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authoring-data-cli-source

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,...
当用户需要添加或重新设计 agent-data-cli 数据源时使用,支持 RSS、新闻、社交媒体、金融、API、网页爬取、浏览器自动化、身份认证等功能。
severinzhong
开发者工具 clawhub v1.0.1 2 版本 100000 Key: 无需
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概述

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

版本历史

共 2 个版本

  • v1.0.1 当前
    2026-03-30 03:23 安全 安全
  • v1.0.0
    2026-03-19 18:46

安全检测

腾讯云安全 (Keen)

安全,无风险
查看报告

腾讯云安全 (Sanbu)

安全,无风险
查看报告

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