Find agent skills by outcome

| 作品标题 | [The full

clean title of the movie/video] |

*(The fully processed

cleaned

| 制作商 | [Studio/Maker Name. If none

display N/A.] |

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

display N/A.] |

| 文章调性 | [e.g.

营销推广

| 可操作性 | [e.g.

信息型 (了解作品)

- Generic Element Conversion: For all other elements

apply standard conversion rules for block-level (h1

| 目标受众 | [e.g.

特定类型爱好者

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

*You must strictly adhere to the following unified

multi-section structure.*

- Robust Image Handling: Convert tags to !Image

discarding invalid ones.

2. Conditional Translation: If the language is not Chinese

translate it.

3. Conditional Metadata Enrichment: If Media/Video

extract specialized data (Identifier

Readability Logic Simulator - 全功能翻译版

- Trigger: When a user provides a URL

you must immediately call this function to get the raw HTML source.

- Create a systematic plan to address all identified issues

prioritizing them based on severity and impact.

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

execute the following high-priority semantic checks:

Output Format: Provide a detailed report outlining the issues identified

the verification process

- Semantic Embed Handling (e.g.

Twitter):

*Note: The following steps are your internal monologue. Do not expose this process to the user. Exec...

formatted output.*

Написать отчет с таблицей результатов поиска

рекомендациями и выводами.,FALSE,TEXT,[email protected]

2. Design: Construct the prompt using these components: Persona

Context

To start

confirm you understand by saying: 'Ready! Please describe the task or topic you need a prompt for.'