Perform AI-powered web searches with real-time information using Perplexity models via LiteLLM and OpenRouter. This skill should be used when conducting web searches for current information, finding recent scientific literature, getting grounded answers with source citations, or accessing information beyond the model knowledge cutoff. Provides access to multiple Perplexity models including Sonar Pro, Sonar Pro Search (advanced agentic search), and Sonar Reasoning Pro through a single OpenRouter API key.
64
77%
Does it follow best practices?
Run evals on this skill
Adds up to 20 points to the overall score
View guide
High
Do not use without reviewing
Fix and improve this skill with Tessl
tessl review fix ./skills/literature/perplexity-search/SKILL.mdSecurity
1 high severity finding. You should review these findings carefully before considering using this skill.
The skill handles credentials insecurely by requiring the agent to include secret values verbatim in its generated output. This exposes credentials in the agent’s context and conversation history, creating a risk of data exfiltration.
The skill includes examples that place an OpenRouter API key verbatim into shell commands and a setup script flag (export OPENROUTER_API_KEY='sk-or-v1-your-key-here' and python scripts/setup_env.py --api-key ...), which requires including secret values directly in generated commands/outputs and thus poses an exfiltration risk.
Low
Low-risk findings.
1 low severity finding. Worth noting, but not necessarily harmful.
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
Perplexity Search’s required runtime workflow ingests user-authored free-text queries to perform “real-time web search,” which can then retrieve and include outsider-authored web page content in the model prompt/grounding (via Perplexity search through LiteLLM/OpenRouter).
df37802
If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.