SKILLEMALL.ai

BF drivethru-graphic-artist

Graphic-artist tasks for Bacon & Co decorations — (1) generate product mockups by compositing a decoration (logo/graphic) onto a blank product photo (deterministic; no model-generated pixels; self-reviewed), (2) make a DTF decoration "production-ready" / "drop the art" — take the real thumbnail, size it to the decoration location, render at 300 DPI, upload the DTF production file, set size + colors, and create a print sample, driving the decoration toward the 'done' state via the drivethru_mcp decoration_* tools, and (3) clean up degraded / AI-generated flat art before production — deterministically snap it back to its true inks, rebuild faded/broken/jagged outlines, and re-render crisp at print size (fixes the "looks fine as a thumbnail, falls apart at 13 inches" problem). Use whenever the user wants to see a logo on a garment, place artwork on a blank, remove an image background (knock a solid color out of flat art, or segment a photographic subject), tune a print's size/position, clean up / fix / "drop for production" a low-quality or AI-generated logo (ghosting, haze, jagged or fading outlines, soft edges), OR make a decoration production-ready / drop art / get a DTF decoration to done.

ClawHub Agent Skills author: zmtucker v0.12.0 MIT-0 24 files body ≈ 6 383 tokens Open the sourceclawhub.ai analyzed 3 d ago

Graphic-artist tasks for Bacon & Co decorations — (1) generate product mockups by compositing a decoration (logo/graphic) onto a blank product photo…

As a process F 58/100 · Will not run — References files that are not bundled: assets/decoration_guide.png, references/decoration_spec_sheet.pdf

GeneratorDesigntype and topics are labelled automatically from the skill text
JSON
Technical rating
B
77/100
safety, quality, tests
Safety 60%
100
Quality 40%
42
Run on models
none yet
Process rating
F
58/100
Will not run
References files that are not bundled: assets/decoration_guide.png, references/decoration_spec_sheet.pdf
Tools and files w 18
0
Result and completion w 14
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

How to improve

  1. Shorten the description to 1024 characters.
  2. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
  3. The text references files that are not there: add them or drop the references.
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: 24. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • error description-long description is 1209 chars, limit 1024
  • warning body-long SKILL.md body ≈ 6383 tokens (recommended < 5000); move details to references/
  • warning missing-ref reference to a missing file: assets/decoration_guide.png
  • warning missing-ref reference to a missing file: references/decoration_spec_sheet.pdf
  • note frontmatter-key unknown frontmatter key "emoji"

Process rating: all ten parameters 58/100

Will not run. References files that are not bundled: assets/decoration_guide.png, references/decoration_spec_sheet.pdf
  • 0Tools and files. 2 referenced file(s) missing: assets/decoration_guide.png, references/decoration_spec_sheet.pdf
  • 0Result and completion. Does not say what the result is
  • 30Running it twice. 24 mutating operations with no state check
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 70Execution cost. Instruction body is 6383 tokens
  • 85Steps. 32 steps, 3 vague phrases
  • 100When it triggers. States when to use and when not to
  • 100Failures and branches. 2 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 15 top-level sections: this looks like several domains in one skill

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)
  • +3Description length 1209: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -31 of 12 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 4 example trigger phrases
  • +4Structure: 20 headings
  • +3Step-by-step instructions: 32 items
  • +4Has examples (8 code blocks)
  • +4Reference files are cited in the instructions (7 of 7)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 42.

External checks

ClawHub: suspicious
The skill is legitimate graphic-production automation, but it needs Review because it can make persistent Odoo business-record changes using bearer credentials and raw HTTP uploads with weak destination controls.
LLM: suspicious (high) · 8 Sept 2026