ai.toolkit.gaia

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.

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.

Provides planned implementation delivery guidance that keeps a branch coherent, stabilized, and ready for testing without redefining the target solution. Use it by implementing the planned tasks against existing repo conventions, keeping diffs scoped, running lint/build locally, and updating tasks_update as work progresses. Use it when a current plan branch is ready for code or definition-file edits, when implementation-side cleanup is needed, or when targeted early QA support is useful during delivery.

Provides execution planning guidance that turns approved architecture into a branch-aware plan with dependencies, QA checkpoints, release gates, and proof expectations. Use it by translating the current architecture into MCP tasks (tasks_create) sequenced by branch, with explicit required_gates and blockers, then keeping the plan current as new work is discovered. Use it after architecture is current, when work needs explicit sequencing instead of informal next steps, or when new branches, blockers, or gate definitions require re-planning.

Provides Gaia's end-to-end workflow coordination guidance for intake, routing, QA checkpoints, release gates, and proof expectations. Use it by routing every meaningful request through the intake → architecture → planning → engineering → testing → release sequence and only completing tasks once the corresponding gates and proof are recorded. Use it for meaningful requests, workflow resets after drift or blockers, and maintenance work that changes Gaia's operating model.

Provides Gaia's formal validation guidance across unit, integration, manual regression, automated regression, and evidence review. Use it by running the test layers required by each task's gates (unit → integration → e2e → manual regression), recording proof labels (e.g. 'curl', 'playwright-mcp') on tasks_complete, and vetoing completion when evidence is missing. Use it when a branch is stable enough for hardening, when high-risk behavior needs targeted early validation, or when release readiness depends on a clear QA signal.

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.

Provides the money-gated lifecycle and coordination playbook for taking a consumer one-off / in-app-purchase product from idea to validated bet through launch and live-ops. Use it to classify a product request, run each of the 10 stages as fan-out -> adversarial review -> synthesis against one shared unit-economics model, and apply net-of-fee money gates with explicit loop-backs. Use when coordinating product discovery, monetization design, validation, soft-launch, or live-ops for non-SaaS consumer software.

Provides the single shared, versioned unit-economics model for consumer one-off / in-app-purchase products, created in Discovery and re-run at every gate. Covers inputs (CPI, install->payer conversion, ARPPU, repeat purchase, ad ARPDAU), the gross-to-net stack (store commission, refunds, chargebacks, fraud, tax), LTV by segment, payback window, and a cashflow/working-capital check. Use whenever product economics must be initialized, updated with measured data, or evaluated at a gate.

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).

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.

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).

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.

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).

Provides Stage 3 monetization-design guidance for consumer one-off / in-app-purchase products - selecting a primary model (premium / freemium-IAP / free-ads / hybrid) against retention and platform, a price ladder with psychology, an IAP catalogue, ad-revenue economics, a faucet/sink economy balanced via cohort simulation, a conversion funnel with lifetime ARPPU, validation of net-of-fee unit economics with a cashflow check, and translation into product requirements. Use to design the money model and prove net LTV:CAC >= 3:1 with payback before requirements ship.

Provides the money-gate evaluation discipline for the product-discovery lifecycle - pre-registered thresholds, net-of-fee revenue math (store commission, refunds, chargebacks, fraud, tax), LTV:CAC and payback checks, a cashflow/working-capital check, deflated willingness-to-pay, and pass/fail/kill routing along loop-back edges. Use at every stage gate to decide advance, loop-back, or kill for consumer one-off / in-app-purchase products.

Provides the Stage-10 closure and portfolio-compounding playbook for consumer one-off / in-app-purchase products - end-of-life decision triggers and review cadence, a three-way continue/maintenance/sunset evaluation plus sequel/DLC, a humane sunset that honors recent one-off purchases, a portfolio retrospective that harvests capabilities and calibrates the unit-economics model, documenting realized priors, and transferring the audience/CRM/payer-base forward into a new Discovery cycle. Use to close a title and compound learnings back to Stage 1. Money-gated and net-of-fee aware (decisions run on NET-LTV vs operating cost and realized-vs-predicted calibration).

Provides Stage 6 production-and-hardening guidance for consumer one-off / in-app-purchase products - scaling content to v1 with tooling and post-launch runway, full art/audio/VFX to the lovable bar with licensing cleared, localization-at-scale with localized price tiers reconciled to net-by-geo, device/OS matrix and performance, backend/economy services with anti-cheat and IAP-fraud/refund-abuse defenses and load testing, an accessibility baseline, and multi-layer QA reconciling production IAP end-to-end. Use to reach feature/content-complete with a production-grade IAP/entitlement path.

Provides the Stage-8 build-iteration and soft-launch playbook for consumer one-off / in-app-purchase products - always-green trunk with feature-flags, a versioned telemetry/event taxonomy wired before external testers, closed/open beta hardening, soft-launch in cheap representative geos with attribution, reading D1/D7/D30 + conversion + ARPPU/ARPDAU by cohort/source, modeling pLTV vs CPI, one-variable A/B tuning, iterate-or-kill discipline, and clearing the multi-condition scale gate. Use to prove real-money retention before paid scale. Money-gated and net-of-fee aware (require net LTV > CPI + payback).

Provides Stage 4 validation guidance for consumer one-off / in-app-purchase products - framing falsifiable money hypotheses under a cost ceiling, IP/trademark/name/domain clearance, problem and solution interviews that probe real past spend, concept tests with a clickable paywall, deflated willingness-to-pay (Van Westendorp, conjoint/MaxDiff), fake-door and painted-price tests, landing-page commitment ladders, ad-creative CPI testing that replaces the placeholder CAC, and community pre-validation. Use to get a go/no-go with at least one money-on-the-line signal before building.

Provides Stage 5 vertical-slice / MVP guidance for consumer one-off / in-app-purchase products - the spec stack (one-pager -> PRD/GDD -> monetization design doc as a binding instrumentation contract), MLP vs MVG with a designed purchase moment, a prototyping fidelity ladder, tech/billing spikes (StoreKit/Play Billing/Steamworks sandbox), server-authority and anti-cheat decisions, building analytics and IAP/entitlement rails first, and a shippable slice with one of every SKU type. Use to ship a lovable core loop with a live sandbox purchase and a clean reconciled funnel.

Researches and outlines multi-step plans. Use this skill when you want to create a detailed, actionable plan for a complex task or feature. The skill clarifies requirements with the user, fans out 3 identical parallel subagents to produce dispassionate plan proposals, critiques them, and synthesizes the best single plan for others to execute.

Provides custom-agent definition guidance with clear role boundaries, strong descriptions, valid tool scopes, delegation rules, and overlap control. Use it by following the agents-specification reference (formatter, role contract, tool allow-list, delegation rules) when adding or revising an agent file, and by mirroring changes across both ".claude/agents/" and ".github/agents/" trees. Use it when adding, revising, auditing, or rationalizing agent files, role ownership, naming, or contract alignment.

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.