AD modelscope-image
魔搭(ModelScope)AI 图片生成。支持多种模型、LoRA 微调。触发词：生成图片、AI绘画、文生图、image generation、generate image。当用户要求生成图片、画图、AI 作画，或提到魔搭、ModelScope时使用。
As a process D 38/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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: 5. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 38/100
- 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
- 40Consistency. Frontmatter name (modelscope-image) differs from the folder (modelscope-img)
- 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
- 75Steps. 3 steps
- 100Execution cost. Instruction body is 385 tokens
- 100Running it twice. No mutating operations
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 126: enough signal without eating the budget
- +4Structure: 4 headings
- +3Step-by-step instructions: 3 items
- +4Has examples (5 code blocks)
- +3All 2 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.
External checks
ClawHub: clean
This is a straightforward ModelScope image-generation helper with disclosed API-key use, network calls, and local image output, though users should treat saved keys and prompts as sensitive.
LLM: benign (high) · VirusTotal: · 29 May 2026