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topic-monitor主题监视器

Agent Skill

topic-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

289,983

周安装

11,963

GitHub Stars

26

下载量

94,747
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:topic-monitor(主题监视器)
来源仓库:https://github.com/robbyczgw-cla/topic-monitor
安装命令:
openclaw skills install topic-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 topic-monitor

简介

监控感兴趣的主题并在发生重要进展时主动发出警报。当用户想要自动监控特定主题(例如项目)时使用

SKILL.md

name
topic-monitor
version
1.5.2
description
Monitor topics of interest and proactively alert when important developments occur. Use when the user wants automated monitoring of specific subjects like product releases, news topics, technology updates, RSS/Atom feeds, or GitHub releases. Supports scheduled web search plus feed polling, boolean topic filters, AI importance scoring with sentiment tracking, smart alerts vs weekly digests, and memory-aware contextual summaries.
metadata
{"openclaw":{"requires":{"bins":["python3"],"env":{"TOPIC_MONITOR_TELEGRAM_ID":"optional - Telegram chat ID for alerts","TOPIC_MONITOR_DATA_DIR":"optional - defaults to .data/ in skill dir","WEB_SEARCH_PLUS_PATH":"optional - defaults to relative path"},"note":"All env vars optional. Defaults work out of the box."}}}

Topic Monitor

Monitor topics continuously and alert only when something looks relevant.

What’s new in v1.5.0

  • RSS/Atom feed monitoring as a first-class source via feeds
  • GitHub release monitoring via github_reposhttps://github.com/{owner}/{repo}/releases.atom
  • Feed auto-discovery from normal URLs
  • OPML import for feed lists
  • Advanced filters with required_keywords and exclude_keywords
  • Sentiment analysis on findings: positive, negative, neutral, mixed
  • Sentiment shift alerts with alert_on_sentiment_shift

Quick start

python3 scripts/quick.py "AI Model Releases"
python3 scripts/quick.py "OpenClaw Releases" --github-repos "openclaw/openclaw"
python3 scripts/quick.py "Security Advisories" --feeds "https://example.com/security.xml"

Then test it:

python3 scripts/monitor.py --dry-run --verbose

Core model

Each topic can mix multiple sources:

  • Web search via query
  • RSS/Atom feeds via feeds
  • GitHub releases via github_repos

All collected results flow into the same pipeline:

  1. gather results
  2. deduplicate
  3. apply advanced filters
  4. score importance
  5. classify sentiment
  6. alert immediately or save for digest
  7. track state and sentiment history

Topic config

Each topic supports these keys:

  • id
  • name
  • query
  • keywords
  • feeds
  • github_repos
  • required_keywords
  • exclude_keywords
  • frequencyhourly|daily|weekly
  • importance_thresholdhigh|medium|low
  • channels
  • context
  • alert_on
  • alert_on_sentiment_shift
  • ignore_sources
  • boost_sources

Example config

{
  "topics": [
    {
      "id": "openclaw-news",
      "name": "OpenClaw Updates",
      "query": "OpenClaw AI assistant update release",
      "keywords": ["OpenClaw", "release", "update"],
      "feeds": ["https://example.com/blog/rss.xml"],
      "github_repos": ["openclaw/openclaw"],
      "required_keywords": ["release"],
      "exclude_keywords": ["rumor", "affiliate"],
      "frequency": "daily",
      "importance_threshold": "medium",
      "channels": ["telegram"],
      "context": "Track product updates and releases",
      "alert_on": ["keyword_exact_match", "github_release"],
      "alert_on_sentiment_shift": true,
      "ignore_sources": [],
      "boost_sources": ["github.com"]
    }
  ]
}

Advanced filters

required_keywords

All listed terms must appear in the title/snippet before scoring.

"required_keywords": ["release", "stable"]

exclude_keywords

Any matching term filters the result out before scoring.

"exclude_keywords": ["beta", "rumor", "affiliate"]

This is intentionally simple boolean logic:

  • any exclude match → reject
  • any missing required term → reject

RSS/Atom feeds

Direct feeds

python3 scripts/manage_topics.py add "Security Feeds" \
  --feeds "https://example.com/rss.xml,https://example.com/atom.xml" \
  --keywords "security,CVE,patch"

Feed discovery

Discover feeds from a normal website URL:

python3 scripts/manage_topics.py discover-feed https://example.com/blog
python3 scripts/monitor.py --discover-feed https://example.com/blog

Add a topic and auto-discover feeds in one step:

python3 scripts/manage_topics.py add "Vendor Blog" \
  --discover-feeds "https://example.com/blog" \
  --keywords "release,announcement"

OPML import

Import feed subscriptions from an OPML file:

python3 scripts/manage_topics.py import-opml feeds.opml

Imported topics default to daily / medium unless you override:

python3 scripts/manage_topics.py import-opml feeds.opml --frequency hourly --importance high

Feed caching

Feed polling uses feedparser and stores per-feed cache data in monitor state:

  • etag
  • last-modified
  • last check metadata

That allows efficient conditional requests and avoids reprocessing unchanged feeds.

GitHub release monitoring

Track repo releases with:

"github_repos": ["openclaw/openclaw", "anthropics/claude-code"]

These map to GitHub Atom feeds automatically:

  • https://github.com/openclaw/openclaw/releases.atom
  • https://github.com/anthropics/claude-code/releases.atom

CLI example:

python3 scripts/manage_topics.py add "CLI Releases" \
  --github-repos "openclaw/openclaw,anthropics/claude-code" \
  --keywords "release,version"

GitHub release items are labeled clearly in alerts.

Sentiment analysis

Each scored finding also gets a sentiment label:

  • positive
  • negative
  • neutral
  • mixed

Alerts and digest entries include that sentiment.

Sentiment shift alerts

Enable:

"alert_on_sentiment_shift": true

When enabled, a result that changes sentiment versus the topic’s previous sentiment history gets promoted for alerting.

State tracks:

  • last_sentiment
  • sentiment_history

Scripts

scripts/manage_topics.py

# Add topic
python3 scripts/manage_topics.py add "Topic Name" \
  --query "search query" \
  --keywords "word1,word2" \
  --feeds "https://example.com/rss.xml" \
  --github-repos "openclaw/openclaw" \
  --required-keywords "release" \
  --exclude-keywords "beta,rumor"

# List topics
python3 scripts/manage_topics.py list

# Edit topic
python3 scripts/manage_topics.py edit topic-id --feeds "https://example.com/rss.xml"

# Discover feeds
python3 scripts/manage_topics.py discover-feed https://example.com/blog

# Import OPML
python3 scripts/manage_topics.py import-opml feeds.opml

# Test topic
python3 scripts/manage_topics.py test topic-id

scripts/monitor.py

python3 scripts/monitor.py
python3 scripts/monitor.py --dry-run
python3 scripts/monitor.py --topic openclaw-news --verbose
python3 scripts/monitor.py --discover-feed https://example.com/blog

Alert output

Alerts can now include:

  • source label (Web, Feed, GitHub Release)
  • score and reason
  • sentiment
  • sentiment shift marker when applicable

Installation note

Feed support uses Python feedparser.

Install if needed:

pip3 install feedparser

Troubleshooting

Feeds not showing results

  • verify the feed URL manually
  • try discover-feed against the site URL
  • install feedparser
  • run python3 scripts/monitor.py --dry-run --verbose

Too much noise

  • tighten required_keywords
  • add exclude_keywords
  • increase importance_threshold

Missing GitHub release alerts

  • confirm repo is owner/repo
  • verify releases exist on GitHub
  • test with --verbose

Notes

  • Search and feed results are merged into the same scoring pipeline.
  • Existing web-search behavior remains supported.
  • Digest entries store sentiment so weekly output reflects tone changes too.

适合场景

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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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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

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按下载量换算70,302

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通过

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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。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。

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