BF wechat-qwen-reply
WeChat chat reader + auto-reply (Qwen-VL vision + AHK send). Supports fast/slow capture, group nickname labels, file/red-packet cards, and filtering system messages on Windows.
As a process F 35/100 · Will not run — References files that are not bundled: scripts/wechat_capture_fast.ps1, scripts/wechat_capture_crop.ps1, scripts/wechat_send_chat.ahk
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- The text references files that are not there: add them or drop the references.
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
description-no-whendescription does not say WHEN to use the skill (no "use when") - warning
missing-refreference to a missing file: scripts/wechat_capture_fast.ps1 - warning
missing-refreference to a missing file: scripts/wechat_capture_crop.ps1 - warning
missing-refreference to a missing file: scripts/wechat_send_chat.ahk
Process rating: all ten parameters 35/100
Will not run. References files that are not bundled: scripts/wechat_capture_fast.ps1, scripts/wechat_capture_crop.ps1, scripts/wechat_send_chat.ahk
- 0Tools and files. 3 referenced file(s) missing: scripts/wechat_capture_fast.ps1, scripts/wechat_capture_crop.ps1, scripts/wechat_send_chat.ahk
- 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
- 100Steps. 15 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 237 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
- -4Absolute local paths (C:\Users, /home/…): not portable
- +1No license
- +2Single-language instructions
- +3Description length 176: enough signal without eating the budget
- +4Structure: 9 headings
- +3Step-by-step instructions: 15 items
- +4Has examples (3 code blocks)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 59.
External checks
ClawHub: suspicious
This skill is meant to read WeChat chats with Qwen-VL, but it handles private chat screenshots and local automation with too much unreviewed or under-scoped behavior for automatic approval.
LLM: suspicious (high) · VirusTotal: · 29 May 2026