Borrowing it
Nothing to install: this file belongs to snoozelieb/coach-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/snoozelieb/coach-mcp/main/CLAUDE.mdgit clone --depth 1 https://github.com/snoozelieb/coach-mcpWrote 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/instructions/snoozelieb/coach-mcp/claude-md)<a href="https://agentmods.dev/instructions/snoozelieb/coach-mcp/claude-md"><img src="https://agentmods.dev/badge/instructions/snoozelieb/coach-mcp/claude-md/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/instructions/snoozelieb/coach-mcp/claude-md"><img src="https://agentmods.dev/badge/instructions/snoozelieb/coach-mcp/claude-md.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 | $0.03196 | $0.03196 |
| Opus 5.5 | $0.01278 | $0.01278 |
| Sonnet 5.5 | $0.00639 | $0.00639 |
| Haiku 4.5 | $0.00320 | $0.00320 |
Grade A, and why
coach-mcp CLAUDE.md 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 yesterday.
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 — 226 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md
Development context for Claude Code (claude.ai/code) sessions in this repository.
Coaching doctrine lives in the server, not in this file. Every MCP client — Claude Code included — receives the coaching identity at connection time via
SERVER_INSTRUCTIONS(coach/mcp_app.py; test-enforced under 3,900 chars because Claude Code sends the model only the first 4,096) and the long-formcoach://coaching/doctrineresource (uncapped, fetched on demand; completeness pinned bytests/test_server_instructions.py). When coaching from this repo, follow those surfaces — the four hard mandates (snapshot first, injury hard gate, verify before confirming, verify before prescribing) — and read the doctrine resource before planning sessions. Do not copy doctrine into this file: the duplicate is the copy that drifts.
Project Overview
An adaptive AI training coach MCP server: fetches fitness data from Garmin
Connect, maintains a rolling 7-day plan with a PURPOSE for every session, persists
coaching memory (decisions, anomalies, approvals) across sessions, and pushes
workouts to the Garmin calendar. Published as garmin-coach-mcp on PyPI and
io.github.snoozelieb/coach-mcp on the MCP registry.
The safety-critical coaching rules are code-enforced, not prompt-enforced:
update_weekly_plan rejects non-rest sessions without a purpose (purpose gate)
and sessions matching an active/improving injury's restricted_activities (injury
gate — taxonomy-aware, re-run on the full plan at push); plans entirely in the past
or with days >21 in the future are rejected; anomalies and season auto-proposals
are idempotent by stable id / event-tag, so rejections are remembered forever.
Capacity grounding is code too: snapshot.capacity is derived from persisted
daily_loads (coach/fitness.py: capacity_by_sport, derive_sport_capacity);
update_weekly_plan returns grounding_warnings (advisory), while
training_program(action='set') rejects a program whose capacity anchor the
history contradicts, and runs the injury gate as well.
See coach/tools/planning_tools.py and coach/tools/decision_tools.py.
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.
- yesterday Changed · +34 lines · +629 tokens per session f0f8466521d9
- 1mo ago First seen · 192 lines · 2,567 tokens per session scan A 0e6ecb611bc7
coach-mcp CLAUDE.md is an instructions file published in the GitHub repository snoozelieb/coach-mcp (3 stars, last pushed yesterday), licensed MIT. It adds 3,196 tokens to every session, about $0.0128 per session on Opus 5.5. 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.
Other instructions, from other repositories
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, cache eligibility and rollout and applying the notice (cutover).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
vscode copilot-instructions.md
Copilot instructions for microsoft/vscode, covering vs code copilot instructions, project overview, root folders, core architecture (src/ folder) and built-in extensions (extensions/ folder).
vscode model-prompts.instructions.md
Model-specific prompt authoring and registry guidelines.