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decompose-multimedia-source-verification

A two-stage strategy to isolate specific visual or bibliographic details from social media and video content by separating source identification from contextual extraction.

DeepseekModel 官方收录技能 质量 良好 · 64 v1.0.0

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name decompose-multimedia-source-verification description A two-stage strategy to isolate specific visual or bibliographic details from social media and video content by separating source identification from contextual extraction. When to Use This strategy is triggered when a query requires identifying a specific object, title, or detail contained within a piece of multimedia content. It is applicable when the user provides metadata signals such as a platform-specific title, an uploader's handle, or a precise upload timeframe. Use this when the answer cannot be found in general knowledge but resides within the visual or auditory stream of a specific digital asset. Decomposition Template Source Authentication & Retrieval : Locate the primary source URL and retrieve the most granular metadata available (full transcript, OCR data, or frame-by-frame descriptions). The goal is to move beyond search engine snippets to the actual content body. Targeted Contextual Extraction : Within the retrieved source, isolate the specific segment referenced. Distinguish between the subject matter (what the video is about) and the target object (the specific item, text, or title requested). Cross-Reference Verification : Compare the extracted detail against the video’s official description or pinned comments to ensure the item is not a misidentified prop or a generic placeholder. Worker Assignment Rules Worker 1 (The Scout) : Responsible for finding the exact video link and the full transcript/metadata. Worker 2 (The Analyst) : Responsible for scanning the transcript or visual descriptions to find the specific timestamp and extracting the requested detail. Worker 3 (The Auditor) : Required if the target is a "title" or "name," to ensure the worker hasn't substituted a descriptive summary for a formal name. Answer Format The final output must clearly state the specific detail found, followed by the timestamp or source segment where it was located. 最终答案: [Specific Detail/Title] (Found at [Timestamp/Context]) Anti-Patterns Topic-Object Confusion : Substituting a general description of the video's theme for the specific bibliographic or physical title requested. Snippet Reliance : Formulating an answer based on search engine preview text which often truncates or summarizes the actual data. Temporal Drift : Failing to verify the upload date, leading to the selection of a similar video from the same creator but a different timeframe. Metadata Blindness : Ignoring the video description or pinned comments which often contain the precise names of items shown in the video.
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下载的 .skill 包内含以下字段。
字段 说明
format格式标识(skill/v1)
skill_id技能唯一 ID
name技能名称
version版本号
description技能描述
category所属分类(数组)
trigger_words触发词列表
tags标签列表
source来源标识
source_url来源链接(本页地址)
exported_at导出时间(每次下载生成)
system_prompt系统提示词正文
model_config模型参数:provider / model / temperature / max_tokens / top_p
examples示例
install_guide各平台导入说明(Coze / Dify / Claude / 自定义框架)
同一份技能可按不同平台格式导出。
.skill 标准格式,含 system_prompt 与 model_config,导入任意 Agent 框架即可使用 下载
.skillpro 增强格式,额外含脚本 / 工具 / 依赖 / 钩子占位 下载
.json 纯 JSON 导出,只含 system_prompt 与模型参数 下载
Coze 带 frontmatter 的 Markdown,Coze 平台导入用 下载
Dify Dify DSL,创建应用后直接导入 下载

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