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.
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
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/content-summary/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How content-summary Compares
| Feature / Agent | content-summary | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/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.
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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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