SKILLEMALL.ai

AB product-photography

Turn a plain product shot or packshot into clean studio, lifestyle, or hero imagery for e-commerce and ads. Use when the user says "make this a product photo", "studio shot of my product", "put it on a white background", "lifestyle shot for my store", "hero image for the ad", "relight this packshot", or wants catalog-ready product images. Often a pipeline: generate or clean, cut the background, then relight. For photoreal images of people, food, or scenes with no product focus, use photoreal-stills. To merge a product into an existing scene photo, use composite-scene.

ClawHub Agent Skills author: runware v1.0.0 MIT-0 3 files body ≈ 2 031 tokens Open the sourceclawhub.ai analyzed 4 d ago

As a process B 74/100 · Nearly there — weak spots: result and completion, running it twice, progress reporting

GeneratorInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
89
Run on models
none yet
Process rating
B
74/100
Nearly there
Result and completion w 14
0
Progress reporting w 2
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

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: 3. 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 74/100

    • 0Result and completion. Does not say what the result is
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 3 mutating operations with no state check
    • 70When it triggers. States when to use, but not when not to
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Tools and files. No external tools needed
    • 100Steps. 45 steps
    • 100Failures and branches. 2 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2031 tokens

    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

    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 6 example trigger phrases
    • +3Description length 574: enough signal without eating the budget
    • +4Structure: 8 headings
    • +3Step-by-step instructions: 45 items
    • +4Reference files are cited in the instructions (1 of 1)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 89.

    External checks

    ClawHub: clean
    This skill gives coherent product-photography workflow guidance and does not contain hidden execution, persistence, or unrelated data access.
    LLM: benign (high) · VirusTotal: · 18 Jul 2026