SKILLEMALL.ai

BD breakup-decision

"分还是不分"关系决策分析 Skill。用户描述一段感情的现状和困惑,AI 扮演犀利毒舌的 Mean Girl 闺蜜,通过结构化维度评估帮用户看清关系本质,给出理性但直接的分析和建议。 触发场景包括: - 明确询问分不分手:分还是不分、要不要分手、纠结要不要分、我不知道要不要和他/她分手 - 感情困惑倾诉:这段关系值不值得继续、帮我分析这段感情、我感情上好累、不知道该怎么办 - 吐槽伴侣:他/她又这样了、跟他/她在一起很累、他/她总是…、我男朋友/女朋友/对象… - 关系状态描述:我们最近经常吵架、他/她不理我、感觉没有以前了、我们好像走不下去了 - 纠结留还是走:舍不得但又很累、想分但下不了决心、不知道要不要给机会、还要不要继续 - 感情迷茫:说不清楚是不是还爱、感觉快到头了、心里有点感觉不对、这段感情还有救吗 - 发送聊天记录:直接粘贴/截图/发送与伴侣/对象/前任的聊天记录,无论是图片截图、文字粘贴还是任何形式,只要内容是两人对话或感情相关,都应触发本 Skill 进行分析

ClawHub Agent Skills author: sachi-PP v1.0.2 MIT-0 7 files body ≈ 396 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
89/100
safety, quality, tests
Safety 60%
100
Quality 40%
72
Run on models
none yet
Process rating
D
49/100
Unfinished process
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

  1. 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: 7. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 49/100

  • 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
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 40Consistency. Frontmatter name (breakup-decision) differs from the folder (dump-or-not)
  • 100Tools and files. No external tools needed
  • 100Steps. 28 steps
  • 100Execution cost. Instruction body is 396 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
  • +4No input/output examples
  • +1No license
  • +2Single-language instructions
  • +3Description length 446: enough signal without eating the budget
  • +4Structure: 10 headings
  • +3Step-by-step instructions: 28 items
  • +4Reference files are cited in the instructions (3 of 3)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.

External checks

ClawHub: suspicious
This relationship-advice skill is mostly coherent, but it automatically pushes sensitive chats into local rendering files and a background web server to send an image card.
LLM: suspicious (high) · VirusTotal: · 29 May 2026