A sophisticated search orchestration skill that combines multiple search engines with automated fallback logic and cross-verification to ensure high-confidence data retrieval.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install multi-search-fallback
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install multi-search-fallback using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Multi-Search Fallback Skill?
Multi-Search Fallback is a robust information retrieval layer designed for high-stakes research and automated data gathering. By integrating multiple search providers into a single workflow, it ensures that your AI agent remains resilient against API failures, rate limits, or poor search results. This skill is a core component for users leveraging Openclaw Skills who require verifiable, multi-perspective data without manually querying different engines. It transforms simple search queries into comprehensive research tasks by automatically deciding whether to use a quick single-source check or a deep, multi-source investigation.
Multi-Search Fallback Skill Use Cases
- Performing deep industry analysis by synthesizing data from global and domestic Chinese search engines.
- Fact-checking controversial or complex claims through automated cross-source verification.
- Building high-availability AI workflows where search uptime is critical and requires redundant engine support.
- Conducting academic research that requires parallel querying of specialized deep-research tools and general web indices.
How Multi-Search Fallback Skill Works
- Query Analysis: The skill determines the intent, classifying the request as a simple fact, complex research, academic query, or financial search.
- Prioritized Execution: It triggers a sequential fallback chain, starting with high-speed providers (like Brave or Google) and cascading to secondary engines (DuckDuckGo, Tavily) if primary sources fail or return empty results.
- Cross-Verification: When multiple sources are utilized, the skill compares findings to calculate a confidence score, tagging results as consistent, conflicting, or supplementary.
- Structured Synthesis: The final output is aggregated into a report featuring a confidence rating, a comparison matrix of all sources, and collapsible raw data for full transparency.
Multi-Search Fallback Skill Setup
To deploy this skill within the Openclaw Skills framework, ensure your environment is configured with the necessary search tool bindings:
# Register the multi-search-fallback skill
openclaw skill add multi-search-fallback
# Configure optional API keys for enhanced providers like Tavily
export TAVILY_API_KEY='your_api_key_here'
Multi-Search Fallback Skill Data Schema & Taxonomy
The skill produces a structured data object optimized for further agent processing or human review:
| Component | Format | Description |
|---|---|---|
| Confidence Score | Percentage | Calculated based on the ratio of consistent findings across all sources. |
| Source Matrix | Markdown Table | Maps each search provider to its specific findings and verification status. |
| Findings List | Unordered List | Synthesized facts sorted by their level of source agreement. |
| Verification Tags | Enum | Labels such as Consistent, Conflict, or Supplement for each data point. |
| Raw Metadata | JSON/Text | Collapsible sections containing original snippets and URLs from each engine. |
Multi-Search Fallback Skill Advanced Features
- Context-Aware Routing: Automatically selects openclaw-skill-search-web for queries involving domestic Chinese policies or companies.
- Parallel Sub-tasking: Uses sessions_spawn to execute multiple searches simultaneously for deep research tasks, significantly reducing total latency.
- Automated Conflict Resolution: Identifies and highlights discrepancies between search engines instead of presenting a single, potentially biased viewpoint.
- Custom Timeout Management: Configurable search windows per engine (ranging from 15s to 60s) to balance speed and depth.
SKILL.md
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