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perplexity-search

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

Quality

77%

Does it follow best practices?

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SecuritybySnyk

High

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tessl review fix ./skills/literature/perplexity-search/SKILL.md
SKILL.md
Quality
Evals
Security

Security

1 high severity finding. You should review these findings carefully before considering using this skill.

High

W007: Insecure credential handling detected in skill instructions.

What this means

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.

Why it was flagged

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.

Report incorrect finding

Low

Low-risk findings.

1 low severity finding. Worth noting, but not necessarily harmful.

Low

W011: Third-party content exposure detected (indirect prompt injection risk).

What this means

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.

Why it was flagged

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).

Repository
wu-yc/LabClaw
Audited
Security analysis
Snyk

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