Batch-generate images via OpenAI Images API. Random prompt sampler + `index.html` gallery.
Install with Tessl CLI
npx tessl i github:qsimeon/openclaw-engaging --skill openai-image-gen72
Does it follow best practices?
If you maintain this skill, you can automatically optimize it using the tessl CLI to improve its score:
npx tessl skill review --optimize ./path/to/skillEvaluation — 92%
↑ 1.06xAgent success when using this skill
Validation for skill structure
DALL-E 3 model-specific parameters
Uses gen.py script
100%
100%
Uses dall-e-3 model
100%
100%
Valid dall-e-3 quality value
100%
100%
Quality is hd
100%
100%
Valid dall-e-3 size
100%
100%
Landscape size chosen
100%
100%
Uses --style flag
100%
100%
Style is vivid
100%
100%
No GPT-only flags
100%
100%
Count respects dall-e-3 limit
57%
100%
Without context: $0.3475 · 1m 34s · 15 turns · 22 in / 6,122 out tokens
With context: $0.4372 · 1m 22s · 21 turns · 236 in / 4,535 out tokens
GPT image model exclusive features (background, output-format)
Uses gen.py script
100%
100%
Uses GPT image model
50%
58%
Passes --background transparent
100%
100%
Passes --output-format webp
100%
100%
Does not use dall-e-2 or dall-e-3
100%
100%
No --style flag
100%
100%
Valid GPT quality if specified
100%
100%
No --quality hd
100%
100%
Valid GPT size if specified
100%
100%
OPENAI_API_KEY from environment
100%
100%
Without context: $0.2853 · 1m 19s · 13 turns · 68 in / 5,093 out tokens
With context: $0.2925 · 57s · 15 turns · 22 in / 2,932 out tokens
Pipeline automation, output structure, exec timeout, API key handling
Calls gen.py via python3
100%
100%
Subprocess timeout >= 300
0%
100%
Uses --out-dir flag
100%
100%
OPENAI_API_KEY from environment
83%
83%
No response_format parameter
100%
100%
Knows prompts.json output
0%
0%
Knows index.html output
100%
100%
Uses correct default model
100%
100%
Validates OPENAI_API_KEY present
0%
0%
No --style flag in pipeline
100%
100%
Without context: $0.4174 · 1m 42s · 16 turns · 23 in / 5,971 out tokens
With context: $0.6367 · 2m 11s · 23 turns · 490 in / 8,580 out tokens
Table of Contents
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