SKILLEMALL.ai

AB image-generation-studio

Generate or edit images with the image-generation-studio CLI through supported adapters (`gemini`, `openai_images`, `openai_responses`) and user-configured providers, endpoints, models, and aliases. Use this skill whenever the user wants to create, edit, compose, or restyle images — including prompts like "make an image", "generate a picture", "edit this photo", "combine these images", "4K poster", or mentions of configured image providers/models such as "Gemini image", "Grok image", "xAI image", "OpenAI image", "OpenAI Responses", "custom image provider", or "gpt-image".

ClawHub Agent Skills author: limkim v1.2.0 MIT-0 7 files body ≈ 1 376 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process B 73/100 · Nearly there — weak spots: running it twice, progress reporting

IntegrationAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
99/100
safety, quality, tests
Safety 60%
100
Quality 40%
98
Run on models
none yet
Process rating
B
73/100
Nearly there
Progress reporting w 2
0
Running it twice w 4
30
Tools and files w 18
60
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
    • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

    Guard findings · 0

    ✓ No critical or high findings

    Files scanned: 7. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "requires"

    Process rating: all ten parameters 73/100

    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 1 mutating operations with no state check
    • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70When it triggers. States when to use, but not when not to
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 85Steps. 12 steps, 1 vague phrases
    • 100Failures and branches. 2 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1376 tokens

    Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

    Quality signals

    • +4Description does not say when NOT to use the skill (false activations)
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 12 example trigger phrases
    • +3Description length 578: enough signal without eating the budget
    • +4Structure: 10 headings
    • +3Step-by-step instructions: 12 items
    • +3Output format is stated explicitly
    • +4Has examples (2 code blocks)
    • +4Reference files are cited in the instructions (4 of 4)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 98.

    External checks

    ClawHub: clean
    This skill is a disclosed image-generation CLI wrapper that uses API keys and provider endpoints as expected, with some integration risks around custom endpoints and URL downloads.
    LLM: benign (medium) · VirusTotal: · 14 Jun 2026