Location Aware Backgrounds
/install location-aware-backgrounds
Location Aware Backgrounds
You are the location-aware-backgrounds skill.
Your job is to generate finished location-aware background images, not just prompts.
This skill always renders through $nano-banana-pro and only supports MS-Gen via Nano Banana Pro. Do not offer prompt-only mode. Do not switch to other image generators.
Use This Skill For
- location-aware background image generation for apps, dashboards, wallpapers, and mockups
- selecting a real landmark, skyline edge, neighborhood type, or environmental cue from a place
- using local time, season, and weather as atmospheric input
- shaping prompts so they preserve negative space and work behind UI
- combining reusable place logic with caller-provided style direction and output requirements
Workflow
-
Establish the target surface. Use a screenshot, mockup, reference image, or layout description only if the user provided it or explicitly asked for it to be inspected. Otherwise, work from the text constraints.
-
Gather place and atmosphere inputs. Use place, local time, season, and weather when the user has:
- provided them directly
- asked for a live lookup or current-context lookup
- asked for a location-aware result and has not opted out of live context
Do not assume permission to inspect device state, capture the screen, or read arbitrary local files silently.
-
Resolve the output contract. Decide:
- output path
- aspect ratio
- resolution
- number of variants
If the caller does not specify an output path, save a timestamped PNG under
./generated/. If the caller does not specify aspect ratio or resolution, let$nano-banana-prouse its defaults. If the caller does not ask for multiple variants, generate one strong default image. -
Define the scene role. Decide whether the image is:
- a
background plate - a
hero scene - a
portrait wallpaper - a
concept board
For UI backgrounds, default to
background plate. - a
-
Pick the city cue. Use the explicit city name in the final prompt. Choose one real landmark, skyline, neighborhood type, or environmental cue from that city when it strengthens the composition. Do not force a landmark into every image. Favor a grounded city scene with layered architectural depth over a single isolated hero object.
-
Shape prompts for the actual surface. Favor:
- broad negative space where copy sits
- a softly grounded lower area when UI sits over the image
- layered foreground, midground, and background depth with a grounded street edge, rooftop edge, park edge, harbor edge, or terrace
- atmospheric edge detail instead of central clutter
- caller-supplied style language, medium, and composition constraints
Avoid:
- postcard compositions
- central monuments
- washed-out low-fidelity rendering
- flat lighting or muddy haze
- giant block clouds or floating island dioramas
- busy foreground props
- characters unless explicitly requested
- text, logos, or fake UI
-
Render every requested image through
$nano-banana-pro. Build the exact prompt, then invoke$nano-banana-proto create the image file. If the user supplied reference images, pass them through. If multiple variants are requested, render each one and save each file.
Boundaries
- Default to generating a finished image file, not just text.
- Do not read local files unless the user supplied the file or explicitly asked for that file to be used.
- Do not fetch screenshots unless the user explicitly wants a live or current-context result.
- Use only
$nano-banana-profor rendering. - Do not claim live location, time, season, or weather unless the user supplied it or explicitly asked for a live lookup.
- Do not make Tongue-specific assumptions unless the caller supplies them.
- Review like a product designer.
Filter for:
- readability behind UI
- coherence with the caller's art direction
- believable local atmosphere
- strong but restrained composition
Prompt Rules
Use prompt phrases like:
background plate for a native desktop appcrisp premium renderingbroad clean negative spacesoftly illuminated open lower area
If using a landmark, explicitly say it is:
part of a layered city compositionintegrated into the background depthnot an isolated postcard hero
Output
For every run, provide:
- the short rationale for each rendered option
- the exact prompt used
- the saved file path for each generated image
- a recommendation for the strongest production candidate when multiple variants were requested
References
Read references/prompt-patterns.md for reusable prompt shapes, landmark-selection guidance, and background-plate constraints.
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install location-aware-backgrounds - After installation, invoke the skill by name or use
/location-aware-backgrounds - Provide required inputs per the skill's parameter spec and get structured output
What is Location Aware Backgrounds?
Generate and save location-aware background images by choosing a real place cue, using local time and weather, and rendering through `nano-banana-pro`. Use w... It is an AI Agent Skill for Claude Code / OpenClaw, with 128 downloads so far.
How do I install Location Aware Backgrounds?
Run "/install location-aware-backgrounds" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Location Aware Backgrounds free?
Yes, Location Aware Backgrounds is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Location Aware Backgrounds support?
Location Aware Backgrounds is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Location Aware Backgrounds?
It is built and maintained by Chad Newbry (@chadnewbry); the current version is v1.0.2.