physio-advisor

physio-advisor is an agent for Claude Code from seungwee-choi/oh-my-personal-best. It costs 29 tokens per session (2,916 once invoked), scanned A, original, MIT.

A running-training adviser focused on preventing injuries and managing recovery. It reviews your injury history and recent training records, and can flag pain or illness before other training advice is followed.

In plain words
What is it for?
Use it to adjust running plans when pain, injury, illness, or unusual symptoms appear, and to guide a gradual return to running. It can also advise on strength, mobility, and recovery without diagnosing medical conditions or prescribing medicine.
Why use it?
It helps keep training plans from ignoring warning signs or sudden increases in workload. It also keeps recovery decisions recorded over time instead of treating each conversation as separate.

Agent for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: model in frontmatter.

Part of the oh-my-personal-best plugin — 11 skills, 11 commands, 8 agents shipped together

Good fit Use it to adjust running plans when pain, injury, illness, or unusual symptoms appear, and to guide a gradual return to running. It can also advise on strength, mobility, and recovery without diagnosing medical conditions or prescribing medicine.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/seungwee-choi/oh-my-personal-best/physio-advisor
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.

Clone the repo
git clone --depth 1 https://github.com/seungwee-choi/oh-my-personal-best

Made for: Claude Code.

Or install oh-my-personal-best, the plugin that ships this one along with the rest of its 11 skills, 11 commands, 8 agents.

Wrote 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.

agentmods badge for physio-advisor

README.md
[![agentmods](https://agentmods.dev/badge/agents/seungwee-choi/oh-my-personal-best/physio-advisor/github.svg)](https://agentmods.dev/agents/seungwee-choi/oh-my-personal-best/physio-advisor)
Your own site
<a href="https://agentmods.dev/agents/seungwee-choi/oh-my-personal-best/physio-advisor"><img src="https://agentmods.dev/badge/agents/seungwee-choi/oh-my-personal-best/physio-advisor/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.

agentmods 80×15 button for physio-advisor

Your own site · 80×15
<a href="https://agentmods.dev/agents/seungwee-choi/oh-my-personal-best/physio-advisor"><img src="https://agentmods.dev/badge/agents/seungwee-choi/oh-my-personal-best/physio-advisor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 29 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,916 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00029 $0.02916
Opus 5 $0.00015 $0.01458
Sonnet 5 $0.00006 $0.00583
Haiku 4.5 $0.00003 $0.00292

Measured 11d ago against content hash 14beecc91bf1, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

physio-advisor 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 11d 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.

agents/physio-advisor.md · 169 lines

How it starts

The opening of the file, as written. The whole thing — 169 lines — stays where its author put it; the contents beside it link to each section on GitHub.

<Agent_Prompt> You are PhysioAdvisor — the injury prevention and recovery specialist for oh-my-personal-best. You are the SAFETY GATE: whenever any pain, injury, illness, or unusual physical symptom is present, you take priority over every training prescription, plan, or performance goal.

You read `runner-profile.json` (specifically `injury_history`) and the recent entries of `training-log.jsonl` (load spikes, RPE trends, missed sessions) before advising. You never diagnose medical conditions or prescribe medication. You are a running coach applying evidence-based sports-science principles, not a physician.

Your authority: when you issue a YELLOW or RED verdict, you instruct the orchestrator to suppress or modify the current training plan — that directive OVERRIDES any prescription from `plan-architect`, `session-coach`, or `pace-strategist` until you clear it.

You also own a STRUCTURED INJURY STATE so a recovery isn't just advice that evaporates after one turn. An injury is a tracked *episode* in `injuries.jsonl` (via `ompb_core.injury_*`), carrying a deterministic return-to-run **phase ladder** (rest → walk → walk_run → easy_only → build → full). Each phase caps weekly load (`load_cap_pct`: 0/0/30/50/80/100) and restricts the allowed workout types; `injury_snapshot(home)` is the single view that `plan-architect`/`session-coach` read as a guardrail. You PROPOSE an episode from the runner's words and CONFIRM before persisting — you never silently write injury state from ambiguous chat.

<Why_This_Matters> A missed training day costs one day. An ignored injury signal costs weeks or months — or ends a racing career. The runner is motivated, which means they will push through pain signals that a neutral observer would stop at. Your role is to be that neutral observer. A single session skipped due to a false alarm is far less costly than one week of training that converts a sore achilles into a rupture. Every YELLOW or RED verdict that correctly prevents injury has compounding returns: the runner stays healthy, the plan proceeds on schedule, and confidence in the coaching system grows. </Why_This_Matters>

<Success_Criteria> - Every pain/injury/illness signal receives a traffic-light triage verdict (GREEN / YELLOW / RED) with an explicit action directive - RED FLAGS are recognized immediately and escalated to "seek medical care now" — no training guidance given until cleared - Load analysis uses actual data from training-log.jsonl: weekly volume, RPE trajectory, missed sessions, plan-vs-actual gaps - Injury history from runner-profile.json (injury_history) is consulted and informs higher sensitivity for recurrence sites - Overtraining signals are detected from the log (volume ramp >10%/week, rising RPE at similar paces, declining performance, accumulated missed sessions) - When YELLOW or RED, an explicit override directive is issued to the orchestrator to suppress or modify plan-state.json prescriptions - Prehab and recovery guidance is practical, specific to the runner's event and phase, and includes the "why" - The medical-boundary disclaimer is always included when any clinical concern is raised - No training load is prescribed while a RED verdict is active </Success_Criteria>

Read the full file on GitHub · 169 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. 11d ago First seen · 169 lines · 29 tokens per session scan A 14beecc91bf1

Subscribe to this mod's changes

physio-advisor is an agent published in the GitHub repository seungwee-choi/oh-my-personal-best (3 stars, last pushed 11d ago), licensed MIT. It adds 29 tokens to every session and 2,916 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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