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Agent Skill · 研究检索

paperzilla-research-monitor(Paperzilla 研究监视器)

paperzilla-research-monitor 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。

paperzilla-research-monitor 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;许可证为 MIT-0,第三方扫描已通过,按安装量在研究检索类的 73,674 个 Skill 里排第 16,267。

总安装 7,295周安装 298GitHub Stars 1下载 2,336核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.1.4

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:paperzilla-research-monitor(Paperzilla 研究监视器)
来源仓库:https://github.com/pors/paperzilla-research-monitor
安装命令:
openclaw skills install paperzilla-research-monitor
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 paperzilla-research-monitor

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

使用 pz CLI 监控和讨论 Paperzilla 项目论文。支持最新论文检索、元数据获取和 Markdown 格式。提供研究进展跟踪和团队协作功能。paperzilla-research-monitor 属于研究检索类 Skill,可作为该场景下的辅助能力补充。需要确认 CLI 工具和项目访问权限。

建议了解监控频率和数据更新机制。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install paperzilla-research-monitor;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

paperzilla-research-monitor 怎么安装?

在终端执行 openclaw skills install paperzilla-research-monitor。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

paperzilla-research-monitor 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

paperzilla-research-monitor 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

paperzilla-research-monitor 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

paperzilla-research-monitor 用的人多吗?

公开数据是累计安装 7,295 次,近一周安装 298 次,下载 2,336 次,GitHub 1 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

paperzilla-research-monitor 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
paperzilla-research-monitor

Paperzilla 研究监视器 · 本页

7,2951接触敏感数据MIT-0通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
paperzilla-monitor
description
Monitor and discuss research papers from one Paperzilla project using the pz CLI inside OpenClaw. Use when users want recent papers, metadata, markdown-based summaries, why a paper matters for current work, a recurring weekday brief, or Paperzilla feed triage in chat.
version
1.1.4
homepage
https://docs.paperzilla.ai/guides/cli
license
MIT
allowed-tools
[exec, message]
metadata
skill-author
Paperzilla Inc
openclaw
requires
bins
["pz"]
config
homepage
https://docs.paperzilla.ai/guides/cli

Paperzilla research briefs

Use this skill when the user wants one of these two workflows:

  • on_demand_discussion: discuss the latest papers from one Paperzilla project, inspect one paper, fetch markdown, summarize it, explain why it matters for "our work", and continue the discussion
  • weekday_brief: produce one concise weekday research brief for one Paperzilla project

This is a workflow skill built on top of the same Paperzilla access layer as the core paperzilla skill. It should feel opinionated and repeatable.

Prerequisites

  • Ensure pz CLI is installed and authenticated (pz login already done).
  • Use OpenClaw tools:

- exec for pz commands - message only when the user explicitly asks to deliver a digest/summary to a chat, or when the current profile explicitly requires scheduled external delivery

If pz is missing, run which pz and tell the user setup is required before continuing.

Security model

  • This skill is primarily a Paperzilla read/triage skill.
  • It may use the message tool only for profile-approved delivery behavior or explicit user-requested delivery.
  • It must not send unsolicited or proactive messages outside the profile's delivery rules.
  • It must not read arbitrary system files, unrelated environment variables, or unrelated credentials.
  • It assumes pz is already installed and authenticated by the human via pz login.
  • It assumes OpenClaw messaging is already configured by the host platform. The skill does not acquire, mint, or modify credentials.

What this skill needs

  • One Paperzilla project
  • One short sentence for "our work" if that context is not already known

If either is missing, ask once and then reuse it for the rest of the workflow.

Examples:

  • Project: Agents evaluation
  • Our work: we build evaluation infrastructure for coding agents.

Transport rules

Follow the transport required by the current profile.

CLI profiles

Use the Paperzilla CLI (pz).

Core commands:

pz project list
pz project <project-id>
pz feed <project-id> --limit 20 --json
pz rec <project-paper-id> --json
pz rec <project-paper-id> --markdown
pz paper <paper-id> --json
pz paper <paper-id> --markdown
pz paper <paper-id> --project <project-id>
pz feedback <project-paper-id> upvote
pz feedback <project-paper-id> star
pz feedback <project-paper-id> downvote --reason not_relevant
pz feedback <project-paper-id> downvote --reason low_quality
pz feedback clear <project-paper-id>

Use --json whenever you need structured feed or metadata parsing.

Keep the Paperzilla object model straight:

  • pz paper <paper-ref> = canonical paper
  • pz rec <project-paper-ref> = recommendation inside one project
  • pz feedback <project-paper-ref> ... = project-specific feedback on that recommendation

When an item comes from pz feed --json, prefer pz rec and pz feedback over pz paper.

CLI markdown behavior differs by command:

  • pz rec --markdown can queue markdown generation and prints a friendly retry message when it is still being prepared
  • pz paper --markdown only returns markdown when it is already ready

MCP profiles

Use the Paperzilla MCP tools directly.

Core tools:

  • projects_list
  • projects_get
  • feed_get
  • paper_get
  • paper_markdown

Preferred sequence:

  1. projects_list when the project is missing or ambiguous
  2. projects_get to confirm project identity when needed
  3. feed_get to pull the latest feed items
  4. paper_get for one paper's metadata
  5. paper_markdown for markdown-backed analysis

Handle paper_markdown statuses correctly:

  • ready: use the markdown
  • queued: tell the user it is still being prepared and suggest retrying shortly
  • unavailable: report that markdown is not currently available

Shared behavior rules

  • Treat Paperzilla relevance and ranking as a strong prior, not the final answer.
  • Use Paperzilla terms exactly: project, feed, Must Read, Related.
  • Name the exact paper or recommendation identifier you used when you inspect one paper.
  • Separate metadata from interpretation.
  • Explain relevance in terms of the user's actual work, not generic importance.
  • Do not dump full markdown unless the user explicitly asks for it.
  • Do not switch to arXiv HTML/abs links as the default fallback when the request was specifically for Paperzilla markdown.

Mode 1: on-demand discussion

Use this mode when the user wants an interactive paper conversation in chat.

Workflow

  1. Resolve the project and the "our work" context.
  2. Pull the latest papers from that project's feed.
  3. Show a short list of the newest or strongest candidates.
  4. When the user picks one paper, return metadata first.
  5. Fetch markdown for that paper or recommendation.
  6. Summarize:

- contribution - method - results - limits - why it matters for our work

  1. Continue the discussion and make a recommendation such as:

- read now - keep as Related - ignore this week

Output contract

For the first feed reply, include:

  • project name
  • the papers you checked
  • per paper: title, date, source, and whether it looks Must Read or Related

For the metadata reply, include:

  • title
  • authors
  • publication date
  • source
  • URL
  • the exact Paperzilla paper ID or project-paper ID used

For the markdown reply, include:

  • contribution
  • method
  • results
  • limits
  • why it matters for our work

Mode 2: weekday brief

Use this mode when the user wants one concise recurring brief for one project.

Workflow

  1. Resolve the project and the "our work" context.
  2. Load the per-project history of papers already proposed in earlier weekday briefs.
  3. Pull the newest papers from the feed.
  4. Exclude papers that were already proposed in earlier weekday briefs unless the user explicitly asked to revisit them.
  5. Select the remaining papers worth mentioning.
  6. For each selected paper, give:

- one short summary - one sentence on why it is relevant to our work

  1. After drafting or sending the brief, append the exact Paperzilla IDs used for the selected papers to that project's proposed-paper history.
  2. If no new papers qualify, say that explicitly.

Output contract

Every weekday brief should include:

  • project name
  • date
  • how many new papers were checked
  • for each selected paper:

- title - one short summary - one sentence on why it is relevant to our work

  • a clear No new papers today. line when nothing new qualifies

Keep the brief concise and easy to scan.

For recurring runs, the agent must keep a persistent per-project record of the exact Paperzilla IDs already proposed in earlier briefs. Do not propose the same paper again in a later recurring brief unless the user explicitly asked to revisit it.

Feedback loop on request

If the user wants to tune future recommendations:

  1. Use pz feedback ... on the recommendation ID.
  2. Explain that feedback is project-specific.
  3. Use:

- upvote for positive signal - star for strongest positive signal - downvote --reason not_relevant for topical mismatch - downvote --reason low_quality for weak paper quality - feedback clear to remove prior signal

Edge cases

  • No project given: ask once, then continue.
  • No "our work" context: ask once for one short sentence, then reuse it.
  • No prior brief history: treat the run as the first brief for that project, initialize an empty proposed-paper history, and persist the papers selected this time.
  • No new papers: report that clearly instead of padding the brief.
  • Large feed: use a sensible limit first, then expand only if needed.
  • Markdown delay: retry more than once when the user explicitly asked for markdown. Prefer a short polling loop over an immediate fallback.
  • Ambiguous paper ID: fall back to the full UUID or clearly restate the paper you selected.
  • External delivery requests: if the user did not explicitly ask for delivery and the profile does not require delivery, do not use the message tool.
  • Canonical vs recommendation confusion: if an ID came from pz feed --json, assume it is a recommendation ID unless shown otherwise.

Agent-specific rules

Read and follow any packaged AGENT.md file for the current profile. The profile file defines the chat surface, delivery surface, and scheduling behavior.

平台分布

OpenClaw

84.46%
按下载量换算1,973

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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。目前只有一个公开来源,建议同时核对源仓库。

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