Synaptic SkillsSynapticSkills
MarketplaceSkill GraphCriar SkillMCP ServerPlataformaEnterprise
v0.1.0-beta
Voltar ao Marketplace
AI / MLMédio

Image Generation Skill

poropenai·openai· v1.0.0 · atualizado em 2026-04-10
80
Score

Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output should be a bitmap asset rather than repo-native code or vector. Do not use when the task is better handled by editing existing SVG/vector/code-native assets, extending an established icon or logo system, or building the visual directly in HTML/CSS/canvas.

image-generationimage-editingai-artvisual-designraster-graphicsbitmap-images
0Stars
0Forks
0Usos
Fork

Documento do Skill

SKILL.mdimagegen/workflow
1. Decide the top-level mode: built-in by default, fallback CLI only if explicitly requested.
2. Decide the intent: `generate` or `edit`.
3. Decide whether the output is preview-only or meant to be consumed by the current project.
4. Decide the execution strategy: single asset vs repeated built-in calls vs CLI `generate-batch`.
5. Collect inputs up front: prompt(s), exact text (verbatim), constraints/avoid list, and any input images.
6. For every input image, label its role explicitly:
reference image
edit target
supporting insert/style/compositing input
7. If the edit target is only on the local filesystem and you are staying on the built-in path, inspect it with `view_image` first so the image is available in conversation context.
8. If the user asked for a photo, illustration, sprite, product image, banner, or other explicitly raster-style asset, use `image_gen` rather than substituting SVG/HTML/CSS placeholders. If the request is for an icon, logo, or UI graphic that should match existing repo-native SVG/vector/code assets, prefer editing those directly instead.
9. Augment the prompt based on specificity:
If the user's prompt is already specific and detailed, normalize it into a clear spec without adding creative requirements.
If the user's prompt is generic, add tasteful augmentation only when it materially improves output quality.
10. Use the built-in `image_gen` tool by default.
11. If the user explicitly chooses the CLI fallback, then and only then use the fallback-only docs for quality, `input_fidelity`, masks, output format, output paths, and network setup.
12. Inspect outputs and validate: subject, style, composition, text accuracy, and invariants/avoid items.
13. Iterate with a single targeted change, then re-check.
14. For preview-only work, render the image inline; the underlying file may remain at the default `$CODEX_HOME/generated_images/...` path.
15. For project-bound work, move or copy the selected artifact into the workspace and update any consuming code or references. Never leave a project-referenced asset only at the default `$CODEX_HOME/generated_images/...` path.
16. For batches, persist only the selected finals in the workspace unless the user explicitly asked to keep discarded variants.
17. Always report the final saved path for any workspace-bound asset, plus the final prompt and whether the built-in tool or fallback CLI mode was used.

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

Skills Relacionados

Similar aScreenshot Capture
65%
Hebbian Synapse
Composite0.650
w = 0.3·α + 0.5·β + 0.2·γ
80
Similar aSora Video Generation Skill
65%
Hebbian Synapse
Composite0.650
w = 0.3·α + 0.5·β + 0.2·γ
81
Similar aSpeech Generation Skill
65%
Hebbian Synapse
Composite0.650
w = 0.3·α + 0.5·β + 0.2·γ
83
Similar aAudio Transcribe
65%
Hebbian Synapse
Composite0.650
w = 0.3·α + 0.5·β + 0.2·γ
80
Similar a ←Sora Video Generation Skill
60%
Hebbian Synapse
Composite0.600
w = 0.3·α + 0.5·β + 0.2·γ
81
Co-executedSora Video Generation Skill
49%
Hebbian Synapse
Composite0.491
w = 0.3·α + 0.5·β + 0.2·γ
81

Árvore do Skill

Image Generation Skill
imagegen
Fases Cognitivas5
1.SENSE
2.CONTEXTUALIZE
3.HYPOTHESIZE
4.ACT
5.REFLECT
Triggers8
generate an imageedit an existing imagecreate a visual assetproduce a product mockupgenerate variants of an imagecreate a transparent background cutouttransform an image's lightingremove an object from an image

Avaliar este Skill

Score Breakdown

⭐Avaliação Humana0%
🤖Sucesso de Agentes0%
🕐Atualidade100%
🔗Saúde de Dependências100%
🕸️Centralidade no Grafo0%
🛡️Segurança49%
CompositeScore = α·Humano + β·Agente + γ·Recência + δ·Deps + ε·Centralidade + ζ·Segurança

Instalação

$ synaptic mcp download imagegen
$ synaptic skills detail imagegen
$ synaptic skills live imagegen

Links

GitHub Repository