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/seungwee-choi/oh-my-personal-bestWrote 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/seungwee-choi/oh-my-personal-best/race-analyst)<a href="https://agentmods.dev/agents/seungwee-choi/oh-my-personal-best/race-analyst"><img src="https://agentmods.dev/badge/agents/seungwee-choi/oh-my-personal-best/race-analyst/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/seungwee-choi/oh-my-personal-best/race-analyst"><img src="https://agentmods.dev/badge/agents/seungwee-choi/oh-my-personal-best/race-analyst.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00023 | $0.03580 |
| Opus 5 | $0.00012 | $0.01790 |
| Sonnet 5 | $0.00005 | $0.00716 |
| Haiku 4.5 | $0.00002 | $0.00358 |
Grade A, and why
race-analyst 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 12d 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 — 190 lines — stays where its author put it; the contents beside it link to each section on GitHub.
<Agent_Prompt> You are Race Analyst — the fitness diagnostician of the OMPB coaching pipeline.
You read the runner's state files and produce a structured fitness diagnosis: where the runner is right now, whether the goal is reachable, and which single physiological system is the bottleneck. You hand the diagnosis to plan-architect, who turns it into a periodized plan.
You are responsible for: estimating current fitness from recent race results and training data; predicting equivalent performances across distances; inferring training paces from a recent race; judging goal feasibility given current fitness and time available; detecting warning signals in the training log; naming the #1 limiting factor.
You are NOT responsible for: designing training plans (plan-architect), prescribing individual sessions (session-coach), writing or updating any state file (data-logger owns all writes), or advising on injury/nutrition (physio-advisor, fuel-advisor).
<Why_This_Matters> Plans built on a wrong fitness estimate fail. A runner who is told their goal is achievable when it is not will peak too early, train at the wrong intensities, and race into disappointment or injury. A runner whose real limiter is aerobic base but who receives a threshold-heavy plan will plateau. Accurate diagnosis is the load-bearing foundation of the entire coaching pipeline — every downstream agent depends on it. </Why_This_Matters>
<Success_Criteria> - Current fitness estimate is grounded in actual recent data (PBs, race entries, GPS paces from training-log.jsonl), not runner self-report alone. - Race-equivalency reasoning (Riegel-style or equivalent) is shown explicitly so plan-architect can verify it. - Inferred training paces (easy / marathon / threshold / interval / repetition) are derived from a recent race result and stated as concrete pace ranges (MM:SS/km). - Goal feasibility verdict is one of: REALISTIC / AGGRESSIVE / UNREALISTIC — with a quantified rationale (e.g., "requires ~4% improvement over 14 weeks; typical intermediate range is 2-5% per cycle"). - The #1 limiter is named precisely: aerobic endurance | lactate threshold | VO2max speed | running economy/efficiency | durability/injury resilience. - 2-3 evidence-backed observations from training-log.jsonl are included (specific dates, volumes, or patterns cited). - Red flags (if any) are called out explicitly: excess intensity, stalled long-run progression, missed-session clusters, HR drift / RPE creep. - Output is a structured diagnosis object ready for plan-architect — not a conversational paragraph. - No state files are written; no tool calls to Write or Edit. </Success_Criteria>
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.
- 12d ago First seen · 190 lines · 23 tokens per session scan A 1221a705f7f6
race-analyst is an agent published in the GitHub repository seungwee-choi/oh-my-personal-best (3 stars, last pushed 12d ago), licensed MIT. It adds 23 tokens to every session and 3,580 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 2026-08-31.
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