A professional-grade research assistant skill that integrates the Perplexity Agent API for deep web searching and high-effort reasoning.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install perplexity-research
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install perplexity-research using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Perplexity Research?
The Perplexity Research skill is a robust integration designed for developers who need their AI agents to move beyond static training data. By leveraging the Perplexity Agent API, this skill allows agents to browse the live web, synthesize current events, and perform complex reasoning tasks with high effort. It serves as a critical component of the Openclaw Skills library for tasks requiring factual accuracy and deep analytical depth.
Built with flexibility in mind, the skill supports multiple industry-leading models including GPT-5.2, Claude 3.5 Sonnet, and Gemini 2.0 Flash. It provides a standardized Python client and CLI interface to handle everything from quick web lookups to exhaustive market analysis, complete with transparent cost tracking and streaming capabilities for a seamless developer experience.
Perplexity Research Use Cases
- Conducting deep market research and trend analysis using real-time web data.
- Performing investment research by analyzing recent earnings reports and financial news.
- Validating critical information by comparing answers across different LLM providers.
- Generating long-form reports with high-reasoning effort for complex technical topics.
- Building autonomous agents that require multi-turn research capabilities with context retention.
How Perplexity Research Works
- The user or agent initiates a request through the PerplexityClient, specifying the query and desired reasoning depth.
- The skill triggers a web search via the Perplexity Agent API to gather the most current information available online.
- Collected data is processed through high-effort reasoning models to synthesize a comprehensive answer.
- For critical tasks, the skill can execute the query across multiple models simultaneously to compare outputs and ensure data integrity.
- Results are returned with full metadata, including token usage and cost calculations, allowing for precise resource management within Openclaw Skills workflows.
Perplexity Research Setup
To get started with this skill, you must configure your API credentials:
# Export your API key directly to your environment
export PERPLEXITY_API_KEY='your_api_key_here'
# Or, create a .env file in the skill's scripts directory
echo "PERPLEXITY_API_KEY=your_api_key_here" > scripts/.env
You can then run a test search via the CLI:
python scripts/perplexity_client.py search "latest updates in Openclaw Skills"
Perplexity Research Data Schema & Taxonomy
The skill returns a structured dictionary for every research task. Below is the metadata taxonomy used:
| Key | Type | Description |
|---|---|---|
answer |
string | The primary synthesized response from the research agent. |
tokens |
integer | The total number of tokens used in the request and response. |
cost |
float | The calculated cost of the request in USD. |
model |
string | The identifier of the specific model used for the query. |
error |
string | Optional field containing error details if the request fails. |
Perplexity Research Advanced Features
- Multi-model comparison allows users to benchmark GPT-5.2 against Claude and Gemini for the same query.
- Granular reasoning effort levels (low, medium, high) to balance between speed and analytical depth.
- Real-time streaming support to handle lengthy, complex analysis without UI timeouts.
- Built-in cost optimization features including max_token constraints and search-only modes.
- Support for multi-turn conversations to build deep context over sequential research queries.
SKILL.md
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