From grimoire
Guides training load decisions using daily HRV measurements compared to a 7-day rolling average, with evidence-based thresholds for adjusting intensity and volume.
How this skill is triggered — by the user, by Claude, or both
Slash command
/grimoire:apply-hrv-monitoringThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Measure resting heart rate variability each morning and compare it against your 7-day rolling average — using daily deviations of ≥10% below baseline to reduce intensity or volume, and sustained high HRV trends to identify windows for breakthrough training.
Measure resting heart rate variability each morning and compare it against your 7-day rolling average — using daily deviations of ≥10% below baseline to reduce intensity or volume, and sustained high HRV trends to identify windows for breakthrough training.
Adopted by: Standard in elite cycling (Team Sky/INEOS, Jumbo-Visma), elite triathlon, and professional football clubs. NSCA Essentials of Strength and Conditioning (2016) includes HRV as a recommended readiness monitoring tool. Used by Olympic coaches across swimming, rowing, and track cycling. HRV4Training (100,000+ active users) and Elite HRV (used by 200,000+ athletes and coaches) are the dominant consumer implementations. Tim Ferriss, Peter Attia, and Andrew Huberman have popularized it for non-elite training. Impact: Plews et al. (2012) IJSPP: Elite rowers who trained according to HRV guidance showed significantly better performance outcomes than those following fixed periodization plans. Kiviniemi et al. (2007, IJSPP): HRV-guided training group improved 5km run time by 7.6% vs 3.5% in conventional training group over 4 weeks. Buchheit (2014) Sports Medicine comprehensive review: HRV correlates with training load, overreaching, illness onset, and competition readiness — making it the most actionable non-invasive readiness marker available. The mechanism: HRV reflects parasympathetic (vagal) tone; low HRV = sympathetic dominance = inadequate recovery; high HRV = parasympathetic dominance = ready for load. Why best: Training by fixed schedule (Monday: hard, Wednesday: hard, Friday: hard) ignores day-to-day variation in recovery. Subjective "how do I feel?" is notoriously unreliable — athletes systematically underestimate accumulated fatigue. HRV provides an objective, quantified signal from the autonomic nervous system. The alternative (RPE-based training) requires significant experience to self-assess accurately and is subject to motivation bias. HRV-guided training reduces overreaching episodes and prevents the performance-suppressing cycle of training hard when under-recovered.
Sources: Buchheit (2014) Sports Medicine; Plews et al. (2012, 2013, 2014) IJSPP; Kiviniemi et al. (2007) IJSPP; NSCA Essentials of Strength and Conditioning
Minimum equipment: a chest strap heart rate monitor (Polar H10 is the validated standard; finger-based apps introduce more noise) and an HRV app:
Validated options:
HRV4Training — camera-based (phone camera), good for >3 min morning protocol
Elite HRV — supports chest strap; good for 1-min morning reading
Polar Flow — built-in if using Polar devices
Whoop — continuous monitoring (higher cost, wrist-based)
Garmin — built-in nightly HRV tracking on Fenix/Forerunner 945+
The metric: most apps report rMSSD (root mean square of successive differences) — the standard HRV metric for short recordings. RMSSD reflects parasympathetic activity and is most relevant for daily readiness.
Measure at the same time every morning:
□ Immediately upon waking, before standing
□ Lie supine or sit quietly — consistent position each day
□ Do not check phone or stimulate stress response before measuring
□ Measure before coffee, food, or exercise
□ Duration: 1 minute minimum (HRV4Training camera method), 3–5 min preferred
□ Breathe normally — do not control breathing during measurement
First 7–14 days = baseline period: take daily readings but do not alter training. The app builds your personal baseline. Individual HRV values are meaningless in isolation — a reading of 65 ms rMSSD is high for one person and low for another; only deviation from your own baseline matters.
After 7–14 days of baseline:
Green — HRV within ±10% of 7-day average: proceed as planned
Yellow — HRV 10–20% below 7-day average: reduce intensity or volume by 20–30%
Red — HRV >20% below 7-day average OR lowest reading in 2+ weeks: replace
hard session with easy/active recovery or rest
Also note trend direction (not just single-day value):
Green day → execute planned session as written
Yellow day → replace high-intensity intervals with tempo/moderate; reduce total volume 20%
Red day → active recovery (easy walk, mobility work, zone 1 cardio ≤30 min) or rest
Do NOT try to push through a red day — depressed HRV after a hard session
followed by another hard session is the overtraining mechanism
Review weekly HRV trend (most apps show a 7-day chart):
Healthy training week: HRV depresses after hard days, recovers by next hard day
Overreaching pattern: HRV depresses and stays depressed 3–5+ days without recovery
Undertrained pattern: HRV consistently above baseline — increase training load
Illness onset signal: Sudden HRV drop without preceding hard training session
HRV is affected by factors besides training. Note these daily to avoid false alarms:
| Factor | Effect on HRV |
|---|---|
| Alcohol (even 1–2 drinks) | Depresses HRV 20–40% next morning |
| Poor sleep (<6h) | Depresses HRV |
| Travel / time zones | Depresses HRV 1–3 days |
| Illness onset | Sudden drop before subjective symptoms |
| High stress / anxiety | Depresses HRV |
When HRV drops coincide with known confounders (alcohol the night before), treat as non-training recovery signal — do not infer overtraining.
npx claudepluginhub jeffreytse/grimoire --plugin grimoire2plugins reuse this skill
First indexed Jun 11, 2026
Use when a coach or athlete needs to objectively measure an athlete's recovery status before a training session — to decide whether to train as planned, reduce load, or rest based on physiological and subjective readiness indicators.
Queries Whoop API for sleep, recovery, strain, HRV, and workout data, and generates interactive HTML charts. Useful for health data analysis and visualization.
Provides biometric context (HRV, sleep, recovery, RHR, steps, workouts) for host skills like daily-journal, coaching, advisory-panel, patterns, and insights. Companion layer, never standalone.