Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub ยท Developer Tools
Section 11: Endurance Training Coach (Intervals.icu)
Evidence-based endurance cycling coaching protocol (v11.5). Use when analyzing training data, reviewing sessions, generating pre/post-workout reports, planni...
skill openclawclawhub Free
Evidence-based endurance cycling coaching protocol (v11.5). Use when analyzing training data, reviewing sessions, generating pre/post-workout reports, planni...
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Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- HEARTBEAT_TEMPLATE.md, SKILL.md
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.12
Provenance
- Publisher
- CrankAddict
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
First Use Setup
On first use: 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 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 โ current 7-day snapshot + 28-day derived metrics history.json โ longitudinal data (daily 90d, weekly 180d, monthly 3y) See: https://github.com/CrankAddict/section-11#2-set-up-your-data-mirror-optional-but-recommended Or for interactive guided setup: have the athlete paste SETUP_ASSISTANT.md into any AI chat 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: 11.5
External Sources
All external files referenced by this skill (sync.py, SECTION_11.md, templates, setup guides) are maintained in the open-source CrankAddict/section-11 repository and can be inspected there.
Data Hierarchy
JSON data (always fetch latest.json first, then history.json for longitudinal context) Protocol rules (SECTION_11.md) Athlete dossier (DOSSIER.md) 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 โ 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)
Write Capabilities
If push.py is available in the data repo, the skill can manage the athlete's Intervals.icu calendar and training data: push โ write planned workouts to calendar list โ show planned workouts for a date range move โ reschedule a workout to a different date delete โ remove a workout from the calendar set-threshold โ update sport-specific thresholds (FTP, indoor FTP, LTHR, max HR, threshold pace). Only after validated test results, never from estimates annotate โ add notes to completed activities (description by default, --chat for messages panel) or planned workouts (NOTE: prepended to description) All write operations default to preview mode โ nothing is written without --confirm. Execution via GitHub Actions dispatch (uses existing repository secrets configured by the athlete) or local CLI. See examples/agentic/README.md for full usage, workout syntax, and template ID mappings. Only available on platforms that can execute code or trigger GitHub Actions (OpenClaw, Claude Code, Cowork, etc.). Web chat users cannot use this.
Report Templates
Use standardized report formats from /examples/reports/: Pre-workout: Readiness assessment, Go/Modify/Skip recommendation โ see PRE_WORKOUT_TEMPLATE.md Post-workout: Session metrics, plan compliance, weekly totals โ 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. The skill reads from: user-configured JSON data sources, DOSSIER.md, and HEARTBEAT.md in the workspace. It writes to: DOSSIER.md and HEARTBEAT.md in the workspace (during first-use setup only). Anonymization sync.py (maintained in the source repository) anonymizes raw training data. The skill does not perform anonymization itself. 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.
Category context
Code helpers, APIs, CLIs, browser automation, testing, and developer operations.
Source: Tencent SkillHub
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Package contents
Included in package
2 Docs
- SKILL.md
- HEARTBEAT_TEMPLATE.md