
Custom skill for glm-mcp
Full orchestration workflow with swarm mode: evaluate -> clarify -> classify -> persist -> plan mode -> spawn teammates -> execute -> validate -> retrospective. Use when: (1) implementing features, (2) complex refactoring, (3) multi-file changes, (4) tasks requiring coordination. Triggers: /orchestrator, /orch, 'orchestrate', 'full workflow', 'implement feature'.
Senior Blockchain Architect research agent using Zai MCP for comprehensive analysis of EVM chains, perpetual DEX architectures, CEX integrations, and DeFi-TradFi bridges. Use for: blockchain research, protocol comparisons, technical feasibility studies, security audits, compliance analysis, architecture blueprints. Triggers: /research-blockchain, 'blockchain research', protocol comparisons.
Smart Forking - Find and fork from relevant historical sessions using parallel memory search across vault, memvid, handoffs, and ledgers
Classifies task complexity (1-10) for model and agent routing
Multi-Agent Adversarial Analysis System for code security
Create professional, dark-themed architecture diagrams as standalone HTML files with SVG graphics. Use when the user asks for system architecture diagrams, infrastructure diagrams, cloud architecture visualizations, security diagrams, network topology diagrams, or any technical diagram showing system components and their relationships.
Autonomous experiment loop: modifies code, runs experiments, evaluates metrics, keeps improvements. Inspired by karpathy/autoresearch + pi-autoresearch + autoexp. Triggers: /autoresearch, 'auto research', 'optimize continuously', 'experiment loop', 'autonomous optimization'.
Intensive requirement clarification using structured AskUserQuestion workflow. Gathers MUST_HAVE (blocking) and NICE_TO_HAVE (optional) information before implementation. Use when: (1) starting new feature implementation, (2) requirements are ambiguous, (3) multiple approaches possible, (4) before writing any code. Triggers: /clarify, 'clarify requirements', 'ask questions', 'gather requirements'.
Determines WHAT context an agent needs and packages it optimally. Actions: analyze (identify needed context), load (assemble from sources), prune (trim to token budget), inject (write to .claude/context-payload.md). Use when: (1) before spawning teammates, (2) context window is limited, (3) multi-source context assembly. Triggers: /context-engineer, 'prepare context', 'package context', 'context for agent'.
Use when writing or improving README files. Not all READMEs are the same — provides templates and guidance matched to your audience and project type.
Code quality analyzer that identifies "slop" - code violating established coding principles - and suggests concrete improvements. Analyzes code against principles like KISS, YAGNI, SOLID, DRY, and provides before/after fix examples.
End-of-session learning classification. Reviews accumulated learnings and classifies each as GREEN (generic, goes to global wiki), YELLOW (project-specific, goes to project wiki), or RED (sensitive, discarded). Triggered at session end via Stop hook. Use when: (1) session ending, (2) manual review of learnings. Triggers: /exit-review, 'review learnings', 'classify learnings'.
9-language quality gate validation: linting, formatting, type checking, and test execution. Validates code changes meet quality standards before completion. Use when: (1) after code implementation, (2) before PR creation, (3) as part of /orchestrator Step 6, (4) manual quality check. Triggers: /gates, 'quality gates', 'run validation', 'check quality', 'validate code'.
GLM-5 Agent Teams skill for spawning teammates with thinking mode
Ralph Loop pattern with swarm mode: iterative execution until VERIFIED_DONE with multi-agent coordination. Use when: (1) iterative refinement needed, (2) quality gates must pass, (3) automated validation required. Triggers: /iterate, 'iterate until done', 'keep trying', 'fix until passing', 'loop until done'.
Custom skill for kaizen
Access OpenAI developer documentation via Context7 MCP. Provides up-to-date docs for Codex CLI, OpenAI API, Python/Node SDKs, Agents SDK, and MCP configuration. Use when: (1) configuring Codex CLI or MCP servers, (2) writing OpenAI API integrations, (3) building agents with OpenAI SDKs, (4) troubleshooting Codex execution. Triggers: 'openai docs', 'codex documentation', 'openai api reference', 'codex mcp', 'agents sdk'.
Launch quality subagents in parallel using Claude Code 2.1+ native Task tool. Includes ralph-security for OWASP validation and ralph-frontend for WCAG checks. Reads results post-analysis for orchestrator decision-making.
Analyze completed tasks to improve the Ralph system. Saves learnings to living knowledge vault and coordinates insights across 6 ralph-* teammates.
Comprehensive AI code security review using 27 sec-context anti-patterns. Use for code review when security vulnerabilities are suspected, especially for AI-generated code.
Global skill enforcing senior software engineering best practices
Produce a verifiable technical specification before coding. 6 mandatory sections: Interfaces, Behaviors, Invariants (from Aristotle Phase 2), File Plan, Test Plan, Exit Criteria (executable bash commands + expected results). Use when: (1) before implementing features with complexity > 4, (2) as Step 1.5 in orchestrator workflow, (3) when requirements need formalization. Triggers: /spec, 'create spec', 'write specification', 'technical spec'.
A skill for removing AI-generated writing patterns ('slop') from prose. Eliminates telltale signs of AI writing like filler phrases, excessive hedging, overly formal language, and mechanical sentence structures. Use when: writing content that should sound human and natural, editing AI-generated drafts, cleaning up prose for publication, or any content that needs to sound authentic rather than AI-generated. Triggers: 'stop-slop', 'remove AI tells', 'clean up prose', 'make it sound human', 'edit AI writing'.
Living knowledge base management. Actions: search (query vault), save (store learning), index (update indices), compile (raw->wiki->rules graduation), init (create vault structure). Follows Karpathy pipeline: ingest->compile->query. Use when: (1) searching accumulated knowledge, (2) saving learnings, (3) compiling raw notes into wiki, (4) initializing a new vault. Triggers: /vault, 'vault search', 'knowledge base', 'save learning'.
Architecture Decision Records management. Actions: create (new ADR), list (show all), search (find by keyword). Use when: (1) making architecture decisions, (2) choosing between technologies, (3) documenting trade-offs. Triggers: /adr, 'architecture decision', 'decision record', 'document decision'.
Ask clarifying questions when requirements are underspecified
Generate usage report for MiniMax and token optimization Use when: (1) /audit is invoked, (2) task relates to audit functionality.
Browser testing using Chrome DevTools MCP and Playwright for visual verification. Start dev server, navigate, screenshot, Lighthouse audit, console errors, network check. Use when: (1) verifying frontend changes, (2) accessibility auditing, (3) performance testing, (4) visual regression. Triggers: /browser-test, 'test in browser', 'visual test', 'lighthouse audit'.
Session checkpoint management: save, restore, list, clear state snapshots
Remove AI-generated code slop from a branch. Use when cleaning up AI-generated code, removing unnecessary comments, defensive checks, or type casts. Checks diff against main and fixes style inconsistencies.
OpenAI Codex CLI orchestration for AI-assisted development using gpt-5.3-codex model family. Model variants: gpt-5.3-codex (medium), gpt-5.3-codex-high, gpt-5.3-codex-xhigh. Capabilities: code generation, refactoring, automated editing, parallel task execution, session management, code review, architecture analysis, and MCP integration. Actions: analyze, implement, review, fix, refactor with Codex. Keywords: Codex CLI, gpt-5.3-codex, codex exec, code generation, refactoring, parallel execution, session resume, code review, second opinion, independent review, architecture validation, Context7 MCP. Use when: delegating complex code tasks to Codex, running multi-agent workflows, executing automated reviews, implementing features with AI assistance, resuming previous sessions, querying OpenAI documentation. Triggers: 'use codex', 'codex exec', 'run with codex', 'codex resume', 'implement with codex', 'review with codex', 'codex docs'.
Interactive wizard to create PRD or task lists for /task-batch. Uses /clarify and /ask-questions-if-underspecified for precise task definition. Use when: (1) preparing batch execution, (2) creating PRDs, (3) defining task lists with dependencies. Triggers: /create-task-batch, 'create tasks', 'new batch', 'prepare PRD'.
Full curator pipeline for autonomous learning from quality repositories. Executes: discovery → scoring → ranking → ingest → learn → vault sync. Writes to procedural memory AND Obsidian vault for Graph View visualization and graduation pipeline. Use for: populating procedural memory with domain patterns, first-time domain learning, comprehensive knowledge building. Triggers: /curator full, 'learn patterns from repos', 'build knowledge base'.
Design system management for frontend agents. Actions: init (create DESIGN.md from template), load (inject into agent context), validate (check component compliance). Use when: (1) starting a frontend project, (2) generating UI components, (3) reviewing frontend code for design consistency. Triggers: /design-system, 'design system', 'create design', 'design tokens'.
Eval-Driven Development (EDD) Framework v2.87.0 - Define-before-implement pattern with structured evals. Provides workflow: Define specifications → Implement features → Verify against evals. Components: TEMPLATE.md for eval definitions, edd.sh CLI script, /edd skill invocation. Check types: CC- (Capability), BC- (Behavior), NFC- (Non-Functional). Integrates with orchestrator workflow for quality-first development. Keywords: evals, define, implement, verify, capability checks, behavior checks, non-functional checks, template, quality assurance, test-driven, specification. Use when: defining new features with structured evals, implementing with verification requirements, creating quality specifications, TDD-style workflow with evals.
Model-agnostic parallel execution with Agent Teams coordination
Custom skill for minimax
Run multiple Ralph loops concurrently for independent tasks. Supports all 6 ralph-* teammates (coder, reviewer, tester, researcher, frontend, security). Manages parallel agent execution with proper isolation and result aggregation. Use when: (1) multiple independent fixes needed, (2) parallel reviews required, (3) batch processing tasks. Triggers: /parallel, 'parallel loops', 'concurrent execution', 'run in parallel', 'batch'.
Codebase defense analysis system for security profiling
[DEPRECATED] Use /research skill with Zai MCP instead - Optimal patterns for MiniMax MCP tools
Tree of Attacks with Pruning for systematic code analysis
Visualize task dependencies and progress (Gastown-style)
Manage git worktrees with PR workflow and multi-agent review (Claude + Codex). Use when developing features in isolation with easy rollback.
React and Next.js performance optimization guidelines from Vercel Engineering. Use when writing, reviewing, or refactoring React/Next.js code. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.
Test case mutation and variation generator for adversarial testing
Patterns for using Context7 MCP for library documentation (v2.25)
Google Gemini CLI orchestration (v0.22.0+) for AI-assisted development. Capabilities: second opinion/cross-validation, real-time Google Search grounding, codebase architecture analysis with codebase_investigator, Gemini 3 model access, extensions support (Conductor, Endor Labs), parallel code generation, code review from different perspective. INTEGRATED WITH TASK PRIMITIVE - creates traceable tasks in claude-task-viewer. Actions: query, search, analyze, generate, review with Gemini. Keywords: Gemini CLI, Gemini 3, google_web_search, codebase_investigator, second opinion, cross-validation, web research, current information, parallel AI, code review, architecture analysis, gemini prompt, AI comparison, real-time search, alternative perspective, extensions, Conductor. Use when: needing second AI opinion, searching current web information, analyzing codebase architecture, generating code in parallel, getting alternative code review, researching current events/docs, using Gemini extensions.