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attention-research注意力研究

Agent Skill

attention-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。

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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:attention-research(注意力研究)
来源仓库:https://github.com/riverho/attention-research
安装命令:
openclaw skills install attention-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 attention-research

简介

attention-research 定时监控指定主题并生成信号优先的研究摘要。

  • 适用于市场情报收集、趋势追踪和竞争动态分析场景。
  • 每日两次自动更新 META.json 状态文件,保持信息新鲜度。
  • 安装命令为 openclaw skills install attention-research,需配置监控关键词列表。
  • 输出内容依赖公开数据源,可能存在延迟或信息不完整情况。

SKILL.md

name
attention-research
description
Scheduled intelligence research pipeline — monitors topics on a twice-daily cadence, produces signal-first digests, maintains META.json freshness state. Use for tracking geopolitical conflicts, AI trends, macro signals, climate, and biotech with structured state and delta-based updates.
metadata

attention-research Skill

Scheduled intelligence research pipeline with topic monitoring, freshness state, signal-first digest delivery, and per-topic alerting based on topic-defined threshold criteria.

What It Is

A twice-daily research cadence (morning + afternoon) that:

  • Scans configured topics via the agent's web search tool
  • Maintains per-topic freshness state in META.json
  • Uses each PROMPTS/TOPICS/<topic>.md file as the standing monitoring note for that topic
  • Produces digests that connect signals, not just dump headlines
  • Alerts the user when key events or threshold criteria defined by the topic are met
  • Delivers via Telegram or WhatsApp

Core Concepts

Topic

A long-running monitoring domain (e.g., us-iran-conflict, ai, geopolitics).

Topic Monitoring Note

PROMPTS/TOPICS/<topic>.md is not just setup text. It is the standing monitoring note for that topic. It should contain the topic's methodology, analysis framework, entity framing, signal criteria, watch items, and threshold/key event logic used to decide when the user should be alerted.

Thread

An active research question within a topic. Threads have state, typed connections, and delta updates.

Digest

The default output surface. A structured readout of what changed and why.

META.json Freshness Contract

Every topic has a META.json that acts as a shared freshness marker for all writers:

  • Morning and afternoon slots have independent timestamps
  • Max 2 retries per topic per day total
  • After 2 failures → topic skipped for that day

Research Root

$HOME/.openclaw/workspace/docs/research/

Package Structure

attention-research/
├── PROMPTS/
│   ├── CORE/                    # Generic analysis framework shared across topics
│   │   ├── system-prompt.md
│   │   ├── signal-rules.md
│   │   └── digest-format.md
│   ├── TOPICS/                  # Topic-local methodology and monitoring notes
│   │   ├── us-iran-conflict.md
│   │   ├── ai.md
│   │   ├── geopolitics.md
│   │   ├── finance-markets.md
│   │   ├── climate-changes.md
│   │   └── bio-tech.md
│   ├── TEMPLATES/
│   │   ├── morning-research.md
│   │   ├── afternoon-research.md
│   │   └── onboarding.md
│   └── GENERATOR/
│       └── generator.md
├── CONFIG/
│   ├── topics.yaml
│   └── default-paths.yaml
├── SCHEMA/
│   └── META.json.template
├── SCRIPTS/
│   ├── research-executor.sh
│   └── setup-cron.sh
├── INSTALL/
│   └── install.sh
├── SKILL.md
├── README.md
└── package.json

Installation

# Install via clawhub (after publishing)
clawhub install attention-research

# Or install directly from GitHub with git
mkdir -p ~/.openclaw/skills
git clone https://github.com/riverho/attention-research.git ~/.openclaw/skills/attention-research
cd ~/.openclaw/skills/attention-research
bash INSTALL/install.sh --fresh

# Or install directly from GitHub with curl
mkdir -p ~/.openclaw/skills && \
cd ~/.openclaw/skills && \
curl -L https://github.com/riverho/attention-research/archive/refs/heads/master.tar.gz \
  | tar -xz && \
mv attention-research-master attention-research && \
cd attention-research && \
bash INSTALL/install.sh --fresh

Configuration

Agent onboarding contract

Any agent using this skill should follow this order:

  1. Install the repo or skill files
  2. Ask the user to confirm the default research root:

- preferred: ~/.openclaw/workspace/docs/research - fallback: ~/docs/research

  1. Check delivery configuration (Telegram chat ID or WhatsApp recipient)
  2. Present the default OSS topic set:

- us-iran-conflict - ai - finance-markets

  1. For each selected topic, read PROMPTS/TOPICS/<topic>.md and extract the key entities / entity framework back to the user before activation
  2. Ask whether to activate the topic
  3. Ask whether to register the morning and afternoon cron jobs
  4. Only after approval: update config, run setup, and activate monitoring

topics.yaml — What to Track

topics:
  us-iran-conflict:
    display_name: "US-Iran Conflict"
    description: "US-Iran tensions, Hormuz, nuclear talks, sanctions"
    enabled: true
    search_query: "US Iran conflict Hormuz nuclear talks"

Delivery Channel

Edit CONFIG/default-paths.yaml:

delivery:
  telegram:
    chat_id: "YOUR_CHAT_ID"

Cron Jobs

JobSchedulePurpose
AR morning digest08:00 HKTMorning research scan
AR afternoon update16:00 HKTAfternoon research scan

Publishing

clawhub publish ./attention-research \
  --slug attention-research \
  --name "Attention Research Pipeline" \
  --version 1.0.0 \
  --changelog "First public OSS cut"

Requirements

  • Python 3 + PyYAML
  • OpenClaw with cron daemon
  • A web search tool available to the agent (agent-chosen: Tavily, Brave, native, etc.)
  • Telegram or WhatsApp delivery channel

Agent operating rule

Agents should treat this skill as an attention-research workflow, not just a folder of prompts.

On every run:

  • follow the prompt stack order
  • read PROMPTS/TOPICS/<topic>.md as the live monitoring note for that topic
  • use the topic's own methodology and key-event criteria to judge significance
  • keep runtime artifacts isolated per topic under the research root
  • alert the user when threshold or key-event criteria in the topic file is met
  • do not let one topic's analysis framework bleed into another topic's reasoning

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

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可疑

ClawScan

可疑

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通过

权限和风险

external-service

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

安装前确认

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