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Found 9,266 Skills
World-class character and art style consistency for AI-generated images and videos - ensures visual coherence across series, maintains character identity, and provides rigorous QA before deliveryUse when "character consistency, art style, same character, consistent character, visual continuity, series, turnaround sheet, character sheet, reference image, character bible, style guide, anime character, consistent look, face consistency, outfit consistency, lora training, ip-adapter, flux kontext, visual qa, art quality, generation review, style drift, character drift, character-consistency, art-style, visual-qa, ai-art, image-generation, video-generation, anime, illustration, lora, ip-adapter, flux, midjourney, stable-diffusion" mentioned.
Implement end-to-end feature changes in go-sphere scaffold projects by following sphere-layout conventions and generation workflow. Use when adding or modifying APIs, protobuf contracts, Ent schemas, bind/map registration, service logic, or cross-layer refactors that must stay protocol-first and avoid manual edits to generated files.
Universal context reviewer: delegates arbitrary context (plans, decisions, documents, architecture proposals) to external agents (Codex + Gemini) for independent review with debate protocol. Context always passed via files.
Markets orchestration — connects ESPN live schedules with Kalshi & Polymarket prediction markets. Unified dashboards, odds comparison, entity search, and bet evaluation across platforms. Use when: user wants to see prediction market odds alongside ESPN game schedules, compare odds across platforms, search for a team/player on Kalshi or Polymarket, check for arbitrage between ESPN odds and prediction markets, or evaluate a specific game's market value. Don't use when: user wants raw prediction market data without ESPN context — use polymarket or kalshi directly. For pure odds math (conversion, de-vigging, Kelly) — use betting. For live scores without market data — use the sport-specific skill.
MongoDB and PostgreSQL database administration. Databases: MongoDB (document store, aggregation, Atlas), PostgreSQL (relational, SQL, psql). Capabilities: schema design, query optimization, indexing, migrations, replication, sharding, backup/restore, user management, performance analysis. Actions: design, query, optimize, migrate, backup, restore, index, shard databases. Keywords: MongoDB, PostgreSQL, SQL, NoSQL, BSON, aggregation pipeline, Atlas, psql, pgAdmin, schema design, index, query optimization, EXPLAIN, replication, sharding, backup, restore, migration, ORM, Prisma, Mongoose, connection pooling, transactions, ACID. Use when: designing database schemas, writing complex queries, optimizing query performance, creating indexes, performing migrations, setting up replication, implementing backup strategies, managing database permissions, troubleshooting slow queries.
Architecture-aware project initialization combining online research with archetype selection. project initialization, new project, architecture decision, project setup, which architecture, choose architecture, project architecture Use when: initializing a new project and need to select an appropriate architecture based on project type, team size, domain complexity, and current best practices DO NOT use when: architecture is already decided - use project-init instead.
Bridge web search capability for LLM workflows. Use when user asks for latest info, external facts, or source links and the active model/toolchain lacks direct search ability.
Expert guide for Schema.org structured data and JSON-LD implementation. Use when creating schema markup, validating structured data, implementing rich results (FAQ, HowTo, Product, Article, LocalBusiness, Breadcrumb, Organization, etc.), troubleshooting rich snippet eligibility, or understanding Google's structured data requirements.
Use when writing or reviewing Java unit tests. Enforces Mockito/JUnit 5 best practices - strict stubbing, no lenient mode, specific matchers, complete flow stubbing, Arrange-Act-Assert structure, and clear test naming.
Competitive battle card creation for sales teams combining competitive intelligence, sales enablement, and document formatting. Use when building battle cards, competitive analysis decks, or win/loss analysis materials.
When the user wants to set up, optimize, or manage Google Ads campaigns. Also use when the user mentions "Google Ads," "Google Search Ads," "PPC," "SEM," "PMF testing with ads," "test product-market fit," "Responsive Search Ads," "RSA," "Performance Max," "Quality Score," "keyword bidding," or "Google Display/YouTube ads."
When the user wants to add recommendations, links, or content to Grokipedia. Also use when the user mentions "Grokipedia," "GEO wiki," "AI encyclopedia," "suggest Grokipedia article," "Grokipedia citation," "Grokipedia listing," "AI search citation," "GEO visibility," or "Grokipedia optimization." For parasite SEO strategy, use parasite-seo.