AD 银行业本体建模专家（基础版）
以教练的方式，一步步引导新手咨询顾问亲手完成"银行业务领域"的知识工程式本体建模，全程对标行业参照标准 FIBO（Financial Industry Business Ontology），并陪着他搭出一份"概念+定义+关系+FIBO对标"的结构化文档。严格服务于银行/金融业务咨询场景。当用户表示想学习或练习银行（或金融机构）的本体建模、领域建模、概念建模、数据治理术语建模，想把某块银行业务（如对手方、法人实体、受益所有权、账户、金融工具、监管报送、KYC/AML、风险敞口等）的概念结构化、理清关系，或提到"本体""ontology""FIBO""领域本体""胜任力问题"且语境是金融/银行时，务必使用本技能。即使用户只是丢来一块银行业务、说"帮我把这块的概念理一理 / 对标一下 FIBO"而没明确说"建模"，只要意图是把某个银行业务领域的概念体系梳理清楚，也应主动用本技能进入教练式引导，而不是直接替他给出成品。本技能不处理银行业以外的通用本体建模需求。
以教练的方式，一步步引导新手咨询顾问亲手完成"银行业务领域"的知识工程式本体建模，全程对标行业参照标准 FIBO（Financial Industry Business…
As a process D 49/100 · Unfinished process — 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 · 0
✓ No critical or high findings
Files scanned: 6. 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") - note
frontmatter-keyunknown frontmatter key "slug"
Process rating: all ten parameters 49/100
- 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
- 40Consistency. Frontmatter name (银行业本体建模专家（基础版）) differs from the folder (banking-ontology-coach)
- 100Tools and files. No external tools needed
- 100Steps. 29 steps
- 100Execution cost. Instruction body is 1324 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
- +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
- +5Description quotes 4 example trigger phrases
- +3Description length 432: enough signal without eating the budget
- +4Structure: 15 headings
- +3Step-by-step instructions: 29 items
- +4Has examples (1 code blocks)
- +4Reference files are cited in the instructions (4 of 4)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.