BC ai-photo-restyler
Turn a photo into anime, manga, comic, cartoon, watercolor, clay, or 3D character art while the person, pet, or product stays recognisable. This AI photo restyler works as a photo-to-anime converter and AI cartoonizer you can steer: apply a style like a filter over your own picture, or add style samples to steer the palette, line weight, and shading. A selfie, portrait, pet photo, product shot, or travel picture becomes illustration-style art for social avatars, profile pictures, sticker sets, posters, merchandise, and content series, with one chosen look repeated across a whole batch.
Turn a photo into anime, manga, comic, cartoon, watercolor, clay, or 3D character art while the person, pet, or product stays recognisable.
As a process C 63/100 · Has gaps — weak spots: result and completion, progress reporting
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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: 14. 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 63/100
- 0Result and completion. Does not say what the result is
- 0Progress reporting. Says nothing while it works
- 50When it triggers. No condition that starts the skill
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (bash) that frontmatter does not declare
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Steps. 17 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1940 tokens
- 100Running it twice. Mutating operations check current state
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
- -32 of 3 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +3Description length 592: enough signal without eating the budget
- +4Structure: 9 headings
- +3Step-by-step instructions: 17 items
- +4Has examples (1 code blocks)
- +4Reference files are cited in the instructions (8 of 8)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.