SKILLEMALL.ai

AB wechat-desktop-sender

Windows WeChat desktop automation for opening chats and sending messages. Use when the user wants to open 微信桌面端, search a contact or group, send a message, send the same message to multiple contacts/groups in serial batch mode, or send personalized messages where each recipient gets different content. Best for direct desktop WeChat messaging workflows like 文件传输助手 testing, one-to-one outreach, 串行群发, and名单驱动个性化发送. Not for browser WeChat,朋友圈 scraping, or reliable historical-message forwarding.

ClawHub Agent Skills author: Koi v0.4.0 MIT-0 13 files body ≈ 930 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process B 67/100 · Nearly there — weak spots: result and completion, inputs and preconditions, running it twice

ProcedureInfrastructureSales and CRMtype and topics are labelled automatically from the skill text
JSON
Technical rating
A
98/100
safety, quality, tests
Safety 60%
100
Quality 40%
95
Run on models
none yet
Process rating
B
67/100
Nearly there
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: 13. 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 67/100

    • 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. 22 mutating operations with no state check
    • 50Failures and branches. 0 branches, has a failure section
    • 100Tools and files. No external tools needed
    • 100Steps. 36 steps
    • 100When it triggers. States when to use and when not to
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 930 tokens
    • 100Progress reporting. Reports progress
    • low 12 top-level sections: this looks like several domains in one skill

    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
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 495: enough signal without eating the budget
    • +4Structure: 13 headings
    • +3Step-by-step instructions: 36 items
    • +4Has examples (8 code blocks)
    • +4Reference files are cited in the instructions (4 of 4)
    • +3All 5 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 95.

    External checks

    ClawHub: suspicious
    This skill matches its WeChat automation purpose, but it can send real messages in bulk and persist sensitive contact, message, screenshot, and UI data with limited safeguards.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026