From grimoire
Classifies sleep problems (insomnia, sleep apnea, RLS, circadian disorders) using ICSD-3 criteria and guides intervention or referral.
How this skill is triggered — by the user, by Claude, or both
Slash command
/grimoire:diagnose-sleep-issueThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Systematically classify a sleep problem using evidence-based criteria to guide targeted intervention or referral.
Systematically classify a sleep problem using evidence-based criteria to guide targeted intervention or referral.
Adopted by: American Academy of Sleep Medicine (AASM), sleep medicine specialists, CBT-I certified practitioners Impact: AASM and NIH designate CBT-I as the first-line treatment for chronic insomnia (superior to medication); correct diagnosis is a prerequisite — the wrong intervention (e.g., sleep restriction for someone with sleep apnea) is ineffective and potentially harmful.
Why best: Misdiagnosing the type of sleep disorder leads to ineffective or counterproductive interventions. Insomnia, sleep apnea, restless leg syndrome, and circadian rhythm disorders have different causes and require different treatments; a structured diagnostic approach prevents wasted months on the wrong solution.
Case: 38-year-old female, difficulty falling asleep (60+ min), 3–4 awakenings/night, 5 nights/week for 8 months, daytime fatigue 7/10. Sleep diary confirms: SOL 55 min average, WASO 45 min, TST 5.5 hours. No snoring, no leg discomfort, goes to bed at 10pm but lies awake. No caffeine after noon. Diagnosis: Chronic insomnia disorder. Contributing factor: excessive time in bed creating low sleep drive. Intervention: CBT-I with sleep restriction (initial sleep window 12:30am–6:30am) and stimulus control.
Health disclaimer: This skill encodes evidence-based best practices for educational purposes. It is not medical advice. Consult a qualified healthcare professional before making health decisions.
npx claudepluginhub jeffreytse/grimoire --plugin grimoireGenerates evidence-based sleep hygiene recommendations including sleep schedule design, environment optimization, light exposure, and behavioral modifications drawn from AASM and CDC guidelines.
Analyzes sleep data to identify patterns, evaluate quality, and generate personalized improvement suggestions, with support for correlation analysis with other health metrics.
Helps users investigate ambiguous non-emergency health symptoms via intake, tracking, testing, analysis, and low-risk experiments. Supports file inspection and artifact creation.