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Anti-Render 智能图像转换
por
lionad-morotar
·
lionad-morotar
· v1.0.0 · atualizado em 2026-04-10
80
Score
智能识别任何领域的"理想承诺 vs 残酷现实"对比需求，生成理想化渲染、现实主义真实面貌或对比图的三种视觉风格转换
image-generation
visual-transformation
ai-agents
contrastive-analysis
style-transfer
image-editing
0
Stars
0
Forks
0
Usos
Cursor
Claude Code
Claude Desktop
Codex
Copilot
Windsurf
Zed
Fork
Documento do Skill
📋 Workflow
✅ Best Practices
🎯 Triggers & Fases
SKILL.md
anti-render/workflow
1
Receive Image:
— User uploads an image.
2
Domain Identification:
— Identify the image's domain (architecture, person, other).
3
Intent Recognition:
— Determine the user's desired transformation (idealized, realistic, contrast).
4
Resource Loading:
— Load the appropriate style feature library based on the domain.
5
Image Generation:
— Generate the transformed image(s) based on the chosen mode and style guidelines.
6
Composition Preservation:
— Ensure original image structure and elements are maintained.
7
Output:
— Return the transformed image(s) to the user.
Telemetria de Agentes
Execuções
0
total
Taxa de Sucesso
0%
últimos 30d
Latência Média
0.0s
p50
Alucinação
0.0%
detecção
Tokens Entrada
0
avg 0/exec
Tokens Saída
0
avg 0/exec
Uso por Plataforma
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Árvore do Skill
Anti-Render 智能图像转换
anti-render
Fases Cognitivas
5
1.
SENSE
2.
CONTEXTUALIZE
3.
HYPOTHESIZE
4.
ACT
5.
REFLECT
Triggers
8
anti-render this image
apply anti-render processing
create a before and after contrast
show the idealized version
show the realistic version
make a comparison image
process this image with anti-render
generate a realistic view of this image
Avaliar este Skill
Score Breakdown
⭐
Avaliação Humana
0%
🤖
Sucesso de Agentes
0%
🕐
Atualidade
100%
🔗
Saúde de Dependências
100%
🕸️
Centralidade no Grafo
0%
🛡️
Segurança
50%
CompositeScore = α·Humano + β·Agente + γ·Recência + δ·Deps + ε·Centralidade + ζ·Segurança
Instalação
$
synaptic mcp download anti-render
$
synaptic skills detail anti-render
$
synaptic skills live anti-render
Links
GitHub Repository
SynapticSkills