Menu
Use when completed Brandmint outputs should be published into NotebookLM and turned into NotebookLM artifacts.
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
Based on SOC occupation classification
| name | notebooklm-publisher |
| description | Use when completed Brandmint outputs should be published into NotebookLM and turned into NotebookLM artifacts. |
Wave: 7 (Publishing) Type: Post-hook (no text skills or visual assets) Depends on: Wave 6 (all brand outputs complete)
Transforms all brandmint pipeline outputs into a Google NotebookLM notebook and generates 5 branded artifacts:
| Artifact | Type | Format | Est. Time |
|---|---|---|---|
| Brand Overview Deck | slide-deck | 5-15 min | |
| Product Showcase Deck | slide-deck | 5-15 min | |
| Audio Overview | audio | MP3 | 10-20 min |
| Brand Report | report | Markdown | 5-15 min |
| Mind Map | mind-map | JSON | <1 min |
Source Building: Reads .brandmint/outputs/*.json (16 skill outputs) and
brand-config.yaml, converts them into 5 structured markdown documents
optimised for NotebookLM processing
Notebook Creation: Creates a "{Brand} — Brand Intelligence" notebook in NotebookLM and uploads the 5 source documents
Artifact Generation: Generates artifacts with brand-specific instructions that inject colours, typography, voice/tone, and positioning data
Parallel Execution: Mind map first (instant), then decks + report in parallel (3 workers), then audio (sequential). Total ~25 min wall time.
Download: All artifacts downloaded to deliverables/notebooklm/artifacts/
pip install notebooklm-py # or: pip install 'brandmint[publishing]'
notebooklm login # Google OAuth — opens browser
bm launch --config brand-config.yaml --waves 1-7
bm publish notebooklm --config brand-config.yaml
bm publish notebooklm --config brand-config.yaml --dry-run
bm publish notebooklm --config brand-config.yaml --artifacts audio-overview,mind-map
bm publish notebooklm --config brand-config.yaml --force
<brand-dir>/
deliverables/
notebooklm/
sources/
brand-foundation.md
brand-strategy.md
campaign-content.md
communications-social.md
visual-asset-catalog.md
artifacts/
brand-overview-deck.pdf
product-showcase-deck.pdf
brand-audio-overview.mp3
brand-report.md
brand-mind-map.json
publish-report.json
State is persisted at .brandmint/notebooklm-state.json. Re-running the
command skips already-completed steps (sources already indexed, artifacts
already downloaded). Use --force to start fresh.
| Document | Skills | Purpose |
|---|---|---|
| Brand Foundation | niche-validator, buyer-persona, competitor-analysis + config | Market, audience, brand definition |
| Brand Strategy | positioning, MDS, voice-and-tone, product description, visual identity | Strategy and identity |
| Campaign Content | campaign copy, video script, ads, press release | Marketing creative |
| Communications & Social | email sequences, social calendar, hooks, influencer, reviews | Comms and distribution |
| Visual Asset Catalog | Generated asset inventory | Visual system reference |
End-to-end brand identity orchestration system. Generates text strategy, visual assets, campaign copy, video deliverables, and publishing outputs using 44 specialized skills across 9 categories. Chains FAL.AI/Nano Banana/Flux visual generation with brand positioning, buyer personas, and campaign workflows via wave-based execution. Includes Remotion-based programmatic video generation.
Transform markdown documentation folders into professional Astro-based wikis using refero-design principles (research-first, anti-AI-slop: no default emojis, no 3-column layouts, sections + dividers + media blocks over cards, neutral color system). Use when the user has a folder of .md files and wants to generate a polished wiki/documentation site with dark/light mode support, readable typography, and professional aesthetics. Triggers on requests involving markdown-to-wiki conversion, documentation site generation, Astro wiki creation, or brand wiki themes.
Defines brand voice persona and tone calibration using persona and positioning data to produce a reusable meta-prompt for copywriting.
Generate images with Alibaba Qwen-Image-2.0-Pro via inference.sh CLI. Professional text rendering, fine-grained realism, enhanced semantic adherence. Ideal for posters, banners, and text-heavy designs. Triggers: qwen image pro, qwen-image-pro, qwen 2 pro, alibaba image pro, dashscope pro, professional text rendering
Generate and edit images with Alibaba Qwen-Image-2.0 models via inference.sh CLI. Models: Qwen-Image-2.0 (fast), Qwen-Image-2.0-Pro (professional text rendering). Capabilities: text-to-image, multi-image editing, complex text rendering. Triggers: qwen image, qwen-image, alibaba image, dashscope image, qwen image 2, qwen image pro
Batteries-included agent component for React/Next.js from ui.inference.sh. One component with runtime, tools, streaming, approvals, and widgets built in. Capabilities: drop-in agent, human-in-the-loop, client-side tools, form filling. Use for: building AI chat interfaces, agentic UIs, SaaS copilots, assistants. Triggers: agent component, agent ui, chat agent, shadcn agent, react agent, agentic ui, ai assistant ui, copilot ui, inference ui, human in the loop