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Claude Skills by levalencia
github.com/levalencia516 skills2 installs534 views
- Kalshi Prediction MarketContext and working knowledge for Calci’s prediction-market domain, which is powered by Kalshi. Use this skill whenever the user asks about Calci prediction markets, Kalshi markets, tickers, order books, pricing, settlement, or the Kalshi API/WebSocket.Votes: 0GitHub stars: 3
- Kieran Python ReviewerUse this agent when you need to review Python code changes with an extremely high quality bar. This agent should be invoked after implementing features, modifying existing code, or creating new Python modules. The agent applies Kieran's strict Python conventions and taste preferences to ensure code meets exceptional standards.\\n\\nExamples:\\n- <example>\\n Context: The user has just implemented a new FastAPI endpoint.\\n user: \"I've added a new user registration endpoint\"\\n assistant: \"...Votes: 0GitHub stars: 3
- Kieran Rails ReviewerUse this agent when you need to review Rails code changes with an extremely high quality bar. This agent should be invoked after implementing features, modifying existing code, or creating new Rails components. The agent applies Kieran's strict Rails conventions and taste preferences to ensure code meets exceptional standards.\\n\\nExamples:\\n- <example>\\n Context: The user has just implemented a new controller action with turbo streams.\\n user: \"I've added a new update action to the post...Votes: 0GitHub stars: 3
- Kieran Typescript ReviewerUse this agent when you need to review TypeScript code changes with an extremely high quality bar. This agent should be invoked after implementing features, modifying existing code, or creating new TypeScript components. The agent applies Kieran's strict TypeScript conventions and taste preferences to ensure code meets exceptional standards.\\n\\nExamples:\\n- <example>\\n Context: The user has just implemented a new React component with hooks.\\n user: \"I've added a new UserProfile componen...Votes: 0GitHub stars: 3
- Kol Content MonitorTrack what key opinion leaders (KOLs) in your space are posting on LinkedIn and Twitter/X. Surfaces trending narratives, high-engagement topics, and early signals of emerging conversations before they peak. Chains linkedin-profile-post-scraper and twitter-scraper. Use when a marketing team wants to ride trends rather than create them from scratch, or when a founder wants to know which topics are resonating with their audience.Votes: 0GitHub stars: 3
- Kol DiscoveryFind Key Opinion Leaders (KOLs) in a given domain by combining web research with LinkedIn post search. Given a company/idea and target domain, generates authority keywords, searches LinkedIn posts to find prolific authors with high engagement, and merges with web-researched influencers. Use when someone wants to "find influencers in X space" or "who are the KOLs for Y industry."Votes: 0GitHub stars: 3
- Kol Engager IcpFind ICP-fit leads from KOL audiences on LinkedIn. Given a list of KOLs, scrapes their most relevant high-engagement post from the last 30 days, extracts engagers (reactors + commenters), pre-filters by position, enriches top profiles, and ICP-classifies. Cost-controlled: 1 post per KOL. Use when someone wants to "find leads from KOL audiences" or "scrape engagers from influencer posts" or after running kol-discovery.Votes: 0GitHub stars: 3
- Langchain4j Ai Services PatternsProvides patterns to build declarative AI Services with LangChain4j using interface-based patterns, annotations, memory management, tools integration, and advanced application patterns. Use when implementing type-safe AI-powered features with minimal boilerplate code in Java applications.Votes: 0GitHub stars: 3
- Langchain4j Mcp Server PatternsProvides Model Context Protocol (MCP) server implementation patterns with LangChain4j. Use when building MCP servers to extend AI capabilities with custom tools, resources, and prompt templates.Votes: 0GitHub stars: 3
- Langchain4j Rag Implementation PatternsProvides Retrieval-Augmented Generation (RAG) implementation patterns with LangChain4j. Handles document ingestion pipelines, embedding stores, vector search strategies, and knowledge-enhanced AI applications. Use when creating question-answering systems over document collections or AI assistants with external knowledge bases.Votes: 0GitHub stars: 3
- Langchain4j Spring Boot IntegrationProvides integration patterns for LangChain4j with Spring Boot. Handles auto-configuration, dependency injection, and Spring ecosystem integration. Use when embedding LangChain4j into Spring Boot applications.Votes: 0GitHub stars: 3
- Langchain4j Testing StrategiesProvides testing strategies for LangChain4j-powered applications. Handles mocking LLM responses, testing retrieval chains, and validating AI workflows. Use when testing AI-powered features reliably.Votes: 0GitHub stars: 3
- Langchain4j Vector Stores ConfigurationProvides configuration patterns for LangChain4J vector stores in RAG applications. Use when building semantic search, integrating vector databases (PostgreSQL/pgvector, Pinecone, MongoDB, Milvus, Neo4j), implementing embedding storage/retrieval, setting up hybrid search, or optimizing vector database performance for production AI applications.Votes: 0GitHub stars: 3
- Launch Positioning BuilderResearch competitors, analyze their messaging, and generate a positioning document with category definition, differentiation claims, value propositions, and proof points. Chains web research, competitor site analysis, and review mining to produce a positioning doc ready for website copy and sales deck use. Use when a product marketing team needs to define or refresh positioning ahead of a launch, rebrand, or competitive shift.Votes: 0GitHub stars: 3
- Launch StrategyWhen the user wants to plan a product launch, feature announcement, or release strategy. Also use when the user mentions 'launch,' 'Product Hunt,' 'feature release,' 'announcement,' 'go-to-market,' 'beta launch,' 'early access,' 'waitlist,' 'product update,' 'how do I launch this,' 'launch checklist,' 'GTM plan,' or 'we're about to ship.' Use this whenever someone is preparing to release something publicly. For ongoing marketing after launch, see marketing-ideas.Votes: 0GitHub stars: 3
- Lead QualificationLead qualification engine with conversational intake. Asks structured questions to understand your qualification criteria, generates a reusable qualification prompt, then batch-enriches leads via Apify LinkedIn scraping and scores them with parallel processing. Outputs qualified/disqualified verdicts with confidence scores and reasoning to Google Sheets (via Rube) or CSV. Supports calibration mode for prompt refinement.Votes: 0GitHub stars: 3
- Learnings ResearcherUse this agent when you need to search institutional learnings in docs/solutions/ for relevant past solutions before implementing a new feature or fixing a problem. This agent efficiently filters documented solutions by frontmatter metadata (tags, category, module, symptoms) to find applicable patterns, gotchas, and lessons learned. The agent excels at preventing repeated mistakes by surfacing relevant institutional knowledge before work begins.\\n\\n<example>Context: User is about to impleme...Votes: 0GitHub stars: 3
- LfgFull autonomous engineering workflowVotes: 0GitHub stars: 3
- Linkedin Influencer DiscoveryDiscover top LinkedIn influencers and voices by topic, industry, follower count, and country. Use when you need to find the top 100 voices in a space, build influencer lists for outreach, or identify thought leaders on LinkedIn.Votes: 0GitHub stars: 3
- Linkedin Post ResearchSearch LinkedIn posts by keywords using Crustdata API directly, deduplicate and sort by engagement. Outputs to CSV or JSON. Use when researching LinkedIn content around specific topics.Votes: 0GitHub stars: 3
- LintUse this agent when you need to run linting and code quality checks on Ruby and ERB files. Run before pushing to origin.Votes: 0GitHub stars: 3
- Llm CliProcess textual and multimedia files with various LLM providers using the llm CLI. Supports both non-interactive and interactive modes with model selection, config persistence, and file input handling.Votes: 0GitHub stars: 3
- Ln 001 Standards ResearcherResearch standards/patterns via MCP Ref. Generates Standards Research for Story Technical Notes subsection. Reusable worker.Votes: 0GitHub stars: 3
- Ln 002 Best Practices ResearcherResearch best practices via MCP Ref/Context7/WebSearch and create documentation (guide/manual/ADR/research). Single research, multiple output types.Votes: 0GitHub stars: 3
- Ln 003 Push AllCommit and push ALL changes (staged + unstaged + untracked) to the remote repositoryVotes: 0GitHub stars: 3
- Ln 004 Agent Config SyncSync skills (symlinks) and MCP settings from Claude to Gemini CLI and Codex CLIVotes: 0GitHub stars: 3
- Ln 005 Environment ScannerProbes CLI agents (Codex, Gemini) and writes docs/environment_state.json — agent availability config for Phase 0Votes: 0GitHub stars: 3
- Ln 100 Documents PipelineTop orchestrator for complete doc system. Delegates to ln-110 coordinator (project docs) + ln-120-150 workers. Phase 3: global cleanup. Idempotent.Votes: 0GitHub stars: 3
- Ln 1000 Pipeline OrchestratorMeta-orchestrator: reads kanban board, lets user pick ONE Story, drives it through pipeline 300->310->400->500 via TeamCreate. Creates worktree isolation; coordinates workers + reports.Votes: 0GitHub stars: 3
- Ln 110 Project Docs CoordinatorCoordinates project documentation creation. Gathers context once, detects project type, delegates to specialized workers (ln-111-115).Votes: 0GitHub stars: 3
- Ln 111 Root Docs CreatorCreates 5 root documentation files (CLAUDE.md, docs/README.md, documentation_standards.md, principles.md, tools_config.md).Votes: 0GitHub stars: 3
- Ln 113 Backend Docs CreatorCreates 2 backend docs (api_spec.md, database_schema.md). Invoked when hasBackend or hasDatabase detected.Votes: 0GitHub stars: 3
- Ln 114 Frontend Docs CreatorCreates design_guidelines.md for frontend projects. Invoked when hasFrontend detected.Votes: 0GitHub stars: 3
- Ln 115 Devops Docs CreatorCreates infrastructure.md (always) and runbook.md (if hasDocker). DevOps documentation worker.Votes: 0GitHub stars: 3
- Ln 130 Tasks Docs CreatorCreates task management documentation (docs/tasks/README.md + kanban_board.md). Sets up Linear integration and task tracking rules.Votes: 0GitHub stars: 3
- Ln 160 Docs Skill ExtractorScans project docs, classifies procedural content, extracts into .claude/commands skillsVotes: 0GitHub stars: 3
- Ln 161 Skill CreatorCreates .claude/commands from procedural doc sections with proper structure and transformationVotes: 0GitHub stars: 3
- Ln 162 Skill ReviewerUniversal skill reviewer: SKILL mode (D1-D9 + M1-M5) or COMMAND mode (.claude/commands review)Votes: 0GitHub stars: 3
- Ln 200 Scope DecomposerOrchestrates full decomposition (scope → Epics → Stories → RICE prioritization) by delegating ln-210 → ln-220 → ln-230. Sequential processing. Epic 0 for Infrastructure.Votes: 0GitHub stars: 3
- Ln 201 Opportunity DiscovererTraffic-First opportunity discovery. KILL funnel filters ideas by traffic channel, demand, competition, revenue, interest, MVP-ability. Outputs one idea + one channel recommendation.Votes: 0GitHub stars: 3
- Ln 210 Epic CoordinatorCREATE/REPLAN Epics from scope (3-7 Epics). Batch Preview + Auto-extraction. Decompose-First Pattern. Auto-discovers team ID.Votes: 0GitHub stars: 3
- Ln 220 Story CoordinatorCREATE/REPLAN Stories for Epic (5-10 Stories). Multi-epic routing: auto-groups Stories by correct Epic. Delegates ln-001 for standards research. Self-Check phase.Votes: 0GitHub stars: 3
- Ln 221 Story CreatorCreates Stories from IDEAL plan (CREATE) or appends user-requested Stories (ADD). Generates 9-section documents, validates INVEST, creates in Linear.Votes: 0GitHub stars: 3
- Ln 222 Story ReplannerReplans Stories when Epic requirements change. Compares IDEAL vs existing, categorizes operations (KEEP/UPDATE/OBSOLETE/CREATE), executes in Linear.Votes: 0GitHub stars: 3
- Ln 230 Story PrioritizerRICE prioritization per Story with market research. Generates consolidated prioritization table in docs/market/[epic-slug]/prioritization.md.Votes: 0GitHub stars: 3
- Ln 300 Task CoordinatorOrchestrates task operations. Analyzes Story, builds optimal plan (1-8 implementation tasks), delegates to ln-301-task-creator (CREATE/ADD) or ln-302-task-replanner (REPLAN). Auto-discovers team ID.Votes: 0GitHub stars: 3
- Ln 301 Task CreatorCreates ALL task types (implementation, refactoring, test). Generates task documents from templates, validates type rules, creates in Linear, updates kanban.Votes: 0GitHub stars: 3
- Ln 302 Task ReplannerUpdates ALL task types (implementation/refactoring/test). Compares IDEAL plan vs existing tasks, categorizes KEEP/UPDATE/OBSOLETE/CREATE, applies changes in Linear and kanban.Votes: 0GitHub stars: 3
- Ln 310 Multi Agent ValidatorValidates Stories/Tasks, plans, or context via parallel multi-agent review (Codex + Gemini). Merges findings, debates, applies fixes. GO/NO-GO verdict.Votes: 0GitHub stars: 3
- Ln 400 Story ExecutorOrchestrates Story tasks. Prioritizes To Review -> To Rework -> Todo, delegates to ln-401/402/403/404. Sets Story to To Review when all tasks Done. Metadata-only loading.Votes: 0GitHub stars: 3