AC image-upscaler
Upscale, inspect, or compress JPG, PNG, or WebP images locally on macOS or Windows, including automatic or user-selected photo, portrait, digital-art, sharp-detail, balanced, and fast profiles; 1K/2K/4K/8K output; custom long edges; strict target file sizes; batch folders; aspect-ratio preservation; offline reuse; and verified download fallbacks. Use when the user asks to make an image clearer, enlarge AI-generated art, compare enhancement algorithms, inspect image resolution, upscale without stretching, or reduce a larger image to a target such as 200KB.
Upscale, inspect, or compress JPG, PNG, or WebP images locally on macOS or Windows, including automatic or user-selected photo, portrait, digital-art…
As a process C 55/100 · Has gaps — weak spots: result and completion, 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: 12. 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 55/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 5 mutating operations with no state check
- 40Consistency. Frontmatter name (image-upscaler) differs from the folder (local-image-upscaler)
- 60Tools and files. Uses tools (web, python) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 100Steps. 24 steps
- 100Failures and branches. 1 branches, has a failure section
- 100Execution cost. Instruction body is 1941 tokens
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
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 561: enough signal without eating the budget
- +4Structure: 8 headings
- +3Step-by-step instructions: 24 items
- +4Has examples (8 code blocks)
- +4Reference files are cited in the instructions (3 of 3)
- +3All 4 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 91.