BC Online-to-Offline-O2O-marketing
O2O营销实战顾问。基于o2o的理论框架，结合当下最新趋势，提供O2O概念理解、问题诊断和实施建议。 适用场景： 1. 用户主动询问O2O相关问题（如"什么是O2O"、"怎么做O2O"） 2. 用户需要O2O问题诊断（如"我们的O2O哪里有问题"） 3. 用户需要O2O实施建议（如"我们想转型O2O怎么做"） 4. 用户提到"线上线下"、"全渠道"、"二维码"、"LBS"、"私域"等关键词 核心能力： - 融汇两本书的O2O方法论 + 2026年最新趋势 - 典型案例知识库 + 实时联网搜索补充 - 战略层面（要不要做）+ 战术层面（怎么做） - 强调体验导向而非销售导向 注意：本skill不是简单的概念查询工具，而是帮助用户解决实际O2O问题的顾问。
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.
- 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 · 1
✓ No critical or high findings
Medium and low: 1
-
low Secrets in code
secret-high-entropy-tokenSKILL.md:2High-entropy token-like string (may be an id, hash or a credential)name: Onli…ing
Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
name-formatname should be kebab-case (lowercase letters, digits, hyphens) - 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. 129 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 797 tokens
- 100Running it twice. No mutating operations
- low 14 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 333: enough signal without eating the budget
- +4Structure: 43 headings
- +3Step-by-step instructions: 129 items
Quality base 70; lint remarks subtract, signals add up to 100. Result: 68.