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BB ad-ready

Generate professional advertising images from product URLs using the Ad-Ready pipeline on ComfyDeploy. Use when the user wants to create ads for any product by providing a URL, optionally with a brand profile (70+ brands) and funnel stage targeting. Supports model/talent integration, brand-aware creative direction, and multi-format output. Differs from Morpheus (manual fashion photography) — Ad-Ready is URL-driven, brand-intelligent, and funnel-stage aware.

ClawHub Agent Skills author: Paul de Lavallaz v1.4.0 14 files body ≈ 5 148 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process B 65/100 · Nearly there — weak spots: consistency, progress reporting

GeneratorMarketingtype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
89/100
safety, quality, tests
Safety 60%
97
Quality 40%
78
Run on models
none yet
Process rating
B
65/100
Nearly there
Progress reporting w 2
0
Consistency w 8
40
Tools and files w 18
60
the three weakest of ten parameters · all ten
This is a copy of a skill from another catalog; the rating counts the canonical one: ad-ready (ClawHub)

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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 · 3

✓ No critical or high findings

Medium and low: 3
  • low Secrets in code secret-high-entropy-token scripts/generate.py:55
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "Mast…ion",
    quoted
  • low Secrets in code secret-high-entropy-token scripts/generate.py:61
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "Mast…ive"
    quoted
  • low Secrets in code secret-high-entropy-token scripts/generate.py:371
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    parser.add_argument("--prompt-profile", default="Mast…ive",
    detector

Files scanned: 14. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 5148 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 65/100

  • 0Progress reporting. Says nothing while it works
  • 40Consistency. Frontmatter name (ad-ready) differs from the folder (product-to-ads)
  • 60Tools and files. Uses tools (bash, web, node) that frontmatter does not declare
  • 60Result and completion. Output format stated, no completion criterion
  • 60Failures and branches. 2 branches
  • 70When it triggers. States when to use, but not when not to
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 70Execution cost. Instruction body is 5148 tokens
  • 85Steps. 51 steps, 1 vague phrases
  • 100Running it twice. Mutating operations check current state
  • 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

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • -212 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 461: enough signal without eating the budget
  • +4Structure: 39 headings
  • +3Step-by-step instructions: 51 items
  • +3Output format is stated explicitly
  • +4Has examples (9 code blocks)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.

External checks

ClawHub: suspicious
The skill matches its ad-generation purpose, but its auto-fetch path can retrieve arbitrary URLs and upload the result to a cloud service, and its talent prompts require sensitive appearance handling.
LLM: suspicious (high) · VirusTotal: benign · 10 Sept 2026