content-summary

Short alias for content-search-summarization. Use this to search public content platforms, rank the top relevant items, and summarize them with links.

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Best use case

content-summary is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Short alias for content-search-summarization. Use this to search public content platforms, rank the top relevant items, and summarize them with links.

Teams using content-summary should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/content-summary/SKILL.md --create-dirs "https://raw.githubusercontent.com/openclaw/skills/main/skills/allens0104/content-summary/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/content-summary/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How content-summary Compares

Feature / Agentcontent-summaryStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Short alias for content-search-summarization. Use this to search public content platforms, rank the top relevant items, and summarize them with links.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# Content summary skill

This is the short public alias for:

- `content-search-summarization`

Also available as simpler aliases:

- `summary`
- `内容摘要`

Use this skill when you want to:

- search Bilibili, YouTube, or similar public content platforms
- pick the top N relevant results for a topic
- summarize each item in Chinese with links

## Primary guidance

1. Prefer `opencli` for supported platforms.
2. If `opencli` is unavailable, fall back to Playwright scraping of public result pages.
3. Rank by relevance first, popularity second.
4. Open selected result pages and use metadata to improve summaries.
5. Use a structured output with source, capture time, link, summary, and confidence.

## Key rules

- Always include source links.
- Include capture time or say when the timestamp is not visible.
- Do not pretend a full video was watched if only metadata was collected.
- Phrase summaries conservatively when based on public page metadata.
- Add a confidence label and a short caveat when the summary is metadata-based.

## Quick invocation template

You do not need to use only `/content-summary`.

Reliable invocation patterns include:

1. `/content-summary`
2. `use the content-summary skill`
3. a natural-language request that clearly asks for content search, ranking, and summary output

Use prompts like:

```text
Use /content-summary to find the top 5 results for <topic> on <platform> and summarize each item with links and confidence labels.
```

```text
使用 /content-summary 在 <平台> 搜索 <主题>,筛选 Top 5,并输出带链接与置信度的摘要。
```

```text
Please find the top results for <topic> on <platform>, rank them by relevance, and summarize each item with links and confidence notes.
```

## Output contract

The skill output should always include:

1. search method used (`opencli` or fallback)
2. keyword and capture scope
3. ranked results with links
4. per-item confidence and caveat
5. explicit note when summaries are metadata-inferred

## Pointer

For the full detailed playbook, also see:

- `skills/content-search-summarization/SKILL.md` in this repository

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