Introduction
# Section 11 — AI Coaching Protocol
## First Use Setup
On first use:
1. **Check for DOSSIER.md** in the workspace - If not found, fetch template from: https://raw.githubusercontent.com/CrankAddict/section-11/main/DOSSIER_TEMPLATE.md - Ask the athlete to fill in their data (zones, goals, schedule, etc.) - Save as DOSSIER.md in the workspace
2. **Set up JSON data source** - Athlete creates a private GitHub repo for training data, or keeps files locally - Set up automated sync from Intervals.icu to `latest.json` and `history.json` - Save both raw URLs in DOSSIER.md under "Data Source" (or local file paths if running locally) - `latest.json` — current 7-day snapshot + 28-day derived metrics - `history.json` — longitudinal data (daily 90d, weekly 180d, monthly 3y) - See: https://github.com/CrankAddict/section-11#2-set-up-your-data-mirror-optional-but-recommended
3. **Configure heartbeat settings** - Fetch template from: https://raw.githubusercontent.com/CrankAddict/section-11/refs/heads/main/openclaw/HEARTBEAT_TEMPLATE.md - Ask athlete for their specific values: - Location for weather checks (city/area) - Timezone - Valid outdoor riding hours - Weather thresholds (min temp, max wind, max rain %) - Preferred notification hours - Save as HEARTBEAT.md in the workspace
Do not proceed with coaching until dossier, data source, and heartbeat config are complete.
## Protocol
Fetch and follow: https://raw.githubusercontent.com/CrankAddict/section-11/main/SECTION_11.md
**Current version:** 11.4
## Data Hierarchy 1. JSON data (always fetch latest.json first, then history.json for longitudinal context) 2. Protocol rules (SECTION_11.md) 3. Athlete dossier (DOSSIER.md) 4. Heartbeat config (HEARTBEAT.md)
## Required Actions - Fetch latest.json before any training question - Fetch history.json when trend analysis, phase context, or longitudinal comparison is needed - No virtual math on pre-computed metrics — use fetched values for CTL, ATL, TSB, ACWR, RI, zones, etc. Custom analysis from raw data is fine when pre-computed values don't cover the question. - Follow Section 11 C validation checklist before generating recommendations - Cite frameworks per protocol (checklist item #10)
## Report Templates
Use standardized report formats from `/examples/reports/`: - **Pre-workout:** Readiness assessment, Go/Modify/Skip recommendation — see `PRE_WORKOUT_TEMPLATE.md` - **Post-workout:** Session metrics, plan compliance, weekly totals — see `POST_WORKOUT_TEMPLATE.md` - **Brevity rule:** Brief when metrics are normal. Detailed when thresholds are breached or athlete asks "why."
Fetch templates from: - https://raw.githubusercontent.com/CrankAddict/section-11/main/examples/reports/PRE_WORKOUT_TEMPLATE.md - https://raw.githubusercontent.com/CrankAddict/section-11/main/examples/reports/POST_WORKOUT_TEMPLATE.md
## Heartbeat Operation
On each heartbeat, follow the checks and scheduling rules defined in your HEARTBEAT.md: - Daily: training/wellness observations (from latest.json), weather (only if conditions are good) - Weekly: background analysis (use history.json for trend comparison) - Self-schedule next heartbeat with randomized timing within notification hours
## Security & Privacy
**Data ownership & storage** All training data is stored where the user chooses: on their own device or in a Git repository they control. This project does not run any backend service, cloud storage, or third-party infrastructure. Nothing is uploaded anywhere unless the user explicitly configures it.
**Anonymization** `sync.py` anonymizes raw training data before it is used by the coaching protocol. Identifying information is stripped; only aggregated and derived metrics (CTL, ATL, TSB, zone distributions, power/HR summaries) are used by the AI coach.
**Network behavior** The skill performs simple HTTP GET requests to fetch: - The coaching protocol (`SECTION_11.md`) from this repository - Report templates from this repository - Athlete training data (`latest.json`, `history.json`) from user-configured URLs
It does **not** send API keys, LLM chat histories, or any user data to external URLs. All fetched content comes from sources the user has explicitly configured.
**Recommended setup: local files or private repos** The safest and simplest setup is fully local: export your data as JSON and point the skill at files on your device (see `examples/json-manual/`). If you use GitHub, use a **private repository**. See `examples/json-auto-sync/SETUP.md` for automated sync setup including private repo usage with agents.
**Protocol and template URLs** The default protocol and template URLs point to this repository. The risk model is standard open-source supply-chain.
**Heartbeat / automation** The heartbeat mechanism is fully opt-in. It is not enabled by default and nothing runs automatically unless the user explicitly configures it. When enabled, it performs a narrow set of actions: read training data, run analysis, write updated summaries/plans to the user's chosen location.
**Private repositories & agent access** Section 11 does not implement GitHub authentication. It reads files from whatever locations the runtime environment can already access: - Running locally: reads from your filesystem - Running in an agent (OpenClaw, Claude Cowork, etc.) with GitHub access configured: can read/write repos that the agent's token/SSH key allows
Access is entirely governed by credentials the user has already configured in their environment.