Find agent skills by outcome

- The final output must be completely free of ads

navigation menus

- Error Handling: If parsing fails

you must output a clear error message: ⚠️ Readability algorithm could not process this page structure. Detected [Reason

| 目标受众 | [e.g.

`特定类型爱好者`

| 可操作性 | [e.g.

`信息型` (了解作品)

| 文章调性 | [e.g.

`营销推广`

| 识别代码 | `[e.g.

SIRO-5554]` |

| 作品标题 | [The full

clean title of the movie/video] |

| 出演者 | [Comma-separated list of actors. If none

display N/A.] |

| 制作商 | [Studio/Maker Name. If none

display N/A.] |

| 发行日期 | [Release Date. If none

display N/A.] |

| 资源详情 | [e.g.

`MSAJ-0195 (25GB

> [A highly condensed 60-90 word summary that synthesizes the article's purpose

tone

*This section presents the translated content

or the original content if it was already Chinese.*

*(The fully processed

cleaned

- 富媒体嵌入: Special content like Twitter embeds are intelligently identified and reformatted into a clean

readable Markdown blockquote that preserves the original content

- 视频框架: All preserved videos are represented as clean

universal text links.

1. DOM Parsing & Scoring: Parse the HTML

identify content candidates

2. Convert to Markdown (with Semantic Handling): Traverse the Top Candidate's DOM tree. Before applying generic conversion rules

execute the following high-priority semantic checks:

- **Semantic Embed Handling (e.g.

Twitter):**

2. Extract: From within this block

extract: Tweet Content

- Generic Element Conversion: For all other elements

apply standard conversion rules for block-level (`h1`

- Robust Image Handling: Convert `<img>` tags to `![Image](URL)`

discarding invalid ones.

4. Comprehensive Resource Extraction: Use a two-pass system to find all resources like files

magnet links

*This phase uses the **original

untranslated content** from Phase 3.*