notquenotque/vexjoy-agent/skills/content/image-gen/SKILL.md

image-gen

Skill448 starsChanged 5 days agoMITView on GitHub

AI image generation: Gemini and Nano Banana backends; single/series/batch workflows with prompt-to-disk.

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Installs packages

49 other projects use a version of this.

Adopted by

Most recently taken up by

lohi-ai/babysittheir own version, first seen Nov 8, 2026
uprinter/ai-agents-teamtheir own version, first seen Nov 8, 2026
artemmarketolog/image-gentheir own version, first seen Nov 8, 2026
ITch8/customs-data-skillstheir own version, first seen Nov 8, 2026
dotslashsimran/simcrafttheir own version, first seen Nov 8, 2026
Sma1lboy/rovetheir own version, first seen Nov 6, 2026

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Other versions49 projects use a version of this.
Word for word · 1
notque/claude-code-toolkit★ 448100% same
Edited · 0
None found.
Wrote their own version · 48
ethereum/ethereum-org-website★ 6ksame name
fastclaw-ai/fastclaw★ 1.4ksame name
QuixiAI/agi-memory★ 623same name
QuixiAI/Hexis★ 623same name
suitedaces/dorabot★ 247same name
Sma1lboy/rove★ 184same name
wpsnote/wpsnote-skills★ 184same name
microsoft/Huabu★ 170same name
different-ai-studio/teamclaw★ 128same name
marswaveai/skills★ 82same name
38 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
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The file

We split this skill into the rules it gives an agent

8 rules. 0 are common, 7 are distinctive, and 1 is very specific to this project.

0
Common
Most of the 34 edited versions we read keep these.
7
Distinctive
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.

Common
Distinctive
Very specific

Distinctive:
Write all prompts to disk before any API call.
line 60
Distinctive:
Gate: all prompt files written and reviewed.
line 80
Distinctive:
Use absolute paths for output files.
line 117
Very specific:
Use output of image 1 as --reference for image 2.
line 128
Distinctive:
Read the generated image to verify:
line 137
Distinctive:
No unwanted watermarks or artifacts
line 139
Distinctive:
No excessive padding or dark borders
line 141
Distinctive:
If inspection fails: regenerate with adjusted prompt.
line 143

“Common” is measured: kept by at least 6 in 10 of the 34 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.

Files

SKILL.md

image-gen

Backend-agnostic image generation: single images, series with anchor-chain consistency, batch pipelines. Two backends: Gemini (API) and Nano Banana (local scripts with post-processing).

Deep References

Signal	Load	Content
Gemini backend selected	`references/backends/gemini.md`	Models, env vars, flag table, examples, error codes
Nano Banana needed (post-processing, series, JSON batch, style-match)	`references/backends/nano-banana.md`	Subcommands, flags, aspect ratios, prompt patterns by asset type

Phase 1: Detect Backend

python3 skills/content/image-gen/scripts/detect-backend.py

gemini -- load references/backends/gemini.md
ask -- no key found; ask the user to set GEMINI_API_KEY

Gate: backend confirmed.

Phase 2: Write Prompt Files

Write all prompts to disk before any API call. Prompt files are the generation record and anchor-chain input for series.

File naming: single prompts/YYYY-MM-DD-{slug}.md, series prompts/{series-name}-01.md through -NN.md.

---
model: gemini-3-pro-image-preview
aspect-ratio: 1:1
flags: []
---

Full prompt text. Be explicit about subject, style, background, constraints.

mkdir -p prompts

For series: write ALL prompt files before calling any generation script.

Gate: all prompt files written and reviewed.

Phase 3: Select Script

Use case	Script	Subcommand
Single image, Gemini	`scripts/generate_image.py`	`--prompt`
Batch from text file, Gemini	`scripts/generate_image.py`	`--batch`
Single with post-processing	`scripts/nano-banana-generate.py`	`generate`
Style match from reference	`scripts/nano-banana-generate.py`	`with-reference`
Batch from JSON manifest	`scripts/nano-banana-generate.py`	`batch`
Series (anchor chain)	`scripts/nano-banana-generate.py`	`generate` then `with-reference`
Post-processing only	`scripts/nano-banana-process.py`	`crop` / `remove-bg` / `pipeline`

Model selection:

Scenario	Model
Draft, testing, batch, cost-sensitive	`gemini-2.5-flash-image` (2-5s)
Final asset, character art, typography	`gemini-3-pro-image-preview` (~30s)

Aspect ratio by use case:

Asset type	Ratio
Sprites, characters, icons	`1:1`
Card art, landscape	`16:9`
Vertical maps, portrait bg	`9:16`
Portrait cards	`3:4`
Wide banners	`21:9`

Generate at the target ratio. Generating 1:1 and cropping to 16:9 loses 56% of pixels.

Gate: script and subcommand identified.

Phase 4: Generate

Use absolute paths for output files. Show full script output.

Anchor-Chain Algorithm (Series)

Character drift occurs when images are generated independently. Prevent it by passing the previous output as --reference:

image-01.png (no ref) -> image-02.png (ref=01) -> image-03.png (ref=02) -> ...

Generate image 1 with no reference.
Use output of image 1 as --reference for image 2.
Continue: each image N references image N-1.

Save originals with --save-original for any batch or expensive generation. Re-processing a saved original is free; re-generating costs quota and may break the chain.

Gate: script exits 0.

Phase 5: Verify and Report

Read the generated image to verify:

Subject matches prompt
No unwanted watermarks or artifacts
Aspect ratio and framing correct
No excessive padding or dark borders

If inspection fails: regenerate with adjusted prompt. Report the issue before retrying.

Report: output file path (absolute), dimensions, model, post-processing applied, verification result. Report only what was requested.

Error Handling

Error	Cause	Resolution
`GEMINI_API_KEY not set`	Missing env var	`export GEMINI_API_KEY=your_key`
`No image in response`	Safety filter or text-only response	Adjust prompt; remove policy-adjacent content
`Missing dependency: google-genai`	Package absent	`pip install google-genai pillow`
`Rate limit exceeded (429)`	Too many requests	Increase `--delay`; script retries automatically
`Content policy violation (400)`	Restricted content	Rephrase using neutral language
Model not found	Wrong model string	Use exact strings: `gemini-2.5-flash-image` or `gemini-3-pro-image-preview`

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Adopted by

Most recently taken up by

Used with

spotify

trello

daily-briefing

paid-ads

weather

summarize

Word for word · 1

Edited · 0

Wrote their own version · 48

The file

8 rules. 0 are common, 7 are distinctive, and 1 is very specific to this project.

image-gen

Deep References

Phase 1: Detect Backend

Phase 2: Write Prompt Files

Phase 3: Select Script

Phase 4: Generate

Anchor-Chain Algorithm (Series)

Phase 5: Verify and Report

Error Handling

Does it work?

No reviews yet

Your trail

Now do this for your own.