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GZ-L/photo-to-poster-skills
把参考照片做成编辑级艺术海报的开源 Codex Skill 合集
History
Review weekly changes to SKILL.md before updating. Dates mark the weeks in which we observed each version; checks apply to the recorded commits.
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skills/charcoal-fading-travel-study/SKILL.md
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skills/clean-ink-zen-memory/SKILL.md
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skills/folk-ink-landmark-portrait/SKILL.md
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skills/gouache-travel-still-life/SKILL.md
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skills/impasto-miniature-landscape/SKILL.md
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skills/isometric-healing-blocks/SKILL.md
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skills/kraft-stencil-landmark/SKILL.md
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skills/memory-diary-duet/SKILL.md
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skills/nostalgic-travel-duet/SKILL.md
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skills/observational-pen-wash/SKILL.md
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skills/paper-cutout-travel-figures/SKILL.md
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skills/papercraft-travel-diorama/SKILL.md
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skills/pixel-dissolve-landscape/SKILL.md
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skills/watercolor-travel-card/SKILL.md
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Heat
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Heat never changes the order by stars, and sponsorship never touches it. How heat works
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Individual skills in this repository
- charcoal-fading-travel-study
skills/charcoal-fading-travel-study - clean-ink-zen-memory
skills/clean-ink-zen-memory - folk-ink-landmark-portrait
skills/folk-ink-landmark-portrait - gouache-travel-still-life
skills/gouache-travel-still-life - impasto-miniature-landscape
skills/impasto-miniature-landscape - isometric-healing-blocks
skills/isometric-healing-blocks - kraft-stencil-landmark
skills/kraft-stencil-landmark - memory-diary-duet
skills/memory-diary-duet - nostalgic-travel-duet
skills/nostalgic-travel-duet - observational-pen-wash
skills/observational-pen-wash - paper-cutout-travel-figures
skills/paper-cutout-travel-figures - papercraft-travel-diorama
skills/papercraft-travel-diorama - pixel-dissolve-landscape
skills/pixel-dissolve-landscape - watercolor-travel-card
skills/watercolor-travel-card
How it works
charcoal-fading-travel-study
When your agent uses it
Turn travel photos into restrained 3:4 charcoal memory studies that physically fade into clean paper, with split comparison or full-canvas composition.
What it loads into context
Frontmatter
40 tokensAlways available to the agent
SKILL.md
498 tokensWhen the skill is activated
Reference documents
307 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Delivery and mode selection
- Shared visual rules
- Avoid
Files
SKILL.mdcore2,443 bytesSKILL.mdcore2,443 bytesSKILL.mdcore2,443 bytesSKILL.mdcore2,443 bytesagents/openai.yamlasset272 bytesreferences/full-canvas.mddoc702 bytesreferences/split-comparison.mddoc759 bytes
Read SKILL.md
# Charcoal Fading Travel Study
## Delivery and mode selection
- Produce one standalone 3:4 vertical poster per source image. Never combine photos.
- Offer two modes when the user has not already chosen:
1. **Split comparison** — true source photo above, charcoal memory study below.
2. **Full canvas** — the whole poster becomes a charcoal fading study.
- Use one mode for all uploaded photos unless the user maps modes per image.
- Read only the selected guide: [split-comparison.md](references/split-comparison.md) or [full-canvas.md](references/full-canvas.md).
- Return a ready-to-use prompt only when explicitly requested; otherwise use the available image generation or editing capability.
## Shared visual rules
View the complete source on GitHubclean-ink-zen-memory
When your agent uses it
Turn photos into quiet 3:4 editorial posters using pure black ink masses, controlled stippling, pristine ivory paper, and either split comparison or full-canvas composition.
What it loads into context
Frontmatter
46 tokensAlways available to the agent
SKILL.md
477 tokensWhen the skill is activated
Reference documents
330 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Delivery and mode selection
- Shared visual rules
- Avoid
Files
SKILL.mdcore2,320 bytesSKILL.mdcore2,320 bytesSKILL.mdcore2,320 bytesagents/openai.yamlasset257 bytesreferences/full-canvas.mddoc790 bytesreferences/split-comparison.mddoc860 bytes
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# Clean Ink Zen Memory
## Delivery and mode selection
- Produce one standalone 3:4 vertical poster per source image. Never combine photos.
- Offer two modes when the user has not already chosen:
1. **Split comparison** — contemplative real photography above, clean ink reconstruction below.
2. **Full canvas** — the whole poster becomes a clean ink memory study.
- Use one mode for all uploaded photos unless the user maps modes per image.
- Read only the selected guide: [split-comparison.md](references/split-comparison.md) or [full-canvas.md](references/full-canvas.md).
- Return a ready-to-use prompt only when explicitly requested; otherwise use the available image generation or editing capability.
## Shared visual rules
View the complete source on GitHubfolk-ink-landmark-portrait
When your agent uses it
Turn travel photos with recognizable architecture or human-made landmarks into 3:4 folk ink-and-color posters, with either a photo comparison layout or a full-canvas redraw. Do not use when no landmark is recognizable.
What it loads into context
Frontmatter
56 tokensAlways available to the agent
SKILL.md
545 tokensWhen the skill is activated
Reference documents
309 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Delivery and mode selection
- Shared visual rules
- Avoid
Files
SKILL.mdcore2,645 bytesSKILL.mdcore2,645 bytesSKILL.mdcore2,645 bytesSKILL.mdcore2,645 bytesSKILL.mdcore2,645 bytesagents/openai.yamlasset279 bytesreferences/full-canvas.mddoc779 bytesreferences/split-comparison.mddoc748 bytes
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# Folk Ink Landmark Portrait
## Delivery and mode selection
- Use only for photos with clear architecture or a human-made landmark. If none is recognizable, do not invent one; explain that the image is unsuitable.
- Produce one standalone 3:4 vertical poster per source image. Never combine photos.
- Offer two modes when the user has not already chosen:
1. **Split comparison** — real source photo above, folk ink portrait below.
2. **Full canvas** — the whole poster becomes the folk ink portrait.
- Use one mode for all uploaded photos unless the user maps modes per image.
- Read only the selected mode guide: [split-comparison.md](references/split-comparison.md) or [full-canvas.md](references/full-canvas.md).
- Return a ready-to-use prompt only when explicitly requested; otherwise use the available image generation or editing capability.
## Shared visual rulesView the complete source on GitHubgouache-travel-still-life
When your agent uses it
Turn travel photos into 3:4 opaque-gouache posters using a split photo/still-life layout, a full-canvas object still life, or a full-scene gouache redraw.
What it loads into context
Frontmatter
52 tokensAlways available to the agent
SKILL.md
494 tokensWhen the skill is activated
Reference documents
529 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Delivery and mode selection
- Shared visual rules
- Avoid
Files
SKILL.mdcore2,285 bytesSKILL.mdcore2,285 bytesSKILL.mdcore2,285 bytesSKILL.mdcore2,285 bytesSKILL.mdcore2,285 bytesagents/openai.yamlasset301 bytesreferences/full-canvas-still-life.mddoc801 bytesreferences/full-scene-painting.mddoc939 bytesreferences/split-still-life.mddoc814 bytes
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# Gouache Travel Still Life
## Delivery and mode selection
- Produce one standalone 3:4 vertical poster per source image. Never combine photos.
- Offer three modes when the user has not already chosen:
1. **Split still life** — real source photo above, extracted gouache still life below.
2. **Full-canvas still life** — the entire poster becomes a recomposed object archive.
3. **Full-scene painting** — preserve the source composition and repaint the complete scene in opaque gouache.
- Use one mode for all uploaded photos unless the user maps modes per image.
- Read only the selected guide: [split-still-life.md](references/split-still-life.md), [full-canvas-still-life.md](references/full-canvas-still-life.md), or [full-scene-painting.md](references/full-scene-painting.md).
- Return a ready-to-use prompt only when explicitly requested; otherwise use the available image generation or editing capability.
## Shared visual rulesView the complete source on GitHubimpasto-miniature-landscape
When your agent uses it
Turn uploaded photos into full-canvas 3:4 impasto miniature-landscape posters. Use for sculptural oil-paint dioramas, tactile impasto scenes, or when this skill is invoked.
What it loads into context
Frontmatter
53 tokensAlways available to the agent
SKILL.md
618 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Delivery
- Fixed visual specification
- Quality boundaries
Files
SKILL.mdcore3,025 bytesSKILL.mdcore3,025 bytesSKILL.mdcore3,025 bytesSKILL.mdcore3,025 bytesSKILL.mdcore3,025 bytesSKILL.mdcore3,025 bytesagents/openai.yamlasset268 bytes
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# 3D Impasto Miniature Landscape
## Delivery
- Use the source photo only as a reference for subject, structure, pose, spatial relationships, and color. Stylize the entire final canvas; do not show the original photo or create split-screen or before-and-after layouts.
- Generate one standalone 3:4 vertical poster per source image. Process multiple images separately; never create a collage.
- If the user asks only for a prompt, return a ready-to-use generation prompt. Otherwise, use the available image generation or editing capability directly. Ask for an upload only when no reference image is available.
- Preserve subject identity, count, and defining features. You may refine angle, proportions, and local structure for the miniature format, but the result must remain immediately traceable to the source.
## Fixed visual specification
Reconstruct the source image's most recognizable subject, silhouette, pose, and narrative relationship as a refined, dimensional, tactile 3D impasto miniature landscape.
- Use bright white textured paper, generous negative space, and a centered or slightly off-center diagonal axis.View the complete source on GitHubisometric-healing-blocks
When your agent uses it
Turn uploaded photos into full-canvas 3:4 isometric healing-block sculpture posters. Use for rounded modular sculptures, gentle isometric block art, or when this skill is invoked.
What it loads into context
Frontmatter
49 tokensAlways available to the agent
SKILL.md
624 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Delivery
- Fixed visual specification
- Quality boundaries
Files
SKILL.mdcore3,177 bytesSKILL.mdcore3,177 bytesSKILL.mdcore3,177 bytesSKILL.mdcore3,177 bytesSKILL.mdcore3,177 bytesSKILL.mdcore3,177 bytesagents/openai.yamlasset268 bytes
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# 3D Isometric Healing Blocks
## Delivery
- Use the source photo only as a reference for subject, structure, pose, spatial relationships, and color. Stylize the entire final canvas; do not show the original photo or create split-screen or before-and-after layouts.
- Generate one standalone 3:4 vertical poster per source image. Process multiple images separately; never create a collage.
- If the user asks only for a prompt, return a ready-to-use generation prompt. Otherwise, use the available image generation or editing capability directly. Ask for an upload only when no reference image is available.
- Preserve subject identity, count, mass proportions, axes, curves, interlocks, layers, occlusions, and negative spaces. Simplify secondary detail without changing defining features.
## Fixed visual specification
Use a deconstruct → select → distill → reconstruct process to translate the subject into a healing-style 3D/isometric block sculpture. Reorganize it with rounded, simple, tactile modular volumes while keeping it immediately recognizable.
- Adapt the composition to the subject's center of gravity, pose direction, and spatial relationships.View the complete source on GitHubkraft-stencil-landmark
When your agent uses it
Turn photos with a clearly isolated landmark into two-color 3:4 kraft-paper stencil posters, in split comparison or full-canvas mode. Do not use when no single landmark is recognizable.
What it loads into context
Frontmatter
49 tokensAlways available to the agent
SKILL.md
581 tokensWhen the skill is activated
Reference documents
356 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Applicability, delivery, and mode selection
- Shared visual rules
- Avoid
Files
SKILL.mdcore2,877 bytesSKILL.mdcore2,877 bytesSKILL.mdcore2,877 bytesSKILL.mdcore2,877 bytesSKILL.mdcore2,877 bytesagents/openai.yamlasset271 bytesreferences/full-canvas.mddoc853 bytesreferences/split-comparison.mddoc867 bytes
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# Kraft Stencil Landmark
## Applicability, delivery, and mode selection
- Use only for a clearly isolated landmark or object with a strong single silhouette, such as a lighthouse, tower, gateway, monument, windmill, pavilion, bridge tower, or lone boat. If no single subject is recognizable, do not impose a stock landmark.
- Produce one standalone 3:4 vertical poster per source image. Never combine photos.
- Offer two modes when the user has not already chosen:
1. **Split comparison** — true source photo above, kraft stencil print below.
2. **Full canvas** — the whole poster becomes a kraft stencil print.
- Use one mode for all uploaded photos unless the user maps modes per image.
- Read only the selected guide: [split-comparison.md](references/split-comparison.md) or [full-canvas.md](references/full-canvas.md).
- Return a ready-to-use prompt only when explicitly requested; otherwise use the available image generation or editing capability.
## Shared visual rulesView the complete source on GitHubmemory-diary-duet
When your agent uses it
Turn travel or lifestyle photos into 4:5 memory-diary pages pairing real photography with a watercolor and colored-pencil interpretation of the same moment. Use for editorial memory archives and photo-illustration diaries.
What it loads into context
Frontmatter
52 tokensAlways available to the agent
SKILL.md
638 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Delivery
- Left photograph
- Right memory drawing
- Archive text
- Avoid
Files
SKILL.mdcore3,236 bytesSKILL.mdcore3,236 bytesSKILL.mdcore3,236 bytesSKILL.mdcore3,236 bytesagents/openai.yamlasset266 bytes
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# Memory Diary Duet
## Delivery
- Generate one standalone 4:5 vertical poster per source image. Never combine multiple photos.
- Divide the canvas with a diagonal or near-vertical line into complementary areas: real photography on the left and a hand-drawn interpretation of the same moment on the right. Keep the boundary clear, elegant, and aligned with the subject; no gradients, feathering, or media blending.
- If the user asks only for a prompt, return a ready-to-use generation prompt. Otherwise, use the available image generation or editing capability directly. Ask for an upload only when none is available.
## Left photograph
Preserve subject identity, count, structure, pose, object relationships, environment, materials, natural light, and viewpoint. Apply only subtle lifestyle-editorial grading with warm natural light, soft contrast, faint nostalgia, and fine grain. Do not alter subjects, add or remove objects, replace the setting, invent regional details, or illustrate the photo.
## Right memory drawing
View the complete source on GitHubnostalgic-travel-duet
When your agent uses it
Turn travel photos into 3:4 nostalgic editorial posters as either a photo-and-drawing comparison or a full-canvas minimal illustration.
What it loads into context
Frontmatter
38 tokensAlways available to the agent
SKILL.md
397 tokensWhen the skill is activated
Reference documents
293 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Delivery and mode selection
- Shared visual rules
- Avoid
Files
SKILL.mdcore1,996 bytesSKILL.mdcore1,996 bytesSKILL.mdcore1,996 bytesSKILL.mdcore1,996 bytesSKILL.mdcore1,996 bytesagents/openai.yamlasset287 bytesreferences/full-canvas.mddoc838 bytesreferences/split-comparison.mddoc786 bytes
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# Nostalgic Travel Editorial
## Delivery and mode selection
- Produce one standalone 3:4 vertical poster per source image. Never combine photos.
- Offer two modes when the user has not already chosen:
1. **Split comparison** — nostalgic real photography above and a minimal drawing below.
2. **Full canvas** — the complete source scene becomes a nostalgic editorial illustration.
- Use one mode for all uploaded photos unless the user maps modes per image.
- Read only the selected guide: [split-comparison.md](references/split-comparison.md) or [full-canvas.md](references/full-canvas.md).
- Return a ready-to-use prompt only when explicitly requested; otherwise use the available image generation or editing capability.
## Shared visual rules
View the complete source on GitHubobservational-pen-wash
When your agent uses it
Turn uploaded photos into full-canvas 3:4 observational pen-and-wash posters. Use for minimal sketchbook studies, airy pen wash, rhythmic linework, or when this skill is invoked.
What it loads into context
Frontmatter
51 tokensAlways available to the agent
SKILL.md
660 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Delivery
- Fixed visual specification
- Quality boundaries
Files
SKILL.mdcore3,388 bytesSKILL.mdcore3,388 bytesSKILL.mdcore3,388 bytesSKILL.mdcore3,388 bytesSKILL.mdcore3,388 bytesSKILL.mdcore3,388 bytesSKILL.mdcore3,388 bytesagents/openai.yamlasset256 bytes
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# Observational Pen and Wash
## Delivery
- Use the source photo only as a reference for subject, structure, pose, spatial relationships, color, and mood. Stylize the entire final canvas; do not show the original photo or create split-screen or before-and-after layouts.
- Generate one standalone 3:4 vertical poster per source image. Process multiple images separately; never create a collage.
- If the user asks only for a prompt, return a ready-to-use generation prompt. Otherwise, use the available image generation or editing capability directly. Ask for an upload only when no reference image is available.
- Preserve subject identity, count, proportions, direction, defining pose, and scene meaning. Simplify surroundings and secondary details without distorting or replacing defining features.
## Fixed visual specification
Extract only the source image's most recognizable subject, contour, pose, and narrative relationship. Keep the visual clues worth recording, using the minimum information required for immediate recognition while preserving evidence of observation, omission, and stopping.
- Treat the core contour or action as a visual motif. Organize the full page through repetition, variation, pause, accent, and sudden negative space.View the complete source on GitHubpaper-cutout-travel-figures
When your agent uses it
Turn travel photos with recognizable people into 3:4 posters where real photographed environments contain warm-white paper sketch figures, in split comparison or full-canvas mode.
What it loads into context
Frontmatter
46 tokensAlways available to the agent
SKILL.md
539 tokensWhen the skill is activated
Reference documents
314 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Applicability, delivery, and mode selection
- Shared visual rules
- Avoid
Files
SKILL.mdcore2,751 bytesSKILL.mdcore2,751 bytesSKILL.mdcore2,751 bytesSKILL.mdcore2,751 bytesagents/openai.yamlasset286 bytesreferences/full-canvas.mddoc794 bytesreferences/split-comparison.mddoc831 bytes
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# Paper Cutout Travel Figures
## Applicability, delivery, and mode selection
- Use only for photos with recognizable people. If no person is clear enough to preserve, do not add figures; explain that the image is unsuitable.
- Produce one standalone 3:4 vertical poster per source image. Never combine photos.
- Offer two modes when the user has not already chosen:
1. **Split comparison** — full source photo above, reconstructed real environment with paper figures below.
2. **Full canvas** — the whole poster keeps the real environment while all recognizable narrative people become paper figures.
- Use one mode for all uploaded photos unless the user maps modes per image.
- Read only the selected guide: [split-comparison.md](references/split-comparison.md) or [full-canvas.md](references/full-canvas.md).
- Return a ready-to-use prompt only when explicitly requested; otherwise use the available image generation or editing capability.
## Shared visual rulesView the complete source on GitHubpapercraft-travel-diorama
When your agent uses it
Turn uploaded photos into full-canvas 3:4 handcrafted travel diorama posters. Use for papercraft models, tactile miniature travel scenes, or when this skill is invoked.
What it loads into context
Frontmatter
50 tokensAlways available to the agent
SKILL.md
696 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Delivery
- Fixed visual specification
- Quality boundaries
Files
SKILL.mdcore3,615 bytesSKILL.mdcore3,615 bytesSKILL.mdcore3,615 bytesSKILL.mdcore3,615 bytesSKILL.mdcore3,615 bytesagents/openai.yamlasset257 bytes
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# Handcrafted 3D Travel Diorama
## Delivery
- Use the source photo only as a reference for subject, structure, pose, spatial relationships, scene, and color. Stylize the entire final canvas; do not show the original photo or create split-screen or before-and-after layouts.
- Generate one standalone 3:4 vertical poster per source image. Process multiple images separately; never create a collage.
- If the user asks only for a prompt, return a ready-to-use generation prompt. Otherwise, use the available image generation or editing capability directly. Ask for an upload only when no reference image is available.
- Preserve subject identity, count, silhouette, pose, proportions, direction, defining structures, spatial relationships, and narrative context so the result remains immediately traceable to the source. Do not distort, replace, or invent defining features.
## Fixed visual specification
Reconstruct the subject and only the few elements that best reinforce its identity and setting as a refined 3D handcrafted miniature scene. Use paper, cardstock, soft clay, or thin wood. Simplify details without mechanically copying the photograph.
- Build the composition around one dominant subject, one long narrow lightweight floating landscape base, and generous negative space.View the complete source on GitHubpixel-dissolve-landscape
When your agent uses it
Turn uploaded travel photos into full-canvas 3:4 pixel-dissolve landscapes with abundant paper white. Use for curated limited-palette pixel studies or when this skill is invoked.
What it loads into context
Frontmatter
49 tokensAlways available to the agent
SKILL.md
828 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Delivery
- Fixed visual specification
- Quality boundaries
Files
SKILL.mdcore4,052 bytesSKILL.mdcore4,052 bytesSKILL.mdcore4,052 bytesSKILL.mdcore4,052 bytesSKILL.mdcore4,052 bytesSKILL.mdcore4,052 bytesSKILL.mdcore4,052 bytesagents/openai.yamlasset256 bytes
Read SKILL.md
# Pixel Dissolve Landscape
## Delivery
- Use the source photo only as a reference for subject, structure, space, direction, and color. Stylize the entire final canvas; do not show the original photo or create split-screen or before-and-after layouts.
- Generate one standalone 3:4 vertical poster per source image. Process multiple images separately; never create a collage.
- If the user asks only for a prompt, return a ready-to-use generation prompt. Otherwise, use the available image generation or editing capability directly. Ask for an upload only when no reference image is available.
- Create a manually selected, color-limited, recomposed pixel landscape—not a mosaic filter or globally downsampled photo.
## Fixed visual specification
On warm off-white or pale ivory paper, choose one highly recognizable visual anchor from the source, such as a bridge, facade, dome, vehicle, boat, gate, or roof group. Retain only the minimum elements required to communicate subject identity, place, and spatial relationships.
Preserve subject identity, count, pose, architectural proportions, road direction, occlusions, viewpoint, and perspective. Remove repetitive windows, tile texture, tiny signage, tourist clutter, dense cables, foliage noise, and photographic noise when they are nonessential. Never alter defining structures or invent landmarks, people, vehicles, or scene elements.View the complete source on GitHubwatercolor-travel-card
When your agent uses it
Turn uploaded photos into full-canvas 3:4 perforated watercolor travel-card posters. Use for watercolor memory cards, perforated ticket cards, travel archive layouts, or when this skill is invoked.
What it loads into context
Frontmatter
50 tokensAlways available to the agent
SKILL.md
582 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Delivery
- Fixed visual specification
- Quality boundaries
Files
SKILL.mdcore2,972 bytesSKILL.mdcore2,972 bytesSKILL.mdcore2,972 bytesSKILL.mdcore2,972 bytesSKILL.mdcore2,972 bytesagents/openai.yamlasset257 bytes
Read SKILL.md
# Watercolor Travel Card
## Delivery
- Use the source photo only as a reference for subject, structure, space, direction, and color. Stylize the entire final canvas; do not show the original photo or create split-screen or before-and-after layouts.
- Generate one standalone 3:4 vertical poster per source image. Process multiple images separately and never combine them in a single generation.
- If the user asks only for a prompt, return a ready-to-use image-generation prompt. Otherwise, use the available image generation or editing capability directly. Ask for an upload only when no reference image is available.
- Before generation, lock the subject's identity, count, pose, proportions, direction, architectural or terrain structure, spatial relationships, and viewpoint. Do not invent a location, date, coordinates, or attribution.
## Fixed visual specification
The entire canvas is a perforated watercolor travel memory card on warm ivory cotton cold-pressed paper, divided vertically:
- The left 68%–75% reconstructs the scene with transparent watercolor and a few fine pen lines. Preserve the most recognizable contours, pose, direction, colors, and spatial relationships. Remove clutter, repeated objects, micro-texture, and irrelevant detail without changing defining features.View the complete source on GitHubSkills included
- charcoal-fading-travel-study
- clean-ink-zen-memory
- folk-ink-landmark-portrait
- gouache-travel-still-life
- impasto-miniature-landscape
- isometric-healing-blocks
- kraft-stencil-landmark
- memory-diary-duet
- nostalgic-travel-duet
- observational-pen-wash
- paper-cutout-travel-figures
- papercraft-travel-diorama
- pixel-dissolve-landscape
- watercolor-travel-card
Repository facts
- License
- MIT
- Created
- Aug 24, 2026
- Last pushed
- Aug 28, 2026
- Forks
- 1
- Open issues
- 0
- Project activity
- Slowing
Before you install
Instructions onlyAutomated signals, not a guarantee
Checked Nov 7, 2026
Not fully analyzed: some files were too long, unreadable or missing. This never lowers the level.
Show 57 notes
skills/charcoal-fading-travel-study/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/charcoal-fading-travel-study/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/charcoal-fading-travel-study/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/clean-ink-zen-memory/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/clean-ink-zen-memory/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/folk-ink-landmark-portrait/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/folk-ink-landmark-portrait/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/folk-ink-landmark-portrait/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/folk-ink-landmark-portrait/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/gouache-travel-still-life/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/gouache-travel-still-life/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/gouache-travel-still-life/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/gouache-travel-still-life/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/impasto-miniature-landscape/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/impasto-miniature-landscape/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/impasto-miniature-landscape/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/impasto-miniature-landscape/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/impasto-miniature-landscape/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/isometric-healing-blocks/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/isometric-healing-blocks/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzed
- No broad tool permissions
- No dangerous shell commands
- No network access
- No hidden or obfuscated text
- No instruction overrides
- No executable scripts
- No access to secrets
- No requests to vote in Hot
How the signals fit together
Facts from a static read of the files at the pinned commit. They describe what the code does, not why.
Some files could not be read; the facts below still hold.
No combined signals at this commit.
Works with
| Agent | Status | Evidence | Install to |
|---|---|---|---|
| Claude Code | Compatible | Standard SKILL.md skills/charcoal-fading-travel-study/SKILL.md | .claude/skills/<skill-name>/ |
| Codex | Compatible | Standard SKILL.md skills/charcoal-fading-travel-study/SKILL.md | .agents/skills/<skill-name>/ |
| Cursor | Compatible | Standard SKILL.md skills/charcoal-fading-travel-study/SKILL.md | .cursor/skills/<skill-name>/ |
| Gemini CLI | Compatible | Standard SKILL.md skills/charcoal-fading-travel-study/SKILL.md | .gemini/skills/<skill-name>/ |
| GitHub Copilot | Compatible | Standard SKILL.md skills/charcoal-fading-travel-study/SKILL.md | .github/skills/<skill-name>/ |
| OpenCode | Compatible | Standard SKILL.md skills/charcoal-fading-travel-study/SKILL.md | .opencode/skills/<skill-name>/ |
- Native The repository ships a manifest, folder or frontmatter field for this agent.
- Compatible A standard SKILL.md that this agent can read.
- Unknown No evidence either way.
Derived automatically from paths, manifests and frontmatter. Not tested on each agent.