fa-architecture
Provides Gaia architecture documentation guidance that keeps docs, README messaging, and design decisions aligned to the current operating model. Use it by updating the relevant files under /docs/architecture/ (system components, use cases, class diagrams, UI) before any planning or implementation that changes structure, then resolving doc↔code drift before resuming feature work. Use it when system structure, trust boundaries, interfaces, workflows, ownership, or architectural assumptions change, or when architecture drift blocks planning or delivery.
fa-default-tech-stack
Provides Gaia's default full-stack baseline with React, TypeScript, Redux Toolkit, Tailwind CSS, and shadcn/ui on the frontend plus .NET, EF Core, PostgreSQL, and MCP exposure on the backend. Use it by adopting the documented baseline (versions, scaffolds, references) for any new app or unspecified-stack request, and by declaring the stack explicitly before planning when the request leaves it implicit. Use it when the request or repo leaves stack choice open, when bootstrapping a new application, or when standardizing an existing codebase onto Gaia's preferred platform.
fa-ui-engineering
Provides React UI implementation guidance that enforces the design system, shadcn/ui composition, semantic Tailwind tokens, and responsive layout discipline. Use it by composing shadcn/ui primitives with semantic Tailwind tokens (no raw color/spacing literals), respecting the responsive layout rules, and removing dead tokens as you go. Use it when building or refactoring user-facing React components, screens, forms, dialogs, or styling where UI consistency and token cleanup matter.
fa-product-discovery
Provides Stage 1 product-discovery guidance for consumer one-off / in-app-purchase products - trend scanning (Sensor Tower, AppMagic, data.ai, store charts, Steam tags/wishlists, TikTok/Reddit/Product Hunt), opportunity sourcing, demand-signal harvesting as the cheapest kill gate, competitor teardowns, persona + JTBD + WTP-by-segment, and bottoms-up TAM/SAM/SOM sized net-of-fee. Use to find one buildable, monetizable bet and exit with an Opportunity Thesis, unit-economics model v0, and a GO/NO-GO/PIVOT call.
fa-product-compliance
Provides the Stage-7 compliance, ratings, legal and certification playbook for consumer one-off / in-app-purchase products - IARC age ratings and content descriptors, store/console submission and resubmission loops, loot-box/gacha/gambling-law handling (odds disclosure, disable-where-banned, minor spend limits), kids/privacy/consent (COPPA, GDPR-K, ATT, GDPR/CCPA), indirect tax, IP/asset licensing carry-through, and the EULA/ToS/Privacy-Policy set. Use to clear certification before soft-launch and to loop rejections back to production hardening. Money-gated and net-of-fee aware (store-remitted vs developer-remitted tax changes net revenue).
fa-create-skill
Provides Gaia skill-definition maintenance guidance with clear naming, descriptions, ownership boundaries, references, and reuse decisions. Use it by following the skills-specification reference (naming, formatter shape, scope sections, references) when adding or revising a SKILL.md, and by mirroring changes across both ".claude/skills/" and ".github/skills/" trees. Use it when adding, revising, auditing, or rationalizing skills, improving invocation quality, or consolidating drifting procedural guidance.
fa-product-gtm-launch
Provides the Stage-9 go-to-market, launch and user-acquisition playbook for consumer one-off / in-app-purchase products - lock pricing/offer ladder before traffic, ASO/store-listing optimization with a store-page CVR gate, earned/owned demand priming, platform-featuring pitches, creator seeding, launch sequencing, paid UA only after organic CVR validates, a creative-testing engine, virality/referral with fraud detection, support/refund ops, and a blended-CAC-vs-LTV scale-decision control loop. Use to build a repeatable acquisition engine. Money-gated and net-of-fee aware (require positive defensible blended CAC:LTV with payback).
fa-product-ideation
Provides Stage 2 ideation guidance for consumer one-off / in-app-purchase products - an ideation frame with a monetization hypothesis and anti-goals (no auto-renew), divergent ideation (brainwriting, Crazy 8s, SCAMPER on top-grossing, genre mashup, forced constraints), a structured backlog with a mandatory monetization seed, hook/core-loop/meta-loop with a monetization overlay, RICE plus desirability/feasibility/net-viability scoring, and selection of ONE concept. Use to converge from an Opportunity Thesis to one concept brief with riskiest assumptions and provisional kill thresholds.
fa-product-liveops
Provides the Stage-10 live-ops operations playbook for consumer one-off / in-app-purchase products - a live-ops data/economy-health/experimentation foundation, a recurring live-ops calendar with safe rollback, lifecycle CRM/push/in-app, continuous one-variable monetization and store/price experiments, spend-spectrum segmentation and personalized offers, a guardrailed whale/high-value program, community/crisis ops, churn analysis and resurrection, and platform-policy/SDK monitoring. Use to run the steady-state revenue engine. Money-gated and net-of-fee aware (reconcile NET-of-fee revenue, guard retention/refunds, no auto-renew offers).
zig-0.15
This skill provides Zig 0.15.x API guidance and should be used when writing or reviewing Zig code. It ensures correct usage of Zig 0.15 APIs, preventing common mistakes from using outdated 0.11/0.12/0.13/0.14 patterns. Essential for ArrayList, std.Io.Writer/Reader (Writergate), HTTP client, Ed25519, JSON, and type introspection APIs.
zig-0.16
Zig 0.16.0 API guidance and porting notes. Use this when writing or upgrading Zig code to the 0.16.0 stable release (std.Io era, @Type removal, @cImport deprecation).
zig-tiger-style
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n8n-code-javascript
Write JavaScript code in n8n Code nodes. Use when writing JavaScript in n8n, using $input/$json/$node syntax, making HTTP requests with $helpers, working with dates using DateTime, troubleshooting Code node errors, or choosing between Code node modes.
n8n-workflow-patterns
Proven workflow architectural patterns from real n8n workflows. Use when building new workflows, designing workflow structure, choosing workflow patterns, planning workflow architecture, or asking about webhook processing, HTTP API integration, database operations, AI agent workflows, or scheduled tasks.
n8n-workflow-architect
Strategic automation architecture advisor. Use when users want to plan automation solutions, evaluate their tech stack (Shopify, Zoho, HubSpot, etc.), decide between n8n vs Python/Claude Code, or need guidance on production-ready automation design. Invokes plan mode for complex architectural decisions.
n8n-validation-expert
Interpret validation errors and guide fixing them. Use when encountering validation errors, validation warnings, false positives, operator structure issues, or need help understanding validation results. Also use when asking about validation profiles, error types, or the validation loop process.
n8n-node-configuration
Operation-aware node configuration guidance. Use when configuring nodes, understanding property dependencies, determining required fields, choosing between get_node_essentials and get_node_info, or learning common configuration patterns by node type.
n8n-mcp-tools-expert
Expert guide for using n8n-mcp MCP tools effectively. Use when searching for nodes, validating configurations, accessing templates, managing workflows, or using any n8n-mcp tool. Provides tool selection guidance, parameter formats, and common patterns.
n8n-expression-syntax
Validate n8n expression syntax and fix common errors. Use when writing n8n expressions, using {{}} syntax, accessing $json/$node variables, troubleshooting expression errors, or working with webhook data in workflows.
n8n-code-python
Write Python code in n8n Code nodes. Use when writing Python in n8n, using _input/_json/_node syntax, working with standard library, or need to understand Python limitations in n8n Code nodes.
ai-interaction
Continuous communication channel via MCP AI Interaction tool. Activate with 'khởi động ai_interaction'. Enables real-time Vietnamese conversation with action-first principle - execute first, explain minimally.
web-browsing
Web research with automatic fallback mechanism. WebFetch → Browser MCP → User assistance via ai_interaction. Use when need to browse web.
project-scanner
Codebase analysis tool for quality-first editing. Scan before edit to understand relationships, patterns, and impact.
angular-coding
Angular coding standards with version-aware patterns. Automatically detects Angular version from package.json and applies appropriate patterns. Use when writing Angular components, services, or TypeScript code.
tech
Research, validate, and set up technology profiles in content/technologies. Handles both new entries and updates to existing ones.
deslop
Remove AI-generated code slop from the current branch by analyzing diffs against main and cleaning up unnecessary comments, defensive code, and style inconsistencies.
front-end-design
Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, or applications. Generates creative, polished code that avoids generic AI aesthetics.
glab
Expert guidance for using the GitLab CLI (glab) to manage GitLab issues, merge requests, CI/CD pipelines, repositories, and other GitLab operations from the command line. Use this skill when the user needs to interact with GitLab resources or perform GitLab workflows.
codeagent
Execute codeagent-wrapper for multi-backend AI code tasks. Supports Codex, Claude, and Gemini backends with file references (@syntax) and structured output.
codex
Execute Codex CLI for code analysis, refactoring, and automated code changes. Use when you need to delegate complex code tasks to Codex AI with file references (@syntax) and structured output.
gemini
Execute Gemini CLI for AI-powered code analysis and generation. Use when you need to leverage Google's Gemini models for complex reasoning tasks.
kiro-specs
Create a Kiro spec for a feature in .kiro/specs create/update feature spec/PRD/RFC—requirements, design doc, and implementation tasks checklist.Trigger on spec/specification/PRD/RFC/tech spec, requirements/user story/acceptance criteria/EARS, design doc/architecture, task breakdown/implementation plan/checklist; 需求/验收/设计/任务.
living-documentation
Sync spec files with code changes. Triggers when modifying code that affects .kiro/specs/*/requirements.md or .kiro/specs/*/design.md. Use after implementing features, fixing bugs, or refactoring that changes behavior documented in specs.
multi-agent-orchestration
Orchestrate multi-agent workflows from a Kiro spec using codex (code) + Gemini (UI), including dispatch/review/state sync via AGENT_STATE.json + PROJECT_PULSE.md; triggers on user says "Start orchestration from spec at <path>", "Run orchestration for <feature>", or mentions multi-agent execution.
sequential-orchestration
Execute spec tasks one at a time with tmux visibility. Python-based orchestrator with transparent serial execution. Triggers on: rate limit, overnight run, throttled execution, avoid quota exhaustion, sequential mode, slow execution, or user says 'Run sequential orchestration for <spec>'.
test-driven-development
Use when implementing any feature or bugfix, before writing implementation code
listenhub
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asr
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image-gen
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explainer
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creator
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tts
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podcast
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content-parser
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effect-best-practices
Enforces Effect-TS patterns for services, errors, layers, and atoms. Use when writing code with Effect.Service, Schema.TaggedError, Layer composition, or effect-atom React components.
django-celery-expert
Expert Django Celery guidance for asynchronous task processing. Use when designing background tasks, configuring Celery workers, handling task retries and errors, optimizing Celery performance, implementing periodic tasks with Celery Beat, or setting up production monitoring for Celery. Do not use for general Django questions unrelated to Celery, non-Celery task systems (Django Q, Huey, RQ), ML/data pipeline orchestration (Airflow, Prefect), or frontend and API-only concerns. Follows Vinta's Django Celery best practices.
django-expert
Expert Django backend development guidance. Use when creating Django models, views, serializers, or APIs; debugging ORM queries or migrations; optimizing database performance; implementing authentication; writing tests; or working with Django REST Framework. Follows Django best practices and modern patterns.
cdrf-expert
Expert guidance for Django REST Framework class-based views using Classy DRF (https://www.cdrf.co). Use when selecting or debugging APIView, GenericAPIView, concrete generic views, mixin combinations, or ViewSet/GenericViewSet/ModelViewSet behavior; tracing method resolution order (MRO); understanding which method to override (`create` vs `perform_create`, `update` vs `perform_update`, `destroy` vs `perform_destroy`, `get_queryset`, `get_serializer_class`); and comparing behavior across DRF versions. Do not use for function-based views, GraphQL, FastAPI/Flask, frontend work, or non-DRF backend frameworks.
audit
Run technical quality checks across accessibility, performance, theming, responsive design, and anti-patterns. Generates a scored report with P0-P3 severity ratings and actionable plan. Use when the user wants an accessibility check, performance audit, or technical quality review.
cyberpunk-tcg-rules
Official Cyberpunk TCG gameplay rules, glossary, and rule-resolution guidance for this repository. Use whenever work touches gameplay logic, turn flow, combat, Gig theft, Street Cred, deckbuilding, RAM limits, card behavior, AI behavior, balance, rules text, UI copy, tests, or design docs and the output must stay aligned with the published gameplay guide.
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