SKILLEMALL.ai

AC eq-polisher

高情商表达润色器(EQ Polisher)。三大核心功能:(1) 润色模式——将直白、生硬、易引发冲突的文字改写成高情商表达,触发:转高情商/帮我高情商表达/润色语气/改得委婉/EQ优化;(2) 场景应对模式——面对夸奖、面对难题、化解尴尬时提供高情商回应方案,触发:被夸奖怎么回/这个难题怎么回应/尴尬了怎么办等含夸奖/难题/尴尬/化解关键词的输入;(3) 回复建议模式——帮用户生成回复别人消息的得体范本,触发:高情商回复/怎么回/EQ回复/帮我想想怎么回。当用户意图涉及高情商沟通时使用此技能。

ClawHub Agent Skills author: chiling7 v1.2.0 MIT-0 4 files body ≈ 1 877 tokens Open the sourceclawhub.ai analyzed 36 h ago

高情商表达润色器(EQ Polisher)。三大核心功能:(1) 润色模式——将直白、生硬、易引发冲突的文字改写成高情商表达,触发:转高情商/帮我高情商表达/润色语气/改得委婉/EQ优化;(2)…

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

Proceduretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
74
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. 23 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1877 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
  • -248 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 250: enough signal without eating the budget
  • +4Structure: 31 headings
  • +3Step-by-step instructions: 23 items
  • +4Has examples (5 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.

External checks

ClawHub: clean
This skill is a disclosed Chinese communication-polishing helper with no executable code, persistence, credential handling, or hidden data access.
LLM: benign (high) · VirusTotal: · 23 Jul 2026