Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
What This Skill Does
Queries web, academic, and Tavily sources in parallel and synthesizes results into a confidence-scored answer. Uses a two-phase approach: parallel retrieval followed by meta-analysis via AIsa Explain. Each response includes a score from 0 to 100 based on source quality, cross-source agreement, recency, and relevance.
Combining web, academic, and external validation sources in one API call with deterministic confidence scoring removes the need to manually reconcile results from separate search tools.
When to use it
- Finding recent academic papers on a topic with year range filters
- Aggregating web coverage of an industry event or funding round
- Comparing reviews and benchmarks across competing frameworks
- Verifying a technical claim across multiple source types before citing it
- Crawling and extracting content from a list of competitor URLs
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: Is quantum computing ready for enterprise use?
- 1Sends the query to scholar, web, smart, and Tavily endpoints in parallel
- 2Collects structured results from all four streams
- 3Passes combined results to AIsa Explain for meta-analysis
- 4Calculates a confidence score based on source quality, agreement, recency, and relevance
- 5Returns synthesized answer with citations and the numeric confidence score
A confidence-scored summary (e.g. 72/100) with sourced claims and a synthesis of current consensus across academic and web sources
Requirements
Accounts, API keys, or tools you or your AI assistant may need to set up while using this skill.