AB aky-tcm-prescription
AI-powered Traditional Chinese Medicine (TCM) prescription assistant based on classical texts: Shanghan Lun (伤寒论), Jingui Yaolue (金匮要略), and Formula Study (方剂学). Supports syndrome differentiation (八纲/六经/脏腑/卫气营血), formula recommendation with composition analysis, herb safety checking (十八反十九畏, 妊娠禁忌), dosage guidance, and formula modification. Trigger when users ask about: TCM prescription, Chinese herbal formula, syndrome differentiation, 开方, 中药方, 辨证论治, formula analysis, herb substitution, classical formulas (经方), or any TCM clinical guidance.
AI-powered Traditional Chinese Medicine (TCM) prescription assistant based on classical texts: Shanghan Lun (伤寒论), Jingui Yaolue (金匮要略), and Formula Study…
As a process B 69/100 · Nearly there — weak spots: inputs and preconditions, failures and branches, progress reporting
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
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 69/100
- 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
- 60Result and completion. Output format stated, no completion criterion
- 85Steps. 14 steps, 1 vague phrases
- 100Tools and files. No external tools needed
- 100When it triggers. States when to use and when not to
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2774 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
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +1No license
- +2Single-language instructions
- +3Description length 547: enough signal without eating the budget
- +4Structure: 10 headings
- +3Step-by-step instructions: 14 items
- +3Output format is stated explicitly
- +4Has examples (4 code blocks)
- +4Reference files are cited in the instructions (7 of 7)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 91.