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Research Paper Quality Filter

作者 nomorecoding · GitHub ↗ · v1.0.0
cross-platform ⚠ suspicious
420
总下载
0
收藏
2
当前安装
1
版本数
在 OpenClaw 中安装
/install quality-filter-research
功能描述
Academic paper quality filtering agent with rigorous scoring system and comprehensive audit trail. Filters papers based on relevance and quality criteria for...
安全使用建议
This skill is not obviously malicious, but I recommend caution before installing or running it: 1) Confirm scope — the criteria and examples are strongly music-generation–focused despite a generic description; if you expect a general-purpose filter, ask the author for clarification. 2) Expect local data retention — the skill requires writing audit logs and preserving full filtered papers under research/{domain}/…; ensure you are comfortable storing possibly copyrighted or sensitive papers and that storage location is acceptable. 3) There is no provided binary or script despite example CLI commands; decide whether you or your agent will implement the functionality or if the package should include executable code. 4) Metadata mismatch: the registry ownerId differs from _meta.json ownerId/slug — ask the publisher to confirm provenance. 5) If you still want to try it, run it in a restricted/sandbox environment first, inspect any logs created, and limit access to sensitive data. Additional information that would raise or lower concern: presence of network endpoints, included scripts or downloads, or requests for credentials would raise the risk; a provided, signed implementation and consistent metadata would lower it.
功能分析
Type: OpenClaw Skill Name: quality-filter-research Version: 1.0.0 The skill bundle describes an academic paper quality filtering agent. All files (SKILL.md, README.md, _meta.json) consistently describe the skill's purpose, capabilities, and output. The primary security-relevant action is local file storage for logging (`research/{domain}/quality_filtering/quality_filtering_log.md`). While the `{domain}` variable in the path could be a vector for path traversal if the agent's execution environment does not sanitize inputs, the skill itself does not instruct the agent to perform any malicious actions, exploit vulnerabilities, exfiltrate data, or engage in prompt injection. The file writing is explicitly for logging, which is a stated and transparent purpose of the skill.
能力评估
Purpose & Capability
The top-level description claims a general 'academic paper quality filter' but the scoring criteria and examples are narrowly focused on 'music/song/audio generation'. The SKILL.md shows example CLI usage (quality_filter ...) even though this is an instruction-only package with no binaries or scripts provided. These mismatches suggest the skill may be tailored to a narrow domain or is incomplete.
Instruction Scope
Instructions stay within filtering and logging: ingest papers (arXiv), score them, and append results to a local audit log. However the skill explicitly requires preserving filtered papers (i.e., storing full paper content) and writing append-mode logs under research/{domain}/quality_filtering/..., which can retain potentially sensitive or copyrighted documents. SKILL.md does not instruct reading unrelated system files or env vars.
Install Mechanism
This is an instruction-only skill with no install spec or code files, so nothing will be downloaded or written by an installer. That reduces supply-chain risk, but also means the instructions expect the agent or user to implement the CLI behavior themselves.
Credentials
No environment variables, credentials, or external endpoints are requested. The only resource access implied is local filesystem write access to create the research/{domain}/... directory tree, which is proportionate to the stated audit/logging purpose.
Persistence & Privilege
The skill does not request persistent platform privileges (always:false). Its main persistent behavior is writing append-mode logs and preserving filtered papers in a local directory, which is consistent with the audit-trail claim but should be considered by the user for privacy/storage policy reasons.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install quality-filter-research
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /quality-filter-research 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
Systematic quality filtering with scoring system and audit trail
元数据
Slug quality-filter-research
版本 1.0.0
许可证
累计安装 2
当前安装数 2
历史版本数 1
常见问题

Research Paper Quality Filter 是什么?

Academic paper quality filtering agent with rigorous scoring system and comprehensive audit trail. Filters papers based on relevance and quality criteria for... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 420 次。

如何安装 Research Paper Quality Filter?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install quality-filter-research」即可一键安装,无需额外配置。

Research Paper Quality Filter 是免费的吗?

是的,Research Paper Quality Filter 完全免费(开源免费),可自由下载、安装和使用。

Research Paper Quality Filter 支持哪些平台?

Research Paper Quality Filter 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Research Paper Quality Filter?

由 nomorecoding(@nomorecoding)开发并维护,当前版本 v1.0.0。

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