check

A health and training-readiness audit that reviews several weeks of workout, recovery, and injury-related information.

In plain words
What is it for?
Use it to review recent training volume, frequency, intensity, wellness trends, fitness-load changes, and adherence to planned workouts.
Why use it?
It helps identify possible overtraining, sudden increases in workload, insufficient recovery, and warning signs of injury.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/rlacombe/switchback-running/check
Any agent
npx skills add rlacombe/switchback-running --skill check
Clone the repo
git clone --depth 1 https://github.com/rlacombe/switchback-running

Made for: Claude Code, Codex.

Per session 15 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 807 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00015 $0.00807
Opus 5 $0.00008 $0.00404
Sonnet 5 $0.00003 $0.00161
Haiku 4.5 $0.00002 $0.00081

Measured 2d ago against content hash 21f61fc79cb8, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

check scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.claude/skills/check/SKILL.md · 79 lines

How it starts

The opening of the file, as written. The whole thing — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/check — Health & Readiness Audit

Goes deeper than /today's daily snapshot. Analyzes multi-week trends to flag overtraining risk, volume ramp issues, recovery adequacy, and injury warning signs.

If only Strava is configured, limit the audit to completed-activity volume, frequency, intensity, and athlete-reported descriptions. Do not claim HRV, sleep, CTL/ATL/TSB, or planned-workout compliance without Intervals.icu data.

Step 1: Read knowledge base

Read these coaching files for detection criteria and thresholds:

  • knowledge/recovery-overtraining.md — FOR/NFOR/OTS stages, detection methods, warning signs
  • knowledge/injury-prevention.md — red flags, volume ramp limits, return protocols
  • knowledge/volume-progression.md — 10% rule, build:recovery ratios, CTL ramp rates
  • knowledge/age-gender.md — age/gender-specific recovery considerations

Step 2: Gather data

Fetch data using MCP tools (call them directly, in parallel where possible):

  • Wellness endpoint for the last 30 days — sleep, HRV, resting HR, fatigue, mood trends
  • Fitness endpoint for the last 30 days — CTL/ATL/TSB progression
  • Activities endpoint for the last 30 days — actual volume, frequency, intensity
  • Events endpoint for the last 30 days — planned vs completed (compliance) Read athlete/profile.md for injury history, age, known weaknesses, and cached zones.

Step 3: Analyze

Volume Trends

  • Weekly mileage progression over 4 weeks — flag increases >10%/week
  • CTL ramp rate — flag if >5 points/week sustained
  • Are recovery weeks happening? Check for step-back every 3-4 weeks
  • Build:recovery ratio — is it 3:1 or 2:1? Should it be?

Wellness Trends

  • HRV trend: declining over 7+ days = concern
  • Resting HR trend: rising over 7+ days = concern
  • Sleep: average over 30 days, trend direction, any sustained <7h periods
  • Fatigue/mood: worsening trend over 7+ days

Overtraining Risk Assessment

Using the FOR → NFOR → OTS framework from knowledge/recovery-overtraining.md:

  • Steve House's 3 warning signs: slow warmup, poor sleep, suspected injury (2+ = immediate rest)
  • Performance decline: are recent workouts showing pace/HR regression?
  • Compliance: missed workouts may indicate fatigue-driven avoidance

Read the full file on GitHub · 79 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 79 lines · 15 tokens per session scan A 21f61fc79cb8

Subscribe to this mod's changes

check is a skill published in the GitHub repository rlacombe/switchback-running (11 stars, last pushed 7d ago), licensed MIT. It adds 15 tokens to every session and 807 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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