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muapi-multi-angle-reshoot

Re-render a subject or scene from multiple dramatic camera angles, such as fish-eye, bird's-eye, low-angle, and macro, while maintaining consistent identity and detail.

DeepseekModel 官方收录技能 质量 优秀 · 90 v1.0.0

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https://deepseekmodel.com/api/download.php?id=samuraigpt-generative-media-skills-library-visual-multi-angle-reshoot-skill-md&format=skill
下载 .skill 标准格式,含 system_prompt 与 model_config,导入任意 Agent 框架即可使用
.skill 文件中 system_prompt 字段的实际内容。
slug muapi-multi-angle-reshoot name muapi-multi-angle-reshoot version 1.0.0 description Re-render a subject or scene from multiple dramatic camera angles, such as fish-eye, bird's-eye, low-angle, and macro, while maintaining consistent identity and detail. acceptLicenseTerms true Multi-Angle Reshoot Re-render a subject or scene from multiple dramatic camera angles, such as fish-eye, bird's-eye, low-angle, and macro, while maintaining consistent identity and detail. Inputs Name Type Required Default Description subject_description text yes — Description of the subject or scene (e.g. "a professional woman in a black suit holding a laptop"). reference_image image_url no — Optional reference image to maintain consistency across angles. Steps Phase A — Subject Establishment If {{reference_image}} is not provided, submit the plan with ONE step to create the base subject: Subject Generation — muapi image generate (model= nano-banana-pro ): Prompt: A high-quality, professional photograph of {{subject_description}}. Clean studio lighting, sharp focus, realistic textures, cinematic quality. Aspect ratio: 3:4 or 1:1 Present the base image to the user for approval. Phase B — Multi-Angle Reshoot Once the subject is established, submit the plan using muapi image edit (model= nano-banana-2-edit ) to generate the requested angles. Use the approved image from Phase A as the reference for ALL steps. Bird's Eye View Reference: Base Image Prompt: A dramatic bird's eye view (from directly above) of the same subject. High-angle perspective, wide shot, looking down. Maintain exact clothing, face, and setting consistency. Fish Eye Lens Reference: Base Image Prompt: A high-distortion fish-eye lens photograph of the same subject. Ultra-wide angle, curved edges, dramatic perspective, immersive feel. Maintain exact clothing and face consistency. Low Angle (Hero Shot) Reference: Base Image Prompt: A low-angle "hero shot" looking up at the subject. Makes the subject appear powerful and dominant. Maintain exact clothing and face consistency. Dutch Angle Reference: Base Image Prompt: A stylized Dutch angle (tilted horizon) photograph of the same subject. Cinematic, slightly uneasy or dramatic vibe. Maintain exact clothing and face consistency. Macro Close-up Reference: Base Image Prompt: An extreme macro close-up focused on a specific detail of the subject (e.g., eyes, texture of the suit, or a feature of the laptop). Shallow depth of field, incredible detail. Maintain exact colors and textures. Worm's Eye View Reference: Base Image Prompt: A worm's eye view from ground level looking straight up at the subject. Dramatic vertical perspective. Maintain exact clothing and face consistency. After generating the variations, present the multi-angle gallery to the user. You can also offer to generate specific individual angles based on their feedback. Trigger Keywords multi angle , photo reshoot , change camera angle , fish eye view , birds eye view , low angle shot , macro photography , camera perspective Notes for the Executing Agent This recipe is LLM-orchestrated: read each phase, gather any missing inputs from the user, then call muapi CLI commands. Use muapi auth configure first if MUAPI_API_KEY is unset. For model IDs without a CLI alias yet, fall back to the raw endpoint via curl -X POST https://api.muapi.ai/api/v1/<endpoint> -H "x-api-key: $MUAPI_API_KEY" -H 'content-type: application/json' -d '{...}' and poll with muapi predict wait <request_id> . Substitute {{input_name}} placeholders with the user's actual inputs before issuing each call.
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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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