feat: add cycling-training Claude skill (MCP companion)

Modular cycling-training skill: periodization logic, workout design, and
research-backed protocols that companion an Intervals.icu MCP server (the
server owns all data + computed metrics; the skill owns knowledge + reasoning).

Structure:
- SKILL.md router + README (companion-to-MCP architecture, install steps)
- references/: durability, mtb-xco-demands, strength-for-cyclists,
  vo2max-intervals, periodization, data-confounds, citations
- assets/: base + build plan templates, durability field-test protocol

Every quantitative claim carries an inline citation; citations.md is the
single source of truth with PMID/DOI, each verified against PubMed on
2026-07-20. Notable honesty flags baked in:
- VO2 rep-length: running (Fleckenstein 2025) vs cycling (Ronnestad) conflict
  documented rather than asserted; cycling evidence favors short intervals.
- 'Yu et al. 2025' (frequency > distribution) could not be found; not cited.
- Under-researched doses (durability, taper TSB, CTL ramp) flagged 'track response'.
- HR-confound doc forbids naive decoupling<5% / RHR+5 rules.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01TqrhBhC3GEcKyaw8RTk8G6

references/durability.md

@@ -0,0 +1,76 @@
+# Durability / fatigue resistance
+
+**Load this doc when:** the question is about fatigue resistance, why late-race power fades,
+training the ability to hold power deep into long efforts, or running the durability field test.
+
+**Data/knowledge split:** the MCP server gives you the kJ, power curves, and fatigued-vs-fresh
+efforts. This doc explains *why fatigued-state power matters* and *how to train it*.
+
+---
+
+## Durability is a distinct, trainable quality
+
+"Durability" is the time of onset and the magnitude of deterioration in physiological-profiling
+variables (thresholds, efficiency, power) over the course of prolonged exercise — a quality that
+should be profiled **separately** from fresh-state numbers, because two riders with identical fresh
+profiles can fall apart very differently after several hours (Maunder et al. 2021, *Sports Med*
+51(8):1619–1628; PMID 33886100; DOI 10.1007/s40279-021-01459-0).
+
+### Why it matters more than fresh power
+
+- In professional cyclists across a Grand Tour, **fresh** mean-maximal power did **not** separate
+  WorldTour from ProTeam riders — but as work accumulated (0 → 35 kJ·kg⁻¹), WorldTour riders held
+  higher power. **Fatigued-state power differentiated performance; fresh power did not**
+  (Muriel et al. 2022, *Eur J Sport Sci* 22(12):1797–1804; PMID 34586952;
+  DOI 10.1080/17461391.2021.1987528).
+- The **fatigued** power profile varies far more across a season than the fresh profile, and it
+  tracks with **training characteristics (accumulated volume/load)** — meaning durability is
+  something you build with training, not a fixed trait (Spragg, Leo & Swart 2023, *Eur J Sport Sci*
+  23(4):489–498; PMID 35239466; DOI 10.1080/17461391.2022.2049886).
+
+## The load dependency (the key training implication)
+
+**Durability depends on maintaining high overall training load, whereas fresh power can be held on
+reduced load.** You can taper volume and keep your 5-min power; you cannot taper volume for long
+and keep your *fatigued* 5-min power. This is the empirical thrust of the Spragg training-
+characteristics paper (PMID 35239466); the crisp "reduced load keeps fresh power, sustained load
+keeps durability" phrasing is Spragg's applied interpretation of that data — cite it as such.
+
+Physiological correlates of *who* is durable (higher VO2max, better gross efficiency, higher fat-
+oxidation) come from the companion paper (Spragg, Leo & Swart 2023, *Med Sci Sports Exerc*
+55(1):133–140; PMID 35977108; DOI 10.1249/MSS.0000000000003024) — useful for understanding
+mechanism, but the *trainable lever* is sustained load + the practices below.
+
+## How to train durability
+
+1. **Long-term consistency and high volume.** Durability is a load-dependent adaptation — it is
+   built over blocks and lost when load drops. Protect the long ride.
+2. **Prolonged sessions with hard efforts placed late (fatigued-state intervals).** Put the quality
+   work *after* accumulated kilojoules, not at the fresh start of the ride — you are specifically
+   training the fatigued state that discriminates performance.
+3. **Glycogen-sparing nutrition.** Fuel long sessions to spare glycogen; the goal is training the
+   durable state under realistic fueling, not chronic depletion. (Fatigued power is glycogen-
+   sensitive — see the fueling caveat in `data-confounds.md` for why HR is unreliable here.)
+
+> ⚠️ **Under-researched — track individual response.** The *mechanism* (load-dependent fatigue
+> resistance) is well supported, but the **optimal durability dose** — how much accumulated work,
+> how often, how late to place efforts — is not established. **Do not assume a fixed protocol.**
+> Track each athlete's fatigued-state response and titrate.
+
+## Measure it: the fatigued-state field test
+
+Use `../assets/field-test-durability.md`. In brief:
+- Establish a **fresh** 1-min max on a fixed hill.
+- On a separate day, accumulate **~1,500 kJ (~2.5 h)** of mostly-endurance riding, then repeat the
+  **same 1-min max on the same hill**.
+- `Durability % = fatigued ÷ fresh × 100`. Track the trend across a block.
+- Hold the hill, gearing, kJ pre-load, and fueling **constant** so the comparison is valid.
+- **Judge from power, not HR** — HR after 1,500 kJ is confounded by drift, heat, and fueling
+  (`data-confounds.md`).
+
+## Discipline note
+
+Durability matters for both road/TT and MTB, but **keep absolute numbers discipline-specific.** The
+1,500 kJ anchor is a sensible generic default, not a validated cross-discipline constant; a masters
+marathon-MTB rider and an elite road pro do not share a durability dose. See `mtb-xco-demands.md`
+for how fatigue resistance shows up specifically in off-road racing.