When does Claude decide to use Perplexity?

Claude automatically triggers the tool when it encounters unfamiliar technologies, reaches a decision point between multiple libraries, or needs to explain complex, evolving concepts.

Is it expensive to run in terms of tokens?

The skill utilizes a subagent pattern with Claude Haiku to perform the search and summarization, which significantly reduces the token cost compared to using higher-tier models.

What is the Perplexity Context Search skill?

It is a specialized Claude Code capability that allows the assistant to perform real-time web searches using Perplexity AI to provide current information and personalized context.

Does this skill remember my coding preferences?

Yes, it integrates with a local user profile to understand your expertise level and stylistic preferences, ensuring search results are relevant to your specific workflow.

What do I need to use this skill?

You need a Perplexity API key and the brain-jar MCP server configured in your Claude Code environment.

Perplexity Context Search

Name: Perplexity Context Search
Author: designnotdrum

bydesignnotdrum

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Learning & Documentation

Empowers Claude with real-time web search and personalized context enrichment using the Perplexity API.

About

This skill integrates Perplexity AI directly into your Claude Code workflow, allowing the assistant to research unfamiliar technologies, compare architectural patterns, and provide contextually aware answers based on your personal preferences. By leveraging a subagent pattern with Haiku, it efficiently retrieves up-to-date documentation and community discussions, ensuring you always have access to information beyond Claude's training data while maintaining your specific project constraints and learning level.

Key Features

Efficient subagent pattern using Claude Haiku to minimize primary model token usage.
Detailed citations for all findings to ensure transparency and source verification.
Real-time web search for the latest documentation and API updates.
1 GitHub stars
Personalized context enrichment using a local user profile for tailored answers.
Automatic identification of decision points like library comparisons and pattern choices.

Use Cases

Learning a new framework or library released after Claude's last training data cutoff.
Comparing multiple architectural approaches (e.g., SQL vs NoSQL) based on specific project needs.
Getting technical explanations that match your specific expertise level and coding style preferences.

About

Key Features

Efficient subagent pattern using Claude Haiku to minimize primary model token usage.
Detailed citations for all findings to ensure transparency and source verification.
Real-time web search for the latest documentation and API updates.
1 GitHub stars
Personalized context enrichment using a local user profile for tailored answers.
Automatic identification of decision points like library comparisons and pattern choices.

Use Cases

Learning a new framework or library released after Claude's last training data cutoff.
Comparing multiple architectural approaches (e.g., SQL vs NoSQL) based on specific project needs.
Getting technical explanations that match your specific expertise level and coding style preferences.