SKILLEMALL.ai

AC emotion-switch

在 qiqing-liuyu 技能的基础上,为 AI 增加「显式情绪底色」控制层。用户可以命令 AI 以某种情绪状态持续对话,直到明确切换为止。支持强度级别(1–5)。 **触发条件(用户在命令 AI 的情绪,而非表达自己的情绪):** (1) 用户要求 AI 进入某种情绪状态 —— "用难过的情绪跟我聊" / "切换到烦躁" / "你现在很开心" (2) 用户想让 AI 在整段对话里保持某种稳定的情绪底色 (3) 用户提到「emotion-switch」「情绪切换」「切换情绪」「以 XXX 的情绪」「用 XXX 的状态」 (4) 用户为 AI 指定含情绪词的角色身份 —— "你现在是一个很焦虑的客服,情绪按焦虑:3执行" **不触发的情况:** 用户表达自己的情绪("我今天很丧" / "我最近有点焦虑")——这类交由 qiqing-liuyu 共情响应,不启动本技能。 本 Skill 依赖 qiqing-liuyu 作为底座,二者同时激活时协同运行。

ClawHub Agent Skills author: npccxx v1.1.3 MIT-0 4 files body ≈ 801 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
77
Run on models
none yet
Process rating
C
53/100
Has gaps
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: 4. 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 53/100

  • 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
  • 100Tools and files. No external tools needed
  • 100Steps. 15 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 801 tokens
  • 100Running it twice. No mutating operations
  • low 13 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
  • +4No input/output examples
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 4 example trigger phrases
  • +3Description length 435: enough signal without eating the budget
  • +4Structure: 14 headings
  • +3Step-by-step instructions: 15 items
  • +4Reference files are cited in the instructions (1 of 2)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.

External checks

ClawHub: clean
This is a text-only style skill that changes the assistant’s conversational emotion tone and does not add code execution, data access, or external connections.
LLM: benign (high) · VirusTotal: · 29 May 2026