BC ecommerce-aftersales-responder
电商售后客服规范应答生成器。支撑客服人员针对退换货申请、物流异常咨询、售后补偿协商三类高频售后诉求， 快速生成符合品牌服务规范的统一话术。适用场景：(1) 用户发起退货/换货/退款申请需客服审核回复， (2) 用户咨询物流延误、丢件、破损等异常问题，(3) 用户对售后处理不满需协商补偿方案（优惠券、补发、折价等）。 当对话涉及电商售后、退换货、物流异常、售后补偿、客服话术、服务规范等关键词时触发。
As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- 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: 5. 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")
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 202 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 200: enough signal without eating the budget
- +4Structure: 4 headings
- +3Step-by-step instructions: 15 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: clean
This is a text-only Chinese e-commerce customer-service drafting skill with no code execution, credentials, persistence, or hidden data movement.
LLM: benign (high) · VirusTotal: · 29 May 2026