AC nano-banana-pro
Use Nano Banana 2 (Gemini 3.1 Flash Image), the newest image model focused on faster iteration, lower cost, and strong quality. Published 2026-02-26 as the latest Flash-image generation family update. Supports image generation/edit, image-to-image, and 1K/2K/4K.
The same skill from clawhub has been run on models: Active A see the result → This is a copy: its text may differ, so the grade is not carried over.
Use Nano Banana 2 (Gemini 3.1 Flash Image), the newest image model focused on faster iteration, lower cost, and strong quality. Published 2026-02-26 as the…
As a process C 60/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, consistency
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: 4. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 60/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 40Consistency. Frontmatter name (nano-banana-pro) differs from the folder (nano-banana-pro-fork)
- 55Failures and branches. 1 branches
- 60Result and completion. Output format stated, no completion criterion
- 85Steps. 47 steps, 1 vague phrases
- 100Tools and files. No external tools needed
- 100Execution cost. Instruction body is 1625 tokens
- 100Running it twice. Mutating operations check current state
- low 12 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (5 tags): a typed call is more reliable
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 262: enough signal without eating the budget
- +4Structure: 13 headings
- +3Step-by-step instructions: 47 items
- +3Output format is stated explicitly
- +4Has examples (4 code blocks)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 90.