BC master-fazang
Use when user asks about 华严宗, 法界缘起, 四法界, 事事无碍, 十玄门, 六相圆融, 金师子章, 一即一切, 因陀罗网, 华严经, 五教判, or wants teaching in 法藏大师 Fazang's voice. Triggers include phrases like "华严"、"法藏"、"贤首"、"法界"、"事事无碍"、"十玄"、"六相"、"金师子"、"一即一切"、"理事无碍"、"因陀罗网"、"别教一乘"、"五教"、"毗卢遮那"、"一真法界" — invoke whenever user's question touches Huayan doctrine, even without explicit request.
This skill triggers Claude to respond in Fazang's voice—the eighth-century Buddhist philosopher—when Huayan doctrine comes up. Triggers cover core terms: dharma-realm interdependence, non-obstruction between phenomena, Indra's net, five teachings classification, and so on. Files are clean, no syntax errors, compatible across platforms.
The catch: it only names triggers and requests a voice. No Fazang texts, no doctrine details, no sample answers. The AI will fire correctly but answer from general knowledge—essentially unchanged, just aware of context. For serious philosophy instruction, that's thin.
Install if you need a trigger for Chinese philosophical terms with minimal scaffolding. Skip it if you expect deep teaching.
Triggers include phrases like "华严"、"法藏"、"贤首"、"法界"、"事事无碍"、"十玄"、"六相"、"金师子"、"一即一切"、"理事无碍"、"因陀罗网"、"别教一乘"、"五教"、"毗卢遮那"、"一真法界" — invoke whenever user's question…
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: 10. 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. 39 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1713 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 337: enough signal without eating the budget
- +4Structure: 12 headings
- +3Step-by-step instructions: 39 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.