AD wechat-auto-reply
微信消息自动发送/半自动回复。主动发送时，按“搜索联系人→单聊直接 Enter 进入聊天；群聊先识别群聊分组再定位目标项→粘贴消息→发送”的逻辑执行。适用于 macOS + 微信桌面版环境，需本机完成权限和依赖配置。使用方式：wechat-auto-reply "联系人名称" 或 wechat-auto-reply "联系人名称" "消息内容"
As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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: 5. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 46/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 40Consistency. Frontmatter name (wechat-auto-reply) differs from the folder (wechat-auto-reply-mac)
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 100Steps. 50 steps
- 100Execution cost. Instruction body is 1258 tokens
- 100Running it twice. No mutating operations
- low 11 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
- +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
- +5Description quotes 2 example trigger phrases
- +3Description length 173: enough signal without eating the budget
- +4Structure: 34 headings
- +3Step-by-step instructions: 50 items
- +4Has examples (15 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.
External checks
ClawHub: suspicious
This skill is aligned with WeChat automation, but it needs Review because it can send messages from a logged-in account, captures chat UI for OCR, and delegates the main runtime behavior to an AppleScript file that is not included in the reviewed artifact.
LLM: suspicious (high) · VirusTotal: · 29 May 2026