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小红书私信（DM）自动读取与回复，仅 Android（Nexior 手机端），经 Computer Use 无障碍直接操作小红书 App 的界面 —— 打开消息、读取未读私信、生成并（经用户确认后）发送回复。当用户提到：回小红书私信、小红书私信自动回复、小红书 DM、Xiaohongshu/RED 私信、帮我看/回小红书消息、回复主动私信来的人时使用。写操作（发送）一律先 dry-run 并经用户明确同意；受严格的安全红线与每日条数上限约束。

AceDataCloud/Skills Agent Skills author: AceDataCloud 1 file body ≈ 828 tokens Open the sourcegithub.com↗ analyzed 2 h ago

小红书私信（DM）自动读取与回复，仅 Android（Nexior 手机端），经 Computer Use 无障碍直接操作小红书 App 的界面 —— 打开消息、读取未读私信、生成并（经用户确认后）发送回复。当用户提到：回小红书私信、小红书私信自动回复、小红书 DM、Xiaohongshu/RED…

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

ProcedureAI and agentsSecuritytype and topics are labelled automatically from the skill text
Runs in: 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) OpenClaw Goose OpenCode
JSON
Technical rating
B
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
79
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

    • note frontmatter-key unknown frontmatter key "connections"
    • note frontmatter-key unknown frontmatter key "allowed_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
    • 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
    • 100Steps. 22 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 828 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
    • +2Single-language instructions
    • +3Description length 223: enough signal without eating the budget
    • +4Structure: 8 headings
    • +3Step-by-step instructions: 22 items
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.