perplexity

Auto-generated skill for perplexity tools via OneKey Gateway.

3,891 stars

Best use case

perplexity is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Auto-generated skill for perplexity tools via OneKey Gateway.

Teams using perplexity should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/perplexity-onekey-gateway/SKILL.md --create-dirs "https://raw.githubusercontent.com/openclaw/skills/main/skills/ai-hub-admin/perplexity-onekey-gateway/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/perplexity-onekey-gateway/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How perplexity Compares

Feature / AgentperplexityStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Auto-generated skill for perplexity tools via OneKey Gateway.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

### OneKey Gateway
Use One Access Key to connect to various commercial APIs. Please visit the [OneKey Gateway Keys](https://www.deepnlp.org/workspace/keys) and read the docs [OneKey MCP Router Doc](https://www.deepnlp.org/doc/onekey_mcp_router) and [OneKey Gateway Doc](https://deepnlp.org/doc/onekey_agent_router).


# perplexity Skill
Use the OneKey Gateway to access tools for this server via a unified access key.
## Quick Start
Set your OneKey access key:
```bash
export DEEPNLP_ONEKEY_ROUTER_ACCESS=YOUR_API_KEY
```
If no key is provided, the scripts fall back to the demo key `BETA_TEST_KEY_MARCH_2026`.
Common settings:
- `unique_id`: `perplexity/perplexity`
- `api_id`: one of the tools listed below
## Tools
### `perplexity_ask`
Answer a question using web-grounded AI (Sonar Pro model). Best for: quick factual questions, summaries, explanations, and general Q&A. Returns a text response with numbered citations. Fastest and cheapest option. Supports filtering by recency (hour/day/week/month/year), domain restrictions, and search context size. For in-depth multi-source research, use perplexity_research instead. For step-by-step reasoning and analysis, use perplexity_reason instead.

Parameters:
- `messages` (array of object, required): Array of conversation messages
- `messages[].role` (string, required): Role of the message sender Values: system, user, assistant
- `messages[].content` (string, required): The content of the message
- `search_recency_filter` (string, optional): Filter search results by recency. Use 'hour' for very recent news, 'day' for today's updates, 'week' for this week, etc. Values: hour, day, week, month, year
- `search_domain_filter` (array of string, optional): Restrict search results to specific domains (e.g., ['wikipedia.org', 'arxiv.org']). Use '-' prefix for exclusion (e.g., ['-reddit.com']).
- `search_context_size` (string, optional): Controls how much web context is retrieved. 'low' (default) is fastest, 'high' provides more comprehensive results. Values: low, medium, high
### `perplexity_research`
Conduct deep, multi-source research on a topic (Sonar Deep Research model). Best for: literature reviews, comprehensive overviews, investigative queries needing many sources. Returns a detailed response with numbered citations. Significantly slower than other tools (30+ seconds). For quick factual questions, use perplexity_ask instead. For logical analysis and reasoning, use perplexity_reason instead.

Parameters:
- `messages` (array of object, required): Array of conversation messages
- `messages[].role` (string, required): Role of the message sender Values: system, user, assistant
- `messages[].content` (string, required): The content of the message
- `strip_thinking` (boolean, optional): If true, removes <think>...</think> tags and their content from the response to save context tokens. Default is false.
- `reasoning_effort` (string, optional): Controls depth of deep research reasoning. Higher values produce more thorough analysis. Values: minimal, low, medium, high
### `perplexity_reason`
Analyze a question using step-by-step reasoning with web grounding (Sonar Reasoning Pro model). Best for: math, logic, comparisons, complex arguments, and tasks requiring chain-of-thought. Returns a reasoned response with numbered citations. Supports filtering by recency (hour/day/week/month/year), domain restrictions, and search context size. For quick factual questions, use perplexity_ask instead. For comprehensive multi-source research, use perplexity_research instead.

Parameters:
- `messages` (array of object, required): Array of conversation messages
- `messages[].role` (string, required): Role of the message sender Values: system, user, assistant
- `messages[].content` (string, required): The content of the message
- `strip_thinking` (boolean, optional): If true, removes <think>...</think> tags and their content from the response to save context tokens. Default is false.
- `search_recency_filter` (string, optional): Filter search results by recency. Use 'hour' for very recent news, 'day' for today's updates, 'week' for this week, etc. Values: hour, day, week, month, year
- `search_domain_filter` (array of string, optional): Restrict search results to specific domains (e.g., ['wikipedia.org', 'arxiv.org']). Use '-' prefix for exclusion (e.g., ['-reddit.com']).
- `search_context_size` (string, optional): Controls how much web context is retrieved. 'low' (default) is fastest, 'high' provides more comprehensive results. Values: low, medium, high
### `perplexity_search`
Search the web and return a ranked list of results with titles, URLs, snippets, and dates. Best for: finding specific URLs, checking recent news, verifying facts, discovering sources. Returns formatted results (title, URL, snippet, date) — no AI synthesis. For AI-generated answers with citations, use perplexity_ask instead.

Parameters:
- `query` (string, required): Search query string
- `max_results` (number, optional): Maximum number of results to return (1-20, default: 10)
- `max_tokens_per_page` (number, optional): Maximum tokens to extract per webpage (default: 1024)
- `country` (string, optional): ISO 3166-1 alpha-2 country code for regional results (e.g., 'US', 'GB')

# Usage
## CLI

### perplexity_ask
```shell
npx onekey agent perplexity/perplexity perplexity_ask '{"question": "Who won the 2024 World Series?"}'
```

### perplexity_research
```shell
npx onekey agent perplexity/perplexity perplexity_research '{"query": "renewable energy policies US"}'
```

### perplexity_reason
```shell
npx onekey agent perplexity/perplexity perplexity_reason '{"topic": "impact of quantum computing"}'
```

### perplexity_search
```shell
npx onekey agent perplexity/perplexity perplexity_search '{"query": "best VR headsets 2026"}'
```

## Scripts
Each tool has a dedicated script in this folder:
- `skills/perplexity/scripts/perplexity_ask.py`
- `skills/perplexity/scripts/perplexity_research.py`
- `skills/perplexity/scripts/perplexity_reason.py`
- `skills/perplexity/scripts/perplexity_search.py`
### Example
```bash
python3 scripts/<tool_name>.py --data '{"key": "value"}'
```

### Related DeepNLP OneKey Gateway Documents
[AI Agent Marketplace](https://www.deepnlp.org/store/ai-agent)    
[Skills Marketplace](https://www.deepnlp.org/store/skills)
[AI Agent A2Z Deployment](https://www.deepnlp.org/workspace/deploy)    
[PH AI Agent A2Z Infra](https://www.producthunt.com/products/ai-agent-a2z)    
[GitHub AI Agent Marketplace](https://github.com/aiagenta2z/ai-agent-marketplace)
## Dependencies

### CLI Dependency
Install onekey-gateway from npm
```
npm install @aiagenta2z/onekey-gateway
```

### Script Dependency
Install the required Python package before running any scripts.

```bash
pip install ai-agent-marketplace
```
Alternatively, install dependencies from the requirements file:

```bash
pip install -r requirements.txt
```
If the package is already installed, skip installation.

### Agent rule
Before executing command lines or running any script in the scripts/ directory, ensure the dependencies are installed.
Use the `onekey` CLI as the preferred method to run the skills.

Related Skills

---

3891
from openclaw/skills

name: article-factory-wechat

Content & Documentation

humanizer

3891
from openclaw/skills

Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.

Content & Documentation

find-skills

3891
from openclaw/skills

Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.

General Utilities

tavily-search

3891
from openclaw/skills

Use Tavily API for real-time web search and content extraction. Use when: user needs real-time web search results, research, or current information from the web. Requires Tavily API key.

Data & Research

baidu-search

3891
from openclaw/skills

Search the web using Baidu AI Search Engine (BDSE). Use for live information, documentation, or research topics.

Data & Research

agent-autonomy-kit

3891
from openclaw/skills

Stop waiting for prompts. Keep working.

Workflow & Productivity

Meeting Prep

3891
from openclaw/skills

Never walk into a meeting unprepared again. Your agent researches all attendees before calendar events—pulling LinkedIn profiles, recent company news, mutual connections, and conversation starters. Generates a briefing doc with talking points, icebreakers, and context so you show up informed and confident. Triggered automatically before meetings or on-demand. Configure research depth, advance timing, and output format. Walking into meetings blind is amateur hour—missed connections, generic small talk, zero leverage. Use when setting up meeting intelligence, researching specific attendees, generating pre-meeting briefs, or automating your prep workflow.

Workflow & Productivity

self-improvement

3891
from openclaw/skills

Captures learnings, errors, and corrections to enable continuous improvement. Use when: (1) A command or operation fails unexpectedly, (2) User corrects Claude ('No, that's wrong...', 'Actually...'), (3) User requests a capability that doesn't exist, (4) An external API or tool fails, (5) Claude realizes its knowledge is outdated or incorrect, (6) A better approach is discovered for a recurring task. Also review learnings before major tasks.

Agent Intelligence & Learning

botlearn-healthcheck

3891
from openclaw/skills

botlearn-healthcheck — BotLearn autonomous health inspector for OpenClaw instances across 5 domains (hardware, config, security, skills, autonomy); triggers on system check, health report, diagnostics, or scheduled heartbeat inspection.

DevOps & Infrastructure

linkedin-cli

3891
from openclaw/skills

A bird-like LinkedIn CLI for searching profiles, checking messages, and summarizing your feed using session cookies.

Content & Documentation

notebooklm

3891
from openclaw/skills

Google NotebookLM 非官方 Python API 的 OpenClaw Skill。支持内容生成(播客、视频、幻灯片、测验、思维导图等)、文档管理和研究自动化。当用户需要使用 NotebookLM 生成音频概述、视频、学习材料或管理知识库时触发。

Data & Research

小红书长图文发布 Skill

3891
from openclaw/skills

## 概述

Content & Documentation