SKILLEMALL.ai
GitHub ↗ RU Sign in

AD prompt-artist

Optimize and generate text-to-image prompts for AI art platforms. Use when a user wants to: (1) Optimize prompts for Midjourney, Nano Banana, Dreamina, Qwen image generation, (2) Translate simple descriptions into professional prompts, (3) Generate platform-specific prompt variations, (4) Add style/lighting/composition modifiers, (5) Create negative prompts. Supports Chinese/English input. Integrates SkillPay.me at 0.005 USDT/call.

ClawHub Agent Skills author: elevo11 v1.1.0 9 files body ≈ 388 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process D 36/100 · Unfinished process — weak spots: steps, result and completion, when it triggers

GeneratorAI and agentstype 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
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
88
Run on models
none yet
Process rating
D
36/100
Unfinished process
Steps w 15
0
Result and completion w 14
0
Inputs and preconditions w 11
0
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: 9. 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 36/100

    • 0Steps. Prose only: no discrete steps
    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 1 mutating operations with no state check
    • 100Tools and files. No external tools needed
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 388 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

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +3No numbered steps or checklist
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +3Description length 435: enough signal without eating the budget
    • +4Structure: 6 headings
    • +4Has examples (2 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)
    • +3All 5 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.

    External checks

    ClawHub: suspicious
    This prompt tool appears legitimate, but it can charge a SkillPay account by default and stores prompt history locally, so it needs review before use.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026