A professional-grade academic retrieval skill for discovering scholarly papers, verifying citations, and automating literature review workflows.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install searchapi-scholar-search
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 searchapi-scholar-search 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 SearchAPI Scholar Search?
SearchAPI Scholar Search is a specialized toolset designed for high-precision academic discovery and evidence-based web searching. By leveraging SerpApi and SearchAPI compatible engines, this skill enables AI agents to move beyond general web results and tap into structured scholarly data. It is an essential component for any researcher or developer using Openclaw Skills who needs to build robust literature pools, verify paper metadata, or track citation signals across millions of academic records.
The skill provides deep integration for academic workflows, offering specific modes for shortlisting relevant reading, identifying systematic reviews, and verifying the authenticity of DOIs and publication venues. Whether you are conducting a formal thesis review or validating technical claims, this skill ensures your AI agent has access to the most authoritative sources available in the academic ecosystem.
SearchAPI Scholar Search Use Cases
- Building comprehensive literature pools for theses, grant applications, or research proposals.
- Verifying the existence and details of specific academic papers using titles or DOI strings.
- Identifying highly cited or classic works within a specific scientific domain.
- Finding official publisher landing pages, institutional repositories, and open-access PDF sources.
- Discovering recent trends by filtering academic results by specific publication years.
How SearchAPI Scholar Search Works
- The agent initiates a request using the scholar-search.mjs script with a defined query and optional parameters like year ranges.
- The skill interfaces with SerpApi or SearchAPI to fetch structured data from academic databases.
- Results are processed through specialized modes such as review or verify to filter for specific document types or metadata accuracy.
- The system enriches results with DOI information by cross-referencing public APIs like Crossref when necessary.
- A structured output is returned containing titles, authors, citation counts, and verification links for downstream processing.
SearchAPI Scholar Search Setup
To integrate this into your Openclaw Skills environment, ensure you have Node.js installed and set your API keys as environment variables:
# Set your preferred API key
export SERPAPI_API_KEY="your_key_here"
# Or alternatively
export SEARCHAPI_API_KEY="your_key_here"
# Run a basic scholar search
node scripts/scholar-search.mjs "machine learning in healthcare" -n 5
SearchAPI Scholar Search Data Schema & Taxonomy
The skill returns a structured data object optimized for research automation:
| Field | Description |
|---|---|
| title | The full academic title of the paper |
| authors | List of contributing researchers |
| year | Publication year |
| cited_by | Total citation count as an influence signal |
| doi | Digital Object Identifier (enriched via Crossref if needed) |
| paper_type | Heuristic classification (e.g., primary-study, review) |
| verification_link | Direct URL to the publisher or repository page |
SearchAPI Scholar Search Advanced Features
- Multi-mode execution: Toggle between shortlist, review, and verify modes to change search heuristics.
- DOI Enrichment: Automatic background querying of the Crossref API to find missing persistent identifiers.
- Evidence-Oriented Web Search: A secondary web search script specifically tuned to find supporting evidence and repository links.
- Heuristic Detection: Built-in patterns to identify systematic reviews and survey papers for faster literature mapping.
- Structured JSON Output: Native support for --json flags to facilitate seamless multi-agent support and data piping.
SKILL.md
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