AC ecommerce-returns-reply
电商客服退换货标准化应答提示词模板。用于生成符合平台售后规则、语气友好且信息准确的 退换货咨询回复。适用场景：(1) 买家咨询退货/换货流程，(2) 买家询问退款时效或运费承担， (3) 买家反馈商品质量问题需退换，(4) 买家对退换货被拒有疑问， (5) 任何涉及退、换、退款、运费险、售后政策的客服应答。 触发词：退货、换货、退款、退换、运费、售后、七天无理由、质量问题、发错货、退回。
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: 3. 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. 20 steps
- 100Consistency. Name and required fields are in place
- 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
- +1No license
- +2Single-language instructions
- +3Description length 195: enough signal without eating the budget
- +4Structure: 14 headings
- +3Step-by-step instructions: 20 items
- +4Has examples (4 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.
External checks
ClawHub: clean
The skill artifacts are coherent maintainer and Convex workflow instructions with disclosed high-impact actions and no evidence of hidden or malicious behavior.
LLM: benign (medium) · VirusTotal: · 29 May 2026