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Researching Web

Search the web using Perplexity AI. Use when needing to search, look up, research, find current information, best practices, compare technologies, or answer factual questions about tools and libraries.

Data, AI & Research|v1|Updated 7/14/2026|GitHub source
MCP get_skill({ skillId: "researching-web-c0a18a2d" })

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# Web Research with Perplexity

Use `mcp__perplexity-ask__perplexity_ask` for web search.

## When to Use

- Best practices and recommendations
- Current information (releases, news)
- Comparisons between technologies
- Factual questions about tools/libraries

## Usage

```json
{
  "messages": [{ "role": "user", "content": "Your research question" }]
}
```

## Tips

- Be specific: "Go error handling best practices 2024"
- Include context: "Redis vs Memcached for session storage"
- Ask comparisons: "Pros and cons of gRPC vs REST"

---

## Gotchas

- **Search quality varies by phrasing** — "X best practices" returns curated guides; "X mistakes" returns blog rants. Same intent, very different results.
- **Multi-source synthesis** doesn't auto-detect contradictions — facts from sources A and B may directly contradict; the skill doesn't flag this.
- **Date filtering ("last year") is unreliable** — search engines may include cached older content that was indexed recently.
- **Rate limits on the underlying search API silently truncate results** — a "no results" finding may actually be a quota issue.
- **Geo-targeting**: same query from different IPs returns different results — VPN switches mid-research produce inconsistent corpus.
- **NOT FOR official API/library reference** — for those use `looking-up-docs` (Context7); this skill is for trends, comparisons, news.
#broad-capability#devops#azure#kubernetes#productivity#web#searchperplexity

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