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quality-filter-research质量过滤研究

Agent Skill

quality-filter-research 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

13,179

周安装

528

GitHub Stars

公开资料未说明

下载量

4,266
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:quality-filter-research(质量过滤研究)
来源仓库:https://github.com/nomorecoding/quality-filter-research
安装命令:
openclaw skills install quality-filter-research
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install quality-filter-research

简介

学术论文质量过滤代理提供严格的评分系统与审核跟踪机制。

  • 根据相关性与质量标准筛选论文,适用于研究检索场景。
  • 在 OpenClaw 中可通过关键词快速定位候选文献结果。
  • 安装命令为 openclaw skills install quality-filter-research。
  • 建议查阅来源仓库以了解支持的数据库与过滤维度。

SKILL.md

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

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

83.03%
按下载量换算3,542

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

未展示

权限和风险

权限需确认

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安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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