BF Nano-Banana-V2
AI image generation and smart splitting tool based on AceData Nano Banana model. Supports multiple resolutions and sizes, automatic 2/4/6/9 grid splitting, waterfall gallery management, and batch download. Supports 5 languages: Chinese, English, Traditional Chinese, Japanese, Korean.
As a process F 28/100 · Will not run — References files that are not bundled: docs/zh/SKILL.md
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- The text references files that are not there: add them or drop the references.
- 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: 29. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 3, column 14: description: AI image generation and smart splitting tool based on AceData Nano… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value - warning
name-formatname should be kebab-case (lowercase letters, digits, hyphens) - warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - warning
missing-refreference to a missing file: docs/zh/SKILL.md - note
frontmatter-keyunknown frontmatter key "email" - note
frontmatter-keyunknown frontmatter key "wechat" - note
frontmatter-keyunknown frontmatter key "icon" - note
frontmatter-keyunknown frontmatter key "homepage" - note
frontmatter-keyunknown frontmatter key "repository"
Process rating: all ten parameters 28/100
- 0Tools and files. 1 referenced file(s) missing: docs/zh/SKILL.md
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 4 mutating operations with no state check
- 40Consistency. Frontmatter name (Nano-Banana-V2) differs from the folder (banana-v2)
- 100Steps. 53 steps
- 100Execution cost. Instruction body is 1308 tokens
- low 11 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)
- +3Output format is not stated: the model decides each time
- -2localhost URLs: will not work for another user
- +2Single-language instructions
- +3Description length 284: enough signal without eating the budget
- +4Structure: 30 headings
- +3Step-by-step instructions: 53 items
- +4Has examples (3 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 47.