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Agent Skill · 研究检索

using-data-cli(using 数据 CLI)

用于辅助数据整理、表格处理、CSV/Excel 分析、指标计算和图表准备。它适合让 Agent 清洗字段、汇总数据、发现异常、生成统计口径或把分析结果转成可读说明。使用时需要确认数据来源、字段含义和时间范围,避免把样本数据当全量事实;涉及敏感数据、导出文件或批量写回时,应先确认权限和脱敏边界。

using-data-cli 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为执行命令;许可证为 MIT-0,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 15,441。

总安装 7,854周安装 324GitHub Stars 1下载 2,566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
1.0.1

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:using-data-cli(using 数据 CLI)
来源仓库:https://github.com/severinzhong/using-data-cli
安装命令:
openclaw skills install using-data-cli
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 using-data-cli

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。

当用户想要通过 agent-data-cli 和任何配置的发现、跟踪、同步或查询新闻、RSS、社交、金融或其他外部源时使用。

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 using-data-cli;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

    它需要执行命令,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

using-data-cli 怎么安装?

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

using-data-cli 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。

using-data-cli 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 openclaw skills install using-data-cli 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

using-data-cli 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。

using-data-cli 用的人多吗?

公开数据是累计安装 7,854 次,近一周安装 324 次,下载 2,566 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。

using-data-cli 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

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。

先想清楚的地方

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 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。

不太适合

  • 不能接受 Skill 在你机器上执行命令的人。
  • 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
using-data-cli

using 数据 CLI · 本页

7,8541执行命令MIT-0有提醒

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
using-data-cli
description
Use when the user wants to discover, track, sync, or query news, RSS, social, financial, or other external sources through agent-data-cli and any configured source workspace such as agent-data-hub.

Using agent-data-cli

Overview

agent-data-cli is a local information center for multi-source content.

This skill is for discovering sources, searching channels, subscribing, syncing remote content, querying the local database, and running explicit interactions against news, RSS, social media, and financial data sources.

Use it for:

  • news
  • social media
  • financial data
  • RSS feeds
  • other sources that fit the source/channel/content model

This skill is operational, not explanatory. When the user's goal is clear, execute the CLI flow directly instead of only suggesting commands.

When to Use

Use this skill when the user wants to:

  • inspect available sources or channels
  • discover remote content before subscribing
  • subscribe to channels for ongoing tracking
  • sync subscribed channels into the local database
  • query locally stored content
  • run explicit remote interactions on content refs

Do not use this skill for:

  • implementing or redesigning a source
  • changing the command surface or core protocol
  • free-form scraping outside the agent-data-cli model

Install From skills.sh

Install this skill directly from skills.sh:

npx skills add https://github.com/severinzhong/agent-data-cli --skill using-data-cli

Install And Repo Setup

If agent-data-cli is not present locally, install it first:

git clone https://github.com/severinzhong/agent-data-cli
cd agent-data-cli
uv sync

Then:

  1. Load the bundled skills from this repository's skills/ directory.
  2. Use the repo root that contains pyproject.toml, cli/, and store/.
  3. Treat source_workspace as external configuration. The default path is ./sources, and it is typically backed by the separate agent-data-hub workspace.
  4. Execute commands from the repo root.

Always prefer:

uv run -m adc ...

Operating Rules

  • Translate natural language into the smallest correct CLI flow.
  • Respect the command semantics exactly.
  • Do not invent fallback behavior when a capability is unsupported.
  • Do not hide remote side effects behind search or update.
  • Do not turn content query into a remote search.
  • Do not auto-subscribe unless the user's goal implies ongoing tracking.
  • For content interact, require an explicit source and explicit refs.

Read references/command-semantics.md before using a command family you have not touched in the current session.

Read references/task-patterns.md when the user request is ambiguous and needs stable intent-to-command mapping.

Read references/result-reporting.md before reporting back after a multi-step run.

Usage Tips

Configure Proxy

proxy_url uses one field with three states:

  • unset: use the user's current network environment
  • http://127.0.0.1:7890: force that proxy
  • direct: force direct connection and break CLI-level proxy inheritance

When one source needs its own proxy behavior, configure it explicitly:

uv run -m adc config source set <source> proxy_url http://127.0.0.1:7890
uv run -m adc config source set <source> proxy_url direct

If multiple sources should share one proxy, set the CLI-level default:

uv run -m adc config cli set proxy_url http://127.0.0.1:7890
uv run -m adc config cli unset proxy_url

If a source needs to bypass an inherited CLI proxy, set that source to direct.

Inspect current source config:

uv run -m adc config source list <source>

Configure source_workspace

Core only loads sources that exist in the current workspace.

uv run -m adc config cli explain source_workspace
uv run -m adc config cli set source_workspace ./sources
uv run -m adc config cli set source_workspace /abs/path/to/agent-data-hub

If the workspace contains data_hub, use it to discover, install, or uninstall official sources:

uv run -m adc content search --source data_hub --channel official --query xiaohongshu
uv run -m adc content interact --source data_hub --verb install --ref data_hub:content/xiaohongshu
uv run -m adc content interact --source data_hub --verb uninstall --ref data_hub:content/xiaohongshu

Schedule Updates with cron

Use a system scheduler when you want periodic local syncs. Keep the repo path explicit and append logs so the run can be inspected later:

30 8 * * * cd /abs/path/to/agent-data-cli && /abs/path/to/uv run -m adc content update --source bbc >> /abs/path/to/agent-data-cli/update.log 2>&1

If you need tighter OS integration, the same pattern can also be implemented with launchd or systemd.

Use --jsonl with jq or awk

For machine filtering, prefer --jsonl and pipe to shell tools:

uv run -m adc content query --source cryptocompare --channel BTC --limit 30 --jsonl | jq '.title'
uv run -m adc content query --source cryptocompare --channel BTC --limit 30 --jsonl | jq 'select(.channel=="BTC")'
uv run -m adc content query --source cryptocompare --channel BTC --limit 30 --jsonl | awk -F'"' '/"channel": "BTC"/ {print $0}'
uv run -m adc content query --source xiaohongshu --children xiaohongshu:content/note%3A123 --depth -1 --jsonl | jq '.relation_depth'

The same pattern works for remote discovery:

uv run -m adc channel search --source cryptocompare --query BTC --limit 5 --jsonl | jq '.channel_key'

Save Output with > and >>

Use > to overwrite a file and >> to append:

uv run -m adc content query --source cryptocompare --channel BTC --limit 100 --jsonl > btc.jsonl
uv run -m adc content query --source cryptocompare --channel ETH --limit 100 --jsonl >> btc.jsonl
uv run -m adc channel search --source cryptocompare --query BTC --limit 20 --jsonl > channels.jsonl

This is useful when you want to:

  • keep a snapshot for later analysis
  • feed results into jq, awk, or other CLI tools
  • accumulate multiple command outputs into one JSONL file

Execution Flow

  1. Classify the request as discovery, subscription, sync, local query, or remote interact.
  2. Check whether the task should stay local or requires remote execution.
  3. If needed, inspect source capability and config state before executing the main command.
  4. Run the shortest correct command chain.
  5. Report what was done, what was found, and what next action is now available.

Hard Boundaries

  • channel search is remote channel discovery only.
  • content search is remote content discovery only and does not write to the database.
  • content update is the only remote sync path that writes to the database.
  • content query is local-only and never triggers remote work.
  • content interact is explicit remote side effect execution only.
  • installing source runtime dependencies must stay out of the core project manifest; use uv pip install or source-local init.sh, not uv add

If a task does not fit these boundaries, say so directly instead of approximating.

平台分布

OpenClaw

82.5%
按下载量换算2,117

安全审计

VirusTotal

可疑

ClawScan

通过

Static analysis

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 openclaw skills install using-data-cli 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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