360 Secure SkillHub
360 安全技能中心

Research Paper Quality Filter

面向学术论文筛选:依据标题、摘要关键词做相关性评分,并评估实验与基线等技术质量,累计 6/10 分以上通过,明确聚焦音乐/歌曲生成的论文可降分通过;处理结果以追加方式写入本地 quality_filtering_log.md,包含评分明细、通过或过滤分类、汇总统计与人工复核清单。

nomorecoding
nomorecoding
热度 70.92
最近更新 2026-05-11 17:27:50
分类:搜索依赖:代码执行 / 读写文件应用场景:研究 / 数据处理 / 工作流

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add quality-filter-research
Metadata
name
quality_filter
description
Academic paper quality filtering agent with rigorous scoring system and comprehensive audit trail. Filters papers based on relevance and quality criteria for research workflows.
author
Claude (克劳德)
version
1.0.0

Quality Filter Skill

This skill provides systematic quality filtering for academic papers with a rigorous scoring system and complete audit trail for research workflows.

Capabilities

  • Relevance Scoring: Evaluates paper relevance based on title and abstract keywords
  • Quality Assessment: Assesses technical quality and experimental rigor
  • Comprehensive Logging: Maintains detailed records of all filtering decisions
  • Manual Recall Support: Preserves filtered papers for potential human review
  • Local File Storage: Saves all results to organized directory structure

Filtering Criteria

Relevance Scoring (Max 3 points)

  • Strong Match (+3): Title contains "music" or "song" keywords
  • Medium Match (+2): Title contains "audio" + "generation"
  • Weak Match (+1): Title has weak but related keywords
  • Negative Scoring: Abstract verification can subtract points (-1 to -3)

Quality Assessment (Max 3 points)

  • High Quality (+3): Complete experiments, multiple baselines, strong results
  • Medium Quality (+2): Experiments present but limited baseline comparison
  • Low Quality (+1): Limited technical contribution or incomplete evaluation

Pass Threshold

  • Minimum Score: 6/10 points required to pass filtering
  • Strong Relevance Override: Papers with clear "music/song generation" focus may pass with lower scores

Workflow Integration

This skill integrates with the broader research workflow:

  1. Input: Raw paper list from arXiv search
  2. Processing: Applies scoring system to each paper
  3. Output: Categorizes papers as "passed" or "filtered"
  4. Audit Trail: Maintains complete record for manual recall

Output Format

Local File Storage

  • Main Log: research/{domain}/quality_filtering/quality_filtering_log.md
  • Append Mode: All results appended to single comprehensive file
  • Directory Structure: Automatically created if missing

Log Structure

Each filtering session includes:

  • Session Header: Date, domain, search parameters
  • Scoring Standards: Detailed criteria used
  • Individual Paper Results: Title, authors, score breakdown, decision
  • Summary Statistics: Pass/fail counts, score distribution
  • Manual Recall Section: List of filtered papers available for human review

Usage Examples

# Filter music generation papers
quality_filter --domain "music_generation" --papers "[paper_list]" --date "2026-02-28"

# Filter with custom threshold
quality_filter --domain "speech_audio" --threshold 5 --papers "[paper_list]"

Files Created

  • research/{domain}/quality_filtering/quality_filtering_log.md (append mode)
  • Directory structure automatically created if missing

Audit Trail Requirements

All filtering decisions must include:

  • Complete score breakdown (relevance + quality components)
  • Clear pass/fail rationale
  • Preservation of filtered papers for manual recall
  • Timestamp and session context