Find agent skills by outcome

- Avoid skipping any details

as every part is important.

- Focus on one section at a time

ensuring thorough analysis and coding.

- 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

| 可操作性 | [e.g.

`信息型` (了解作品)

| 目标受众 | [e.g.

`特定类型爱好者`

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

universal text links.

*(The fully processed

cleaned

| 资源详情 | [e.g.

`MSAJ-0195 (25GB

| 发行日期 | [Release Date. If none

display N/A.] |

| 制作商 | [Studio/Maker Name. If none

display N/A.] |

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

display N/A.] |

| 作品标题 | [The full

clean title of the movie/video] |

| 识别代码 | `[e.g.

SIRO-5554]` |

| 文章调性 | [e.g.

`营销推广`

- Generic Element Conversion: For all other elements

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

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:

*You must strictly adhere to the following unified

multi-section structure.*

2. Conditional Translation: If the language is not Chinese

translate it.

Data

3. Conditional Metadata Enrichment: If `Media/Video`

extract specialized data (Identifier

2. Universal Core Analysis: Analyze Core Takeaways

Target Audience

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

magnet links

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

discarding invalid ones.

- **Semantic Embed Handling (e.g.

Twitter):**