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Documentation Index

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Portal Agent includes a built-in web research capability. When you ask it to look something up, find references, or build a research board, it searches the web, fetches content from the results, and places everything on your canvas as cards — complete with source citations. You never leave the workspace to do research.

How web search works

When you ask the agent to research a topic, it runs a web search and fetches content from the top results. For each result, it extracts the title, a summary snippet, and the source URL. The agent then places each result on the canvas as a card showing the title, snippet, source domain, and a link back to the original article. The agent can fetch up to 10 results per search query. By default it retrieves 5.
1

Ask the agent to research a topic

Type a research request in the agent chat. You can be as specific or broad as you like — the agent will form its own search query.
Research the latest developments in quantum computing and add cards for each major finding
2

The agent searches and fetches content

The agent calls web_search with a tailored query. You will see the tool call appear in the chat as the agent works. It fetches titles, snippets, and source URLs from multiple results simultaneously.
3

Results appear on the canvas as citation cards

Each result becomes an article card on your canvas showing the headline, a brief summary, and the source domain. Cards link back to the original URL so you can open the full article at any time.

web_search tool parameters

ParameterTypeRequiredDescription
querystringYesThe search query to execute
numResultsnumberNoNumber of results to fetch (default: 5, max: 10)

create_article_card tool parameters

The agent creates one card per result using create_article_card:
ParameterTypeRequiredDescription
titlestringYesArticle headline
snippetstringYesSummary text
urlstringYesSource URL
thumbnailstringNoOptional thumbnail image URL
xnumberNoOptional world-space X placement
ynumberNoOptional world-space Y placement
Portal Agent can find real images from the web and add them to your canvas. Use image search when you need visual references, moodboard assets, or design inspiration. The image_search tool searches multiple sources and falls back automatically if one service is unavailable or throttled.
ParameterTypeRequiredDescription
querystringYesWhat to search for
maxResultsnumberNoMaximum images to return (default: 8, max: 12)
image_search finds existing images on the web. To generate a new AI image, use generate_image instead.

Example image search prompts

Find 8 images of minimalist interior design for a moodboard
Search for inspiration images for a dark-mode mobile app UI
Get reference images of mid-century modern furniture
The agent can search YouTube and add video result cards to the canvas using youtube_search and create_youtube_result_card.
ParameterTypeRequiredDescription
querystringYesSearch terms for YouTube
maxResultsnumberNoNumber of results (default: 3, max: 6)
Video cards show the title, channel name, duration, and thumbnail — and link directly to the YouTube URL.
Find three YouTube tutorials on Figma auto-layout and add them to the canvas

Research workflow example

The agent can combine web search, image search, and card creation into a single multi-step workflow from one prompt.
Research sustainable architecture and create a moodboard with key article summaries and reference images
The agent will:
  1. Call web_search to find articles on sustainable architecture
  2. Call image_search to find visual references
  3. Create article cards for each result with citations
  4. Place image cards alongside the article cards
  5. Arrange everything into a coherent layout
Search for the top 5 AI tools released in 2025, summarize each one, and organize them into a comparison board
Build a competitive analysis board for project management apps — find articles, screenshots, and key data points

Combining search results with applets

After running a web search, you can ask the agent to visualize the data it found as an interactive applet.
Search for the latest smartphone market share data, then build a pie chart applet with the actual numbers
The agent will search first, extract the data from the results, then pass it to create_applet to build the visualization — no manual data entry needed.
Portals is currently in early access (v0.8.0-alpha). Web search and image search are subject to rate limits shared across all users. If results are slow or incomplete, the service is automatically falling back to alternative sources.