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AC douyin-messager

Douyin private messaging via browser automation. 抖音私信发送，通过浏览器自动化发送私信、获取聊天记录。Use when user needs to send 抖音私信、回复消息、查看聊天记录。Requires browser login. Triggers: 抖音, douyin, Douyin, TikTok中国, 抖音私信, douyin dm, douyin message, 抖音消息, 抖音发消息, send douyin message, 抖音聊天, douyin chat, 抖音回复, reply douyin, 获取抖音聊天记录, get douyin chat history, 抖音私信发送, send douyin dm, 给抖音用户发消息, message douyin user, 抖音私信自动化, douyin dm automation, 抖音私信工具, douyin messaging tool.

modbender/skill-library-mcp Agent Skills author: modbender MIT 1 file body ≈ 1 056 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Douyin private messaging via browser automation.

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

ProcedureMarketingSoftware developmenttype 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%
84
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: 1. 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 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. No external tools needed
    • 100Steps. 13 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1056 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)
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +3Description length 442: enough signal without eating the budget
    • +4Structure: 33 headings
    • +3Step-by-step instructions: 13 items
    • +4Has examples (18 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.