SKILLEMALL.ai
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AB free-quota-image-skill

Generate images from text with a free-quota-first multi-provider workflow. Use this skill when a user asks for text-to-image generation that needs provider routing (Hugging Face, Gitee, ModelScope, A4F, OpenAI-compatible private endpoints), token pooling with automatic rotation on quota/auth failures, public API fallback for Hugging Face, prompt optimization, model fallback, batch generation in one command, and structured generation outputs.

ClawHub Agent Skills author: ChiayenGu v1.0.0 15 files body ≈ 816 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process B 72/100 · Nearly there — weak spots: when it triggers, inputs and preconditions, progress reporting

ProcedureSales and CRMAI 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
B
72/100
Nearly there
Inputs and preconditions w 11
0
Progress reporting w 2
0
When it triggers w 12
20
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: 15. 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 72/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 60Result and completion. Output format stated, no completion criterion
    • 100Tools and files. No external tools needed
    • 100Steps. 47 steps
    • 100Failures and branches. 1 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 816 tokens
    • 100Running it twice. No mutating operations

    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)
    • -34 of 5 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +3Description length 445: enough signal without eating the budget
    • +4Structure: 8 headings
    • +3Step-by-step instructions: 47 items
    • +3Output format is stated explicitly
    • +4Has examples (5 code blocks)
    • +4Reference files are cited in the instructions (5 of 5)

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

    External checks

    ClawHub: clean
    The skill is a coherent text-to-image helper that uses external image providers as advertised, but users should treat prompts, tokens, and configured endpoints as privacy-sensitive.
    LLM: benign (high) · VirusTotal: · 29 May 2026