perplexity-search — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited perplexity-search (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
Web search with AI-powered answers, deep research, and chain-of-thought reasoning.
| Model | Purpose |
|---|---|
sonar | Lightweight search with grounding |
sonar-pro | Advanced search for complex queries |
sonar-reasoning-pro | Chain of thought reasoning |
sonar-deep-research | Expert-level exhaustive research |
uv run python scripts/mcp/perplexity_search.py \
--ask "What is the latest version of Python?"uv run python scripts/mcp/perplexity_search.py \
--search "SQLite graph database patterns" \
--max-results 5 \
--recency weekuv run python scripts/mcp/perplexity_search.py \
--research "compare FastAPI vs Django for microservices"uv run python scripts/mcp/perplexity_search.py \
--reason "should I use Neo4j or SQLite for small graph under 10k nodes?"uv run python scripts/mcp/perplexity_search.py \
--deep "state of AI agent observability 2025"| Parameter | Description |
|---|---|
--ask | Quick question with AI answer (sonar) |
--search | Direct web search - ranked results without AI synthesis |
--research | AI-synthesized research (sonar-pro) |
--reason | Chain-of-thought reasoning (sonar-reasoning-pro) |
--deep | Deep comprehensive research (sonar-deep-research) |
| Parameter | Description |
|---|---|
--max-results N | Number of results (1-20, default: 10) |
--recency | Filter: day, week, month, year |
--domains | Limit to specific domains |
| Need | Use | Why |
|---|---|---|
| Quick fact | --ask | Fast, lightweight |
| Find sources | --search | Raw results, no AI overhead |
| Synthesized answer | --research | AI combines multiple sources |
| Complex decision | --reason | Chain-of-thought analysis |
| Comprehensive report | --deep | Exhaustive multi-source research |
# Find recent sources on a topic
uv run python scripts/mcp/perplexity_search.py \
--search "OpenTelemetry AI agent tracing" \
--recency month --max-results 5
# Get AI synthesis
uv run python scripts/mcp/perplexity_search.py \
--research "best practices for AI agent logging 2025"
# Make a decision
uv run python scripts/mcp/perplexity_search.py \
--reason "microservices vs monolith for startup MVP"
# Deep dive
uv run python scripts/mcp/perplexity_search.py \
--deep "comprehensive guide to building feedback loops for autonomous agents"Requires PERPLEXITY_API_KEY in environment or ~/.claude/.env.
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.