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中文平台(微信表情开放平台 / 小红书 / 抖音)合规表情包生成助手。提供平台尺寸硬约束裁切与命名、违禁词校验(实时 API + 离线兜底)、静态贴纸转内容匹配动效 GIF、合规参考数据维护与平台规范规则巡检工作流。

ClawHub Agent Skills author: Bonnie Geng v3.1.0 MIT-0 12 files body ≈ 1 764 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

中文平台(微信表情开放平台 / 小红书 / 抖音)合规表情包生成助手。提供平台尺寸硬约束裁切与命名、违禁词校验(实时 API + 离线兜底)、静态贴纸转内容匹配动效 GIF、合规参考数据维护与平台规范规则巡检工作流。

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationInfrastructuretype 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
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
86
Run on models
none yet
Process rating
C
53/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
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: 12. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "trigger"
    • note frontmatter-key unknown frontmatter key "agent_created"
    • note frontmatter-key unknown frontmatter key "tools"

    Process rating: all ten parameters 53/100

    • 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
    • 100Tools and files. Tools declared in frontmatter
    • 100Steps. 59 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1764 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)
    • +3Description length 108: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • +2Single-language instructions
    • +4Structure: 13 headings
    • +3Step-by-step instructions: 59 items
    • +4Has examples (3 code blocks)
    • +4Reference files are cited in the instructions (4 of 4)
    • +3All 3 scripts are documented
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 86.

    External checks

    ClawHub: clean
    The skill is a coherent Chinese sticker-generation helper with expected image-processing and compliance-checking behavior, but users should be aware it can prefer an external compliance checker and uses unpinned install commands.
    LLM: benign (medium) · VirusTotal: · 10 Sept 2026