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web-search-rag-quick

Perform fast, lean web research with concise citations.

Skill by derricka-lau

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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/derricka-lau-web-search-rag-quick

Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.

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About

Perform fast, lean web research with concise citations. Use only when the user explicitly invokes web-search-rag-quick or explicitly requests a quick web lookup.

Use cases: ml, research

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What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

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  • codeload.github.com · found in install command

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  • ~/.claude/skills/web-search-rag-quick

What's inside

Skill name
web-search-rag-quick
Description
Perform fast, lean web research with concise citations. Use only when the user explicitly invokes web-search-rag-quick or explicitly requests a quick web lookup.
License
MIT
Instructions
44 lines in SKILL.md · view on GitHub

Files (1)

  • SKILL.md

SKILL.md (first lines)

# Web Search RAG — Always Search, Always Cite (Quick Mode)

## Why this skill exists

The user wants every response grounded in fresh web information. This is the **fast variant** — search on every message without exception, cite what you find, but keep the research tight and efficient. One or two well-chosen searches, not a deep investigation.

## Core rules

1. **Always search first.** No message gets a response without at least one `web_search` call. No exceptions — greetings, follow-ups, code questions, everything.
2. **Cite every factual claim.** Use the system's built-in citation tags (`antml:cite`) when search indices are available. Fall back to markdown links `([Source](URL))` for `web_fetch` sources.
3. **Keep it lean.** 1–2 searches for simple queries. 2–3 for moderate ones. Only go beyond 3 if the question genuinely demands it. Skip `web_fetch` unless a snippet is too vague to cite confidently.

## Recency enforcement

Fresh results don't happen by accident — you must actively force them:

- **Append the current year** to any query about an evolving topic. `"CakePHP authentication 2026"` not `"CakePHP authentication"`.
- **Use recency terms** for fast-moving topics: `"latest"`, `"new"`, `"updated"`, `"March 2026"`.
- **Check publication dates** on results. If the top results are 6+ months old on a current topic, immediately re-search with a year or date qualifier — this counts as your second search, not a waste.
- **Prefer recent over old** when two sources have similar authority. A 2026 blog post from a core maintainer beats a 2023 official doc if the API has changed.

Example: `"Python 3.13 new features 2026"` not `"Python new features"`. `"NHS diabetes guidelines latest update"` not `"NHS diabetes guidelines"`.

## Search guidance by query type

**Factual questions:** One targeted search with the current year if relevant, cite the best result. A second search only if the first didn't surface a strong primary source or results are stale.

**Technical / code:** One search for official docs with version or year qualifier. Cite it, then write your response.

**News / current events:** One search for the event with date terms. If the top results are hours old, one more to check for updates.

**Opinions / recommendations:** One search for expert reviews or comparisons, preferring recent results. Synthesise briefly.

**Greetings / trivial messages:** One search for a trending topic or "today in history" fact. Mention it briefly and naturally — don't force it.

## Citation rules

Place citations inline, right after the claim they support. Prefer authoritative sources (official docs, major outlets, government data) over blogs and forums. If you can't source a claim, mark it: *(unsourced — general knowledge)*.

## What not to do

Don't run 5+ searches for a simple factual question. Don't `web_fetch` every result. Don't write a research report when the user asked a yes/no question. Match your response depth to the question's complexity — but always search first.

From derricka-lau/ai-agent-contract, MIT.

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Last commit (this folder)
Jul 21, 2026 (3 months ago)

From GitHub (fetched Oct 24, 2026).

Details

License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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web-search-rag-quick skill. Agent Mart. https://agentmart.dev/skills/derricka-lau-web-search-rag-quick (last updated 2026-10-24)