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x-bookmarks-digestx 书签摘要

Agent Skill

x-bookmarks-digest 用于补充效率相关能力,适合在 OpenClaw 中需要让 Agent 承接效率相关任务时使用。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

4,633

周安装

199

GitHub Stars

公开资料未说明

下载量

1,624
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:x-bookmarks-digest(x 书签摘要)
来源仓库:https://github.com/bearly-hodling/x-bookmarks-digest
安装命令:
openclaw skills install x-bookmarks-digest
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 x-bookmarks-digest

简介

自动分析 X/Twitter 书签,提取工具、项目和创意。

  • 帮助发现优质资源、技术趋势和产品灵感。x-bookmarks-digest 属于效率类 Skill,可作为该场景下的辅助能力补充。
  • 输出结构化摘要,便于归档或进一步处理。
  • 通过 xurl 接口获取数据并生成操作建议。
  • 需确保网络连通性和目标 URL 可访问性。

SKILL.md

name
x-bookmarks-digest
description
Automatically review X/Twitter bookmarks for useful tools, projects, repos, products, and ideas. Fetches via xurl, analyses for value, and outputs an actionable digest with proposed next steps — including clawhub installs or new skill scaffolding.
version
1.0.0
author
openclaw
triggers
metadata
openclaw
emoji
🔖
version
1.0.0
author
openclaw
requires
bins
["python3", "xurl"]

X Bookmarks Digest

Fetch, analyse, and digest your X/Twitter bookmarks into actionable insights.

When to Use

Activate this skill when the user says anything like:

  • "digest x bookmarks"
  • "check my bookmarks"
  • "review my x bookmarks"
  • "what's interesting in my bookmarks?"
  • "bookmark digest"
  • "any good stuff in my twitter bookmarks?"

Prerequisites Check

Before running the workflow, verify xurl authentication:

xurl whoami

If 401/Unauthorized: Tell the user to set up xurl authentication:

xurl auth apps add <app-name> --client-id <id> --client-secret <secret>

Then run xurl auth default <app-name> to set it as default. Do NOT proceed until auth works. Stop and report the issue.

Workflow — Step by Step

Step 1: Check Rate Limit

Read the state file to check when the last run was:

cat {baseDir}/state.json 2>/dev/null || echo '{"last_bookmark_id": null, "last_run_ts": null, "processed_count": 0}'

If last_run_ts is less than 1 hour ago, warn the user:

"Last digest was run at {time}. Free tier allows max 1 run/hour. Use --force to override."

Only proceed if:

  • No previous run exists, OR
  • More than 1 hour has elapsed, OR
  • User explicitly says to force/override

Step 2: Fetch Bookmarks

Run the fetch script to get new bookmarks:

python3 {baseDir}/scripts/fetch_bookmarks.py --count 50

Options:

  • --count N — number of bookmarks to fetch (default 50, max 100)
  • --force — skip rate limit check
  • --all — fetch all (ignore last-checked ID, reprocess everything)

Output: JSON array of bookmark objects to stdout. Side effect: Updates {baseDir}/state.json with new watermark.

If the output is empty or [], report: "No new bookmarks since last check."

Step 3: Analyse Bookmarks

Pipe the fetched bookmarks through the analyser:

python3 {baseDir}/scripts/fetch_bookmarks.py --count 50 | python3 {baseDir}/scripts/analyse_bookmarks.py

Or if you saved fetch output to a variable, pass it via file:

python3 {baseDir}/scripts/analyse_bookmarks.py --file /tmp/bookmarks.json

Output: Structured JSON with categories and relevance scores:

{
  "summary": {"total": 50, "new": 12, "high": 4, "medium": 5, "low": 3},
  "bookmarks": [
    {
      "id": "123",
      "text": "...",
      "author": "@user",
      "category": "tool",
      "relevance": 5,
      "urls": ["https://github.com/..."],
      "github_repos": ["user/repo"],
      "keywords": ["python", "cli"]
    }
  ]
}

Step 4: Generate Digest

Using the structured analysis output, write a digest following this format:

# X Bookmarks Digest — {date}

## Summary
- {total} bookmarks checked, {new} new since last run
- {high} high-value, {medium} medium, {low} low

## High Value (relevance 4-5)

### [{category}] {title or key topic}
@{author}: "{first 100 chars of text}..."
- URL: {extracted url}
- Why: {1-line explanation of value}
- Action: {specific next step}

## Medium Value (relevance 3)
{same format, briefer}

## Proposed Actions
1. [ ] {action 1}
2. [ ] {action 2}
...

Step 5: Decide on Actions

For each high-value bookmark, decide:

Bookmark TypeAction
GitHub repo / toolPropose git clone or brew install
Clawhub-compatible skillPropose clawhub install <slug>
Interesting project to buildPropose scaffolding a new skill in skills/
Useful article/threadPropose saving to Obsidian vault
Tip/techniquePropose saving to OpenClaw memory

Ask the user which actions to execute. Do not auto-execute without confirmation.

Step 6: Update State

After successful digest, verify state was updated:

cat {baseDir}/state.json

Should show updated last_bookmark_id and last_run_ts.

Error Handling

ProblemAction
xurl not foundTell user: brew install xurl
xurl 401Guide user through xurl auth apps add setup
xurl 429 (rate limit)Report rate limit hit. Suggest waiting 15 mins.
Empty bookmarksReport "No bookmarks found" — user may need to bookmark posts first
No new bookmarksReport "No new bookmarks since {last_run_ts}"
state.json missingFirst run — create fresh state after fetch
Python errorPrint stderr, check Python 3.10+ installed

Test Commands

Quick test (dry run, no state update):

# Test xurl auth
xurl whoami

# Test fetch (small batch)
python3 {baseDir}/scripts/fetch_bookmarks.py --count 5 --force

# Test analyse (with sample data)
echo '[{"id":"1","text":"Check out this amazing CLI tool https://github.com/user/repo","author_username":"devuser","created_at":"2026-03-19T10:00:00Z"}]' | python3 {baseDir}/scripts/analyse_bookmarks.py

# Full pipeline test
python3 {baseDir}/scripts/fetch_bookmarks.py --count 10 --force | python3 {baseDir}/scripts/analyse_bookmarks.py

Or just say: "digest x bookmarks" to run the full workflow.

Configuration

All config is in {baseDir}/state.json:

  • last_bookmark_id — watermark for incremental fetches
  • last_run_ts — rate limit enforcement
  • processed_count — running total of processed bookmarks

No additional configuration files needed. xurl manages its own auth.

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

74.88%
按下载量换算1,216

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。

来源信息

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