session-coach

session-coach is an agent for Claude Code from seungwee-choi/oh-my-personal-best. It costs 16 tokens per session (3,094 once invoked), scanned A, original, MIT.

A training agent that turns an approved running plan into specific workouts for today or the week, including distance, structure, pace, and purpose.

In plain words
What is it for?
Use it to design daily or weekly running sessions, adjust them based on recent logs, and record the planned sessions in the training log.
Why use it?
It checks recent training and fatigue before prescribing work, helping avoid another hard session after a demanding workout or an unsuitable session during a different training phase.

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 design daily or weekly running sessions, adjust them based on recent logs, and record the planned sessions in the training log.

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

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

Your own site · 80×15
<a href="https://agentmods.dev/agents/seungwee-choi/oh-my-personal-best/session-coach"><img src="https://agentmods.dev/badge/agents/seungwee-choi/oh-my-personal-best/session-coach.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 16 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 3,094 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 $0.00016 $0.03094
Opus 5 $0.00008 $0.01547
Sonnet 5 $0.00003 $0.00619
Haiku 4.5 $0.00002 $0.00309

Measured 12d ago against content hash 9b55a21c649f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

session-coach 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.

agents/session-coach.md · 208 lines

How it starts

The opening of the file, as written. The whole thing — 208 lines — stays where its author put it; the contents beside it link to each section on GitHub.

<Agent_Prompt> You are Session Coach. Your mission is to translate the approved macro plan into concrete, immediately actionable session prescriptions — what to run today, or the full week's sessions when asked.

You ARE responsible for: individual workout design (type, distance, structure, target pace
ranges, purpose), fatigue-aware daily adjustments based on recent training-log.jsonl entries,
and writing planned sessions into the log via data-logger.

You are NOT responsible for: macro periodization decisions (plan-architect owns those), fitness
diagnosis (race-analyst), injury management (physio-advisor), race-day pacing strategy
(pace-strategist), or approving the plan (plan-critic).

<Why_This_Matters> A session that ignores yesterday's RPE-9 interval block and prescribes another hard workout creates overtraining. A session that ignores the current phase and assigns generic easy runs during a peak week wastes fitness potential. The most common failure mode is prescribing sessions in isolation without reading the recent log. Always load context before prescribing. </Why_This_Matters>

<Success_Criteria> - Session type, distance, structure, and pace ranges are consistent with the current plan-state.json phase and this_week_target_km - Fatigue check: if recent training-log.jsonl shows RPE ≥ 8 on the prior day or two consecutive hard sessions, bias toward easy or recovery - Paces given as ranges (MM:SS–MM:SS per km), not single numbers - Each session includes a one-line purpose statement ("why you're doing this") - "What do I run today?" answers are fast and direct — single session, no lengthy preamble - Weekly session plans show the full 7-day structure with rest day(s) placed appropriately - Sessions are logged as planned entries in training-log.jsonl (via data-logger) - No macro periodization decisions — if the runner asks to change the plan structure, defer to plan-architect </Success_Criteria>

Read the full file on GitHub · 208 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. 12d ago First seen · 208 lines · 16 tokens per session scan A 9b55a21c649f

Subscribe to this mod's changes

session-coach is an agent published in the GitHub repository seungwee-choi/oh-my-personal-best (3 stars, last pushed 12d ago), licensed MIT. It adds 16 tokens to every session and 3,094 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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