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authoring-data-cli-sourceauthoring 数据 CLI source

Agent Skill

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。

总安装

7,437

周安装

313

GitHub Stars

1

下载量

2,604
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:authoring-data-cli-source(authoring 数据 CLI source)
来源仓库:https://github.com/severinzhong/authoring-data-cli-source
安装命令:
openclaw skills install authoring-data-cli-source
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 authoring-data-cli-source

简介

当用户需要添加或重新设计 RSS、新闻、社交媒体、金融、API、抓取、浏览器自动化、身份验证等的 agent-data-cli 源时使用。

SKILL.md

name
authoring-data-cli-source
description
Use when the user needs to add or redesign an agent-data-cli source for RSS, news, social media, finance, APIs, scraping, browser automation, authentication, or remote content sync.

Authoring agent-data-cli source

Overview

Use this skill to design and implement an agent-data-cli source with stable behavior and clear project fit.

This skill is deliberately stricter than normal feature work because a weak source design causes protocol drift, command confusion, and unreliable sync behavior.

It is the source-authoring path for RSS feeds, HTTP APIs, HTML scraping, browser-driven sites, finance data, news content, and other remote content systems that must fit the source/channel/content model.

Current core contract to keep in mind:

  • source/channel is still the only core resource model
  • content update sources return ContentSyncBatch, not flat per-row persistence instructions
  • shared persistence is now content_nodes, content_channel_links, and content_relations
  • structural relations in core use abstract parent; source-specific meaning belongs in relation_semantic

Hard Gate

Do not start implementation immediately.

The required sequence is:

  1. research
  2. spec
  3. plan
  4. approval
  5. implement
  6. verify

If the user explicitly wants to skip a stage, say what risk that creates before proceeding.

When to Use

Use this skill when the user wants to:

  • add a new source
  • redesign an existing source
  • add source capabilities such as channel search, content search, content update, or content interact
  • add support for RSS, APIs, scraping, browser automation, authentication, cookies, or remote side effects

Do not use this skill for:

  • ordinary content operations against an existing source
  • unrelated CLI or store changes with no source work

Install From skills.sh

Install this skill directly from skills.sh:

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

Install

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 load the bundled skills from this repository's skills/ directory and work from the repo root.

Important boundary:

  • source code belongs in the source workspace repo, typically agent-data-hub
  • keep agent-data-cli focused on core/cli/store/protocol work
  • do not install source runtime dependencies into the core project with uv add
  • use uv pip install or init.sh inside the source workspace instead

Workflow

1. Research

Identify the source type before making architecture decisions.

Classify it as one or more of:

  • RSS
  • API
  • HTML scraping
  • browser-driven
  • auth or session driven
  • interact capable

Research must confirm:

  • whether the source has a real channel concept
  • whether remote discovery and remote sync are distinct
  • how to identify unique content
  • whether the source has hierarchical or container-like content that should become content_relations
  • what time field is available
  • how pagination or incremental fetch works
  • what config is required
  • whether interact is actually possible

Use available web research, local fetch tools, and the repo's fetchers/ where appropriate.

2. Spec

Write a source-specific spec before implementation.

It must define:

  • source to resource mapping
  • supported capabilities
  • config fields and mode if needed
  • content normalization and dedup strategy
  • content_key strategy
  • whether update returns only direct content, or also context nodes and content_relations
  • whether the source needs relation_semantic values such as reply, contains, or list_item
  • storage requirements
  • error boundaries
  • CLI-visible semantics
  • testing scope

For native search/query views:

  • treat column names as a soft compatibility surface because multi-source and multi-channel aggregation merges by column header
  • prefer explicit names such as published_at, publisher, author, price, volume
  • avoid vague names such as time, source, value unless that meaning is genuinely exact
  • column order is mainly for readability; header naming is what determines merge behavior

3. Plan

Turn the approved spec into an implementation plan.

The plan must break work into:

  • failing tests to add first
  • source code units to implement
  • ContentSyncBatch construction path
  • CLI verification steps
  • persistence and audit verification

4. Approval

Wait for user approval after the spec and plan.

Do not jump from research straight to code.

5. Implement

Implement with TDD.

  • write failing tests first
  • verify the failure is correct
  • write minimal code
  • rerun focused tests

6. Verify

Before claiming completion, verify:

  • unit tests
  • CLI simulation tests
  • help output
  • capability and config behavior
  • persistence side effects
  • content_nodes / content_channel_links / content_relations side effects when update is involved
  • interact audit behavior when applicable

Read Next

  • references/source-contract.md for repository rules
  • references/source-type-rss.md for feed-like sources
  • references/source-type-api.md for JSON or HTTP API sources
  • references/source-type-browser.md for browser-driven sources
  • references/source-type-interact.md for remote side effects
  • references/source-testing.md for test matrix
  • references/source-review-checklist.md before final verification

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

79.92%
按下载量换算2,081

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

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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