BC master-xuyun
Use when user asks about 虚云, 参禅, 话头, 念佛是谁, 疑情, 开悟, 桶底脱落, 禅七, 行香, 丛林, 五宗兼嗣, 临济, 曹洞, 沩仰, 云门, 法眼, 老实修行, 头陀行, 持戒, 禅净双修, 云居山, 南华寺, or wants teaching in 虚云老和尚 Xuyun's voice. Triggers include "虚云"、"参话头"、"念佛是谁"、"疑情"、"禅七"、"行香"、"丛林规矩"、"桶底脱落"、"五宗"、"杯子扑落地"、"老实修行"、"头陀"、"禅堂"、"坐禅"、"数息" — invoke whenever user's question touches Chan practice, meditation methods, or monastic discipline, even without explicit request.
The skill triggers on Xuyun and Chan practice queries, catching keywords like念佛是谁,疑情,禅七 in parallel. Promises to teach in the old master's voice, covering meditation and monastic discipline. Nine files, zero critical errors, safety at 100. Quality score 86 is solid for a specialized skill, but process score 52 suggests trigger logic may lag or misfire. No model runs or sandbox tests.
If you need an AI assistant versed in Chan tradition, the skill works. For production use—install it, but watch whether it catches the right moments or lets Zen questions slip through.
Triggers include "虚云"、"参话头"、"念佛是谁"、"疑情"、"禅七"、"行香"、"丛林规矩"、"桶底脱落"、"五宗"、"杯子扑落地"、"老实修行"、"头陀"、"禅堂"、"坐禅"、"数息" — invoke whenever user's question touches Chan…
As a process C 52/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches
The same skill appears in 1 more place: Master-skill
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: 9. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- note
frontmatter-keyunknown frontmatter key "lineage" - note
frontmatter-keyunknown frontmatter key "dates" - note
frontmatter-keyunknown frontmatter key "sources" - note
frontmatter-keyunknown frontmatter key "citation_format" - note
frontmatter-keyunknown frontmatter key "verified_by" - note
frontmatter-keyunknown frontmatter key "verified_at"
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
- 60Tools and files. Uses tools (web) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 100Steps. 40 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1783 tokens
- 100Running it twice. No mutating operations
- low 11 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (5 tags): a typed call is more reliable
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
- +2Single-language instructions
- +3Description length 403: enough signal without eating the budget
- +4Structure: 12 headings
- +3Step-by-step instructions: 40 items
- +4Has examples (1 code blocks)
- +4Reference files are cited in the instructions (2 of 2)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 86.