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AC cloudbase-wechat-integration

CloudBase WeChat integration guide for Mini Program WeChat Pay, Mini Program virtual payment (虚拟支付, wx.requestVirtualPayment), Official Account JSAPI Pay, Native QR-code Pay, Official Account OAuth, openid handling, payment callbacks, and CloudBase Integration Center generated functions. This skill should be used when users ask to add, debug, or extend WeChat payment, virtual payment, or official-account flows on CloudBase.

ClawHub Agent Skills author: Booker Zhao v1.2.45 MIT-0 9 files body ≈ 1 744 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process C 57/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

IntegrationSoftware developmentInfrastructuretype 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
93/100
safety, quality, tests
Safety 60%
100
Quality 40%
83
Run on models
none yet
Process rating
C
57/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Running it twice w 4
30
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

    • note frontmatter-key unknown frontmatter key "alwaysApply"

    Process rating: all ten parameters 57/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 30Running it twice. 4 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 85Steps. 38 steps, 1 vague phrases
    • 100Failures and branches. 3 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1744 tokens
    • 100Progress reporting. Reports progress

    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)
    • +3Output format is not stated: the model decides each time
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +3Description length 427: enough signal without eating the budget
    • +4Structure: 11 headings
    • +3Step-by-step instructions: 38 items
    • +4Reference files are cited in the instructions (7 of 7)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 83.

    External checks

    ClawHub: clean
    This skill is a CloudBase WeChat payment and OAuth guide that keeps sensitive setup in the console and does not include executable code.
    LLM: benign (high) · VirusTotal: · 8 Sept 2026