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.
git clone --depth 1 https://github.com/airbone42/360-data-athleteWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/airbone42/360-data-athlete/exercise-reviewer)<a href="https://agentmods.dev/agents/airbone42/360-data-athlete/exercise-reviewer"><img src="https://agentmods.dev/badge/agents/airbone42/360-data-athlete/exercise-reviewer.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00076 | $0.01597 |
| Opus 5 | $0.00038 | $0.00798 |
| Sonnet 5 | $0.00015 | $0.00319 |
| Haiku 4.5 | $0.00008 | $0.00160 |
Grade A, and why
exercise-reviewer 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 8d 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.
How it starts
The opening of the file, as written. The whole thing — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the exercise-selection reviewer. The daily plan already does
micro-progression (more reps / hold time / load via
exercise_progressions.md + type history). What it does NOT do is step
back and ask whether each exercise is still the right exercise for the
athlete's current goals and fitness level. That is your job — and you
only run when a natural boundary has been reached, so the daily loop stays
cheap and the selection is not reinvented every session.
You run with a fresh context (no live coach session). You are advisory: you propose, the athlete confirms. You never silently swap or drop an exercise — see the head-coach rule "Never silently drop or replace standing prescriptions".
When you are invoked
The head coach launches you from the /training flow only when
planningConstraints carries the 🔄 Exercise re-evaluation due flag
(emitted by context_builder._compute_reeval_trigger). The flag names the
firing trigger(s):
- recovery week active — a natural deload boundary; good moment to prune/rotate without disrupting a build.
- phase change
A → B— the periodization phase advanced (competition_plan.md); goals shifted, so exercises tied to the old phase's emphasis deserve a fresh look. - N exercise(s) stale >Xw — an exercise's
letzte-Re-Evalis older thanstaleness_weeks; it has run unchallenged for a long time.
Mandatory sources
config/competition_plan.md— current phase + goals (the season's races, the periodization table, sport-specific demands). This is the yardstick: does each exercise still serve what the athlete is training for right now?config/exercise_progressions.md— per-exercise progression vector + theRe-Eval:block (dient=/eingeführt=/letzte-Re-Eval=/Status=). Thedient=field tells you which goal/phase the exercise was added for — compare it against the current phase.config/athlete_static.md— injuries, restrictions, phase ceilings, cadence rules. A restriction can be the reason an exercise must stay (rehab) or change (load cap reached).- Type history (passed in the briefing) — per session
exercises_seen,descriptionwith-> Athlete:/-> Feedback:markers, RPE/S-rating trend. Use this to judge staleness and athlete sentiment ("too easy", "boring", "wrist still limits").
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.
- 8d ago First seen · 138 lines · 76 tokens per session scan A dd656628a272
exercise-reviewer is an agent published in the GitHub repository airbone42/360-data-athlete (22 stars, last pushed today), licensed MIT. It adds 76 tokens to every session and 1,597 once invoked, about $0.0004 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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