SKILLEMALL.ai

BC windows-wechat-mcp

Windows WeChat message monitoring and sending. Achieved through window automation: screenshot, search contacts, send messages. Use when needing to send messages to WeChat contacts, check WeChat window status, or perform WeChat-related automation tasks.

ClawHub Agent Skills author: OpenLark v1.0.0 MIT-0 3 files body ≈ 458 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, failures and branches

ProcedureInfrastructureAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
71
Run on models
none yet
Process rating
C
51/100
Has gaps
Result and completion w 14
0
Failures and branches w 10
0
Progress reporting w 2
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: 3. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • warning frontmatter-yaml SKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 2, column 14: description: Windows WeChat message monitoring and sending. Achieved through wi… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value

    Process rating: all ten parameters 51/100

    • 0Result and completion. Does not say what the result is
    • 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
    • 30Running it twice. 8 mutating operations with no state check
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 5 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 458 tokens

    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
    • -31 of 1 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +3Description length 252: enough signal without eating the budget
    • +4Structure: 9 headings
    • +3Step-by-step instructions: 5 items
    • +4Has examples (4 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.

    External checks

    ClawHub: suspicious
    This skill does what it says, but it lets an agent screenshot WeChat and send messages from the user's live desktop session without built-in confirmation or recipient checks.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026