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paperzilla-research-monitorPaperzilla 研究监视器

Agent Skill

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。

总安装

7,295

周安装

298

GitHub Stars

1

下载量

2,336
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: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

简介

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。

SKILL.md

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.

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

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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。

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安装前确认

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