AB ModelScope-Img
Generate images with ModelScope API. Use for image generation requests. Supports text-to-image + image-to-image; configurable models; use --input-image.
As a process B 65/100 · Nearly there — weak spots: when it triggers, consistency, progress reporting
How to improve
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: 4. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
name-formatname should be kebab-case (lowercase letters, digits, hyphens)
Process rating: all ten parameters 65/100
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 40Consistency. Frontmatter name (ModelScope-Img) differs from the folder (modelscope-img-generator)
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 70Inputs and preconditions. Inputs and preconditions are listed
- 70Failures and branches. 4 branches
- 100Steps. 45 steps
- 100Execution cost. Instruction body is 1590 tokens
- 100Running it twice. Mutating operations check current state
- low 13 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (3 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 152: enough signal without eating the budget
- +4Structure: 14 headings
- +3Step-by-step instructions: 45 items
- +3Output format is stated explicitly
- +4Has examples (7 code blocks)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.
External checks
ClawHub: clean
This skill is a straightforward ModelScope image generator, with one documentation gap around where returned images are downloaded from.
LLM: benign (high) · VirusTotal: · 29 May 2026