A systematic academic paper filtering agent that uses a rigorous scoring system and audit trails to streamline research workflows.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install quality-filter-research
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 quality-filter-research 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 Quality Filter?
The Quality Filter is a specialized agent designed to handle the heavy lifting of academic literature review. By integrating this tool from the Openclaw Skills collection into your research pipeline, you can automatically evaluate papers based on relevance and technical rigor. It provides a structured way to separate high-impact research from noise, ensuring that only the most pertinent studies make it to your reading list.
This skill is particularly valuable for researchers dealing with high-volume arXiv feeds. It does not just filter; it documents every decision in a comprehensive audit trail, allowing for manual recall and verification. By utilizing Openclaw Skills like this one, developers and academics can maintain high standards of experimental rigor without manually screening hundreds of titles and abstracts.
Quality Filter Use Cases
- Automated screening of daily arXiv paper alerts for specific research domains.
- Systematic literature reviews requiring documented inclusion and exclusion criteria.
- High-volume research triage where manual review is time-prohibitive.
- Creating a searchable audit trail of filtered academic papers for team collaboration.
How Quality Filter Works
- The agent receives a raw list of academic papers, typically sourced from an arXiv search or similar database.
- It applies a dual-metric scoring system, evaluating relevance based on title/abstract keywords and assessing technical quality.
- A decision logic is applied where papers meeting the threshold are marked as passed while others are categorized for manual recall.
- Detailed results, including the score breakdown and rationale, are appended to a local markdown log file.
- The final output organizes these results into a directory structure for easy access and review.
Quality Filter Setup
To use this tool within the Openclaw Skills ecosystem, ensure your environment is configured for research workflows. Run the following command to process your paper lists:
# Filter music generation papers with specific domain context
quality_filter --domain "music_generation" --papers "[paper_list]" --date "2026-02-28"
You can also adjust the threshold for different levels of strictness:
# Apply a custom threshold for broader audio research
quality_filter --domain "speech_audio" --threshold 5 --papers "[paper_list]"
Quality Filter Data Schema & Taxonomy
The skill organizes data in a structured directory format, primarily focusing on maintaining a persistent log of all filtering sessions.
| Component | Detail |
|---|---|
| Storage Path | research/{domain}/quality_filtering/ |
| File Name | quality_filtering_log.md (Append Mode) |
| Session Metadata | Includes date, domain, and search parameters used. |
| Paper Metrics | Title, authors, score breakdown (relevance + quality), and decision. |
| Statistics | Summary counts for pass/fail distribution per session. |
Quality Filter Advanced Features
- Strong relevance override to prevent high-value papers from being filtered out due to strict scoring.
- Comprehensive audit trail preservation for all filtering decisions including timestamps.
- Automatic directory structure management for scalable research organization.
- Manual recall support that preserves filtered papers for human review to ensure no critical research is lost.
SKILL.md
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