Skip to main content

​
Overview

Blink lets you talk to Edit Mode and describe the agent you wish you had. For research and web browsing work, the goal is to craft a partner that can scan the web, compare findings, keep track of promising leads, and report back in the style you prefer. This page focuses on the creative side: what capabilities to request, what personality to give your agent, and concrete prompts you can copy and paste to get started quickly.

​
Getting started

  1. Create a new agent directory and run blink init
  2. Start the dev server with blink dev
  3. Press Ctrl+T to toggle to Edit Mode
  4. Describe your research assistant using the ideas below

​
What you can build

Here are examples of what you can ask your research agent to do once you’ve built it. These show the end result: scroll down to see how to build an agent that can handle these requests. 
Do a landscape scan of the top 3 React state management libraries actively
maintained in 2024. For each, include: GitHub stars, last update date, key
differentiator, ideal use case, and major drawbacks. Provide links to
official docs.

Compare Docusaurus vs Mintlify for developer documentation. I'm a startup
with 2 engineers. Focus on: setup time, customization options, cost, and
ongoing maintenance burden. Make a recommendation.

I read that Next.js 14 improved performance by 40% with server actions.
Can you verify this claim? Find the original source and check if other
benchmarks confirm it.

Explain how Vercel's edge runtime works.
Then follow up with:
Can you find some example repos that use edge functions effectively?
And:
What are the main limitations I should know about?

Summarize everything we've discussed about database options for real-time
apps. Format it as a brief I can share with my team on Slack.

​
Building your research agent

Switch to Edit Mode (Ctrl+T) and use these prompts to build your agent. Copy and customize them based on what you want your agent to do.
You don’t need to use all of these prompts. Start with 2-3 that match your needs, test the agent, then add more capabilities as needed.

​
Make it search and gather information

Add a web search tool so the agent can find current information online.
It should search for 5-10 results and extract the full text content,
not just titles and snippets.

​
Make it cite sources properly

Every claim the agent makes should include an inline citation like [1] [2],
with full source details at the end. If I ask for elaboration on a specific
point, it should cite additional sources.

​
Make it compare and analyze

Give the agent the ability to compare multiple sources on the same topic.
It should create a comparison table showing: key claims, level of detail,
recency, and whether sources agree or contradict each other.

​
Make it collaborative and friendly

Give the agent a friendly, collaborative tone. It should act like a
helpful research partner, not a know-it-all. Before diving into research,
it should summarize its research plan and ask if the approach sounds right.

​
Make it verify quality

Add guidance so the agent double-checks any link before sharing it.
It should warn me if a source looks outdated (more than 2 years old),
paywalled, or from a questionable domain. For technical topics, it should
prefer official documentation and established tech blogs.

​
Make it ask clarifying questions

The agent should ask clarifying questions before starting broad searches.
It should confirm: target audience, timeframe (current info vs historical),
desired level of technical depth, and whether I need sources I can share
publicly.

​
Make it track research over time

Add a notes system that persists across messages. For each research topic,
track: key findings, unanswered questions, best sources found so far, and
recommended next actions. Let me ask "show me notes on [topic]" at any time.

​
Make it format reports consistently

When presenting findings, the agent should use this structure:
1) Executive summary (2-3 sentences), 2) Key findings as bullets,
3) Full sources list with titles and URLs, 4) Suggested next steps or
open questions.

​
Make it show confidence levels

The agent should indicate confidence levels for findings: "High confidence"
(3+ agreeing sources), "Medium confidence" (1-2 sources), or "Uncertain"
(conflicting info or single questionable source). Always explain why.

​
Add helpful slash commands

Add slash commands: /summary for quick overview of current research, /sources
to list all references, /questions to see what's still unclear, /export to
format everything as a shareable document.

​
How it works behind the scenes

When you use the prompts above, Edit Mode automatically implements the right tools for your agent. You don’t need to code anything; just describe what you want. Common tools include:
  • Web search - Find current information across the internet
  • Content extraction - Pull full text from URLs and PDFs
  • File operations - Read documents, save research summaries and reports
  • Bash execution - Run scripts to download or process data
Edit Mode handles all the technical implementation. Your job is to describe the agent’s behavior and capabilities.

​
Iterating on your agent

As you test, you’ll discover what works and what needs adjustment. Use these Edit Mode prompts to refine your agent’s behavior: 
The responses are too long. Keep summaries under 200 words and use bullet
points for details. Only include the top 3 most relevant sources unless I
ask for more.

The agent isn't consistently citing sources. Make it mandatory: never make
a factual claim without a citation. If no source exists, say "I couldn't
verify this."

Before searching, the agent should ask me to narrow the scope. For example:
"Should I focus on solutions compatible with TypeScript?" or "Do you want
enterprise or open-source options?"

Prioritize these sources: official documentation, established tech blogs
(like Vercel blog, GitHub blog), recent conference talks, and papers from
known institutions. Avoid: random Medium posts, outdated Stack Overflow
answers, marketing sites.

For technical topics, the agent should read full documentation pages, not
just skim landing pages. It should look for: architecture decisions,
performance characteristics, known issues, and community sentiment.

​
Advanced capabilities

Once your basic agent works well, consider these enhancements: 
Create a research workflow: 1) Initial broad search to identify top options,
2) Deep dive on the top 3 with pros/cons, 3) Fact-check key claims,
4) Generate comparison table, 5) Make recommendation with rationale. Let me
approve or adjust the direction after each step.

Implement a credibility scoring system. Official docs = 10 points, established
tech blogs = 8, GitHub repos with 1k+ stars = 7, recent Stack Overflow answers
= 5, random blogs = 3. Only cite sources scoring 5+. Show scores in citations.

Add a monitoring mode: I should be able to say "track developments in [topic]"
and the agent will periodically search for new information, then notify me of
significant changes or announcements.

Create templates for common research tasks: "framework evaluation", "vendor
comparison", "security audit", "migration planning". Each template should
define the structure, key questions to answer, and required source types.

​
Tips for success

When you’re building:
  • Start with 2-3 capabilities, not all of them
  • Give Edit Mode examples of the output you want to see
  • Make one change at a time, then test it
  • Save prompts that work well for future reference
When you’re ready to scale:
  • Deploy your agent via web or Slack for team access
  • Add persistent memory to track research across sessions
  • Connect to specialized APIs or internal databases
  • Share your agent configuration with teammates
Focus on getting the basic behavior right first. You can always add more sophistication later.
⌘I