AC cantian-naming
中文姓名分析与起名推荐技能（优先按喜用神筛选）。用于用户请求“按姓氏起单字/双字名”“结合喜用神推荐名字”“比较多个候选名”“改名并说明原因”“给男孩/女孩各出一批候选名”“宝宝起名”“公司起名”“品牌名/店铺名起名”“英文名或中英双语名”“艺名/笔名/网名起名”“宠物起名”“按行业气质与目标客群定名”“避开常见重名字并保留寓意”“检查名字读音和语义是否顺口”等场景；支持综合考虑姓氏、性别、生肖、音律、美感、字义与八字五行。关键词包括：姓名分析、起名、改名、宝宝起名、公司起名、品牌起名、英文名、艺名、网名、宠物名、喜用神、八字、生肖、音律、重名、读音、寓意。 / Chinese naming analysis and candidate generation skill (prioritize favorable-element filtering; treat WuGe as secondary reference). Use when users ask to pick one/two-character given names by surname, recommend names by favorable elements, compare candidates, explain rename decisions, generate boy/girl batches, name a baby, name a company, create brand/store names, generate English or bilingual names, suggest stage/screen names, name pets, align names with industry tone and target audience, avoid overused names while preserving meaning, or check pronunciation and semantics, while balancing surname, gender, zodiac, phonetics, aesthetics, meaning, and BaZi context.
As a process C 54/100 · Has gaps — weak spots: result and completion, when it triggers, failures and branches
How to improve
- 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: 10. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 54/100
- 0Result and completion. Does not say what the result is
- 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
- 60Tools and files. Uses tools (node) that frontmatter does not declare
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Steps. 101 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1795 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)
- +3Description length 956: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +5Description quotes 11 example trigger phrases
- +4Structure: 15 headings
- +3Step-by-step instructions: 101 items
- +4Has examples (13 code blocks)
- +3All 3 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 89.