AB image-generation-agent
Image Generation Agent: Google Gemini-powered image generation tool (Nano Banana / Gemini 2.5 & 3 Flash Image). Use this to generate images from a text prompt, produce low-cost draft previews, or render high-resolution finals at 0.5K, 1K, 2K, or 4K. Use when an agent needs image generation agent, ai image generation, nano banana image creation, google gemini image api, text to image, generate budget image, prompt, aspect ratio through AgentPMT-hosted remote tool calls.
Image Generation Agent: Google Gemini-powered image generation tool (Nano Banana / Gemini 2.5 & 3 Flash Image). Use this to generate images from a text…
As a process B 76/100 · Nearly there — weak spots: running it twice, progress reporting
How to improve
- 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: 3. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- note
frontmatter-keyunknown frontmatter key "homepage"
Process rating: all ten parameters 76/100
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 9 mutating operations with no state check
- 60Tools and files. Uses tools (web) 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
- 100Steps. 69 steps
- 100Failures and branches. 2 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3212 tokens
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 13 top-level sections: this looks like several domains in one skill
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
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +1No license
- +2Single-language instructions
- +3Description length 473: enough signal without eating the budget
- +4Structure: 20 headings
- +3Step-by-step instructions: 69 items
- +3Output format is stated explicitly
- +4Has examples (11 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 86.