AD jiuma-free-image-gen
九马AI免费图片生成技能。使用九马AI API进行文本到图片的生成，支持自定义图片尺寸和提示词。当用户需要根据文本描述生成图片时使用此技能。Jiuma AI's free image generation skill. Utilize the Jiuma AI API to generate images from text, supporting customizable image sizes and prompt words. This skill is employed when users need to generate images based on text descriptions.
As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
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: 6. 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 46/100
- 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
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 100Steps. 87 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1684 tokens
- 100Running it twice. No mutating operations
- low 21 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
- +1No license
- +2Single-language instructions
- +3Description length 304: enough signal without eating the budget
- +4Structure: 43 headings
- +3Step-by-step instructions: 87 items
- +4Has examples (11 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.