SKILLEMALL.ai

CC ecommerce-image-workflow

Reference-product ecommerce image workflow for generating a compact set of product-faithful main, feature, and lifestyle images from real product reference photos. V1 requires uploaded product imagery and intentionally defers brief-only concept generation and platform-specific batch exports.

nexu-io/open-design Agent Skills author: nexu-io Apache-2.0 3 files body ≈ 2 124 tokens Open the sourcegithub.com↗ analyzed 6 d ago

Reference-product ecommerce image workflow for generating a compact set of product-faithful main, feature, and lifestyle images from real product reference…

As a process C 60/100 · Has gaps — weak spots: result and completion, when it triggers, running it twice

ProcedureAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
C
89/100
safety, quality, tests
Safety 60%
100
Quality 40%
73
Run on models
none yet
Process rating
C
60/100
Has gaps
Result and completion w 14
0
When it triggers w 12
20
Running it twice w 4
30
the three weakest of ten parameters · all ten

How to improve

  1. 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: 3. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "en_name"
  • note frontmatter-key unknown frontmatter key "triggers"
  • note frontmatter-key unknown frontmatter key "od"

Process rating: all ten parameters 60/100

  • 0Result and completion. Does not say what the result is
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 6 mutating operations with no state check
  • 60Tools and files. Uses tools (bash) that frontmatter does not declare
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 70Failures and branches. 4 branches
  • 100Steps. 45 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2124 tokens
  • 100Progress reporting. Reports progress

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 292: enough signal without eating the budget
  • +4Structure: 17 headings
  • +3Step-by-step instructions: 45 items
  • +4Has examples (4 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.