How do I install the Multi Search skill?

Run npx skillmds@latest add baofeng-tech/multi-search-5 in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Multi Search safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Multi Search?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Multi Search free to use?

Yes. Installing skills from SkillMD is free. This skill is licensed under MIT.

Who published Multi Search?

baofeng-tech (@baofeng-tech) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Multi Search by baofeng-tech — Agent Skill

Name: Multi Search
Author: baofeng-tech

Multi Search

Parallel multi-source search combining Web, Scholar, Smart, and Tavily results with confidence scoring and AI synthesis. Best for comprehensive research requiring cross-source validation. Use when: the user needs web search, research, source discovery, or content extraction.

baofeng-tech Updated Sep 21, 2026 1 repo stars

File contents

AIsa Multi-Source Search

The most comprehensive search tool in this plugin. Queries Web, Scholar, Smart, and Tavily sources in parallel, then computes a confidence score based on source availability, result quality, and diversity. Optionally generates an AI synthesis of all results.

Setup

This skill requires the AISA_API_KEY environment variable. When installed as a Claude plugin, the key is configured via the environment variables.

Usage

Run the search client with the verity subcommand:

python3 scripts/search_client.py verity --query "<search query>" --count <results_per_source>

Arguments

Argument	Required	Default	Description
`--query` / `-q`	Yes	—	Search query
`--count` / `-c`	No	5	Maximum results per source (1–20)

Example

python3 scripts/search_client.py verity --query "impact of AI on healthcare diagnostics" --count 5

Output

The script prints:

Individual results from each source (Web, Smart, Scholar, Tavily)
Confidence Assessment with:
- Score (0–100) — Overall confidence in the search results
- Level — Very High / High / Medium / Low / Very Low
- Sources queried and Sources OK — How many sources responded
- Total results — Combined result count across all sources
AI Synthesis — A coherent summary combining insights from all sources, with citations

Confidence Scoring Breakdown

Factor	Weight	Description
Source availability	40%	How many of the 4 sources returned results
Result quality	35%	Ratio of actual results to expected results
Source diversity	15%	Whether both academic and web sources are present
Recency bonus	10%	Bonus for having at least one successful source

When to Use

Use this skill when the user needs the most thorough and reliable search results possible. Best for fact-checking, comprehensive research, verifying claims across multiple sources, or any query where cross-source validation adds significant value. This tool is slower but more reliable than individual search tools.

---name: multi-search-5description: Parallel multi-source search combining Web, Scholar, Smart, and Tavily results with confidence scoring and AI synthesis. Best for comprehensive research requiring cross-source validation. Use when: the user needs web search, research, source discovery, or content extraction.license: MIT---# AIsa Multi-Source SearchThe most comprehensive search tool in this plugin. Queries Web, Scholar, Smart, and Tavily sources in parallel, then computes a confidence score based on source availability, result quality, and diversity. Optionally generates an AI synthesis of all results.## SetupThis skill requires the `AISA_API_KEY` environment variable. When installed as a Claude plugin, the key is configured via the environment variables.## UsageRun the search client with the `verity` subcommand:```bashpython3 scripts/search_client.py verity --query "<search query>" --count <results_per_source>```### Arguments| Argument | Required | Default | Description ||----------|----------|---------|-------------|| `--query` / `-q` | Yes | — | Search query || `--count` / `-c` | No | 5 | Maximum results per source (1–20) |### Example```bashpython3 scripts/search_client.py verity --query "impact of AI on healthcare diagnostics" --count 5```## OutputThe script prints:1. **Individual results** from each source (Web, Smart, Scholar, Tavily)2. **Confidence Assessment** with: - **Score** (0–100) — Overall confidence in the search results - **Level** — Very High / High / Medium / Low / Very Low - **Sources queried** and **Sources OK** — How many sources responded - **Total results** — Combined result count across all sources3. **AI Synthesis** — A coherent summary combining insights from all sources, with citations### Confidence Scoring Breakdown| Factor | Weight | Description ||--------|--------|-------------|| Source availability | 40% | How many of the 4 sources returned results || Result quality | 35% | Ratio of actual results to expected results || Source diversity | 15% | Whether both academic and web sources are present || Recency bonus | 10% | Bonus for having at least one successful source |## When to UseUse this skill when the user needs the most thorough and reliable search results possible. Best for fact-checking, comprehensive research, verifying claims across multiple sources, or any query where cross-source validation adds significant value. This tool is slower but more reliable than individual search tools.

Frequently asked questions