ari-dai-skills

Local dev skill for the Dataspheres AI Content API. Wraps /api/v1/ REST endpoints for local-to-production content workflows. Use when the user wants to push pages, generate release notes from git log, list pages, or update content in a datasphere from their local machine.

Full newsletter lifecycle — create, configure all settings (frequency, personalization, AI model, web search, reply threading, plan mode wiring), manage subscribers, attach forms, draft and manage issues, preview personalized letters, enable private chat and email replies, and test in dev.

Drive the Dataspheres AI platform from Claude Code — read conversation history, post messages as the user (via API key), poll for ARI replies, read the Reality Engine debug log, update the plan and outcomes, and control orchestration flow. Use when you need Claude Code to interact with ARI or inspect/modify a running reality session.

Knowledge-graph tools for Dataspheres AI — build typed graphs, relate nodes with VISUAL or executable TASK edges, group into colored container bubbles, auto-detect article hero images, embed graphs in pages, run scheduled searches, and report.

Sequencers tools for Dataspheres AI

Manage Kanban tasks, plan modes, and project workflows in Dataspheres AI

Skill for producing high-fidelity, interactive blog posts, research reports, and intelligent reports on the Dataspheres AI platform. Drives ARI and ari-dai-skills to use the full tool suite — web search, image generation, YouTube embeds, code blocks, Mermaid diagrams, datasets, live data cards, citations, and SEO metadata — to produce publication-ready interactive pages.

Media tools for Dataspheres AI

Folders tools for Dataspheres AI

Pages tools for Dataspheres AI

Background AI drafting for Dataspheres AI pages

Connections tools for Dataspheres AI

Manage active datasphere context and session state

Conversation tools for Dataspheres AI

Full LMS course + quiz REST API for Dataspheres AI. Build a course (modules → lessons → graded quizzes), author quiz questions with correct answers + points, manage enrollment, track per-quiz results and the course gradebook, and issue verifiable certificates. Courses are pages-native — the student view is the course's overview page under /pages/:uri/:slug.

Data Cards tools for Dataspheres AI

Datasets tools for Dataspheres AI

Dataspheres tools for Dataspheres AI

Documents tools for Dataspheres AI

Export datasphere content to local workspace/ files

Images tools for Dataspheres AI

Knowledge Bank tools for Dataspheres AI

Upload and manage media in the Dataspheres AI library

Linked Urls tools for Dataspheres AI

Posts tools for Dataspheres AI

Author and edit presentation decks in Dataspheres AI via REST + ARI tools — whole-deck get/set plus granular slide and per-slide component CRUD for every component type. Always test locally first.

Coding principles, completion standards, file headers, and the dai-skills motto. Read before writing any code or marking any task done.

Debug the Render-hosted production deployment directly via the Render MCP — tail service logs, inspect deploys, check service + Postgres health, read env, and correlate errors with deploy/maintenance events. Use when prod is erroring and you need real infrastructure data instead of inferring from the app's error table.

AI-powered web research via Dataspheres AI assistant conversations

Saved Lists tools for Dataspheres AI

Search tools for Dataspheres AI

Create and run automated workflows in Dataspheres AI

Design, run, and analyze surveys in Dataspheres AI — create, add/edit/delete/reorder questions, collect responses, view analytics, export data.

Tasks tools for Dataspheres AI

Create and manage surveys via API. Creates survey pages with questions, configures settings (live results, anonymous, etc.), and seeds to any datasphere locally or in prod. Always test locally first.

The default writing voice for Dataspheres AI page content — blog posts, reports, docs, landing copy. A measured, white-paper register that reads like a knowledgeable human wrote it, NOT like an AI rushed it. Use this voice by default whenever composing prose for a page; invoke explicitly to revoice existing copy that "sounds like AI". Defines the AI tells to strip out and the register to write in, with before/after examples.

Reusable, sanitizer-safe inline data visualizations for Dataspheres pages — stat cards, lifecycle/flow strips, layered architecture diagrams. Use whenever a page, blog post, or report needs a custom diagram or stat row that is NOT live data (for live charts use datasets + data cards; for process flows from data use Mermaid). Works for manual editing, ARI tool flows, and REST API publish scripts. Guarantees the diagram survives TipTap re-serialization and never clips.

Error handling protocol, validation requirements, file header standards, and LLM token budget requirements. Use when writing new services, API endpoints, LLM calls, or when unsure about error handling patterns in this project.

Reference guide for shared component patterns and SOLID OOP design principles used in the Dataspheres AI platform. Use when designing new features, reviewing architecture decisions, or when the user asks "how should I structure this?" or "what's the right pattern for this?"

Manage Faceless AI marketing dataspheres - seed content, create completions, manage newsletters, surveys, and datasets across all public-facing dataspheres. Use when the user wants to create content, seed a datasphere, manage marketing DSes, or work on any Faceless AI datasphere.