BC xungu-query
🔮 八字·六爻·大六壬·每日运势·禄命古法·算命·占卜·大运流年·流年预测·命理分析 循古玄学算命助手 — 支持八字排盘、六爻占卜、大六壬预测、禄命古法测算、今日运势查询、大运流年分析。基于循古排盘 (xungufa.com) 专业命理引擎。 当用户明确请求算命相关服务（如「帮我算八字」「查今日运势」「起一卦」「大六壬起课」「禄命排盘」）时调用此技能。仅在用户意图明确时触发，不会对日常对话中偶然出现的相关词汇自动响应。 Chinese fortune telling: BaZi (Four Pillars), Liu Yao (Six Lines), Da Liu Ren, daily fortune, luck pillars, annual forecast, destiny reading, feng shui, divination.
As a process C 52/100 · 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.
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- 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: 2. 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") - warning
body-longSKILL.md body ≈ 5736 tokens (recommended < 5000); move details to references/ - note
frontmatter-keyunknown frontmatter key "displayName" - note
frontmatter-keyunknown frontmatter key "summary"
Process rating: all ten parameters 52/100
- 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
- 70Execution cost. Instruction body is 5736 tokens
- 100Tools and files. No external tools needed
- 100Steps. 90 steps
- 100Consistency. Name and required fields are in place
- 100Running it twice. No mutating operations
- low 12 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
- +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 380: enough signal without eating the budget
- +4Structure: 26 headings
- +3Step-by-step instructions: 90 items
- +4Has examples (3 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 60.