SKILLEMALL.ai

BC email-apology-zh

专为客服、项目管理及日常职场场景设计的专业道歉邮件生成工具。适用于服务延误、 发货推迟、系统故障、数据错误、承诺未兑现等各类需要正式致歉的情况。能够生成 语气诚恳、结构清晰的道歉邮件/致歉函/补救邮件,包含问题说明、责任承担、具体 补救措施与后续预防方案,帮助快速挽回客户或合作方信任。同义词覆盖:道歉信、 延误通知、错误处理邮件、补救说明、致歉函。

ClawHub Agent Skills author: Olina1Ye v1.0.0 MIT-0 2 files body ≈ 171 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

ReferenceInfrastructuretype 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
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: 2. 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. 6 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 171 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
  • +1No license
  • +2Single-language instructions
  • +3Description length 175: enough signal without eating the budget
  • +4Structure: 4 headings
  • +3Step-by-step instructions: 6 items
  • +4Has examples (0 code blocks)

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

External checks

ClawHub: clean
This is a simple Chinese apology-email drafting skill with no code, dependencies, network use, or hidden actions; the only notable point is its broad read/write tool declaration.
LLM: benign (high) · VirusTotal: · 29 May 2026