Agent skill

Section 11

by CrankAddict in CrankAddict/section-11

Evidence-based endurance coaching protocol (v11.70). An agent skill from CrankAddict/section-11.

MITAuto-check passedProductivity & Automation

Install Section 11

skills CLI
$ npx skills add CrankAddict/section-11 --skill section-11 -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install CrankAddict/section-11 section-11 --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
section-11
GitHub stars
156
Token cost
~5.2k tokens
SKILL.md length
2,758 words
Files
94
Skills in repo
1
Repo updated
First seen
Licence
MIT

At a glance

Evidence-based endurance coaching protocol (v11.70). An agent skill from CrankAddict/section-11.

  • Works in 4 steps: Check for DOSSIER.md in the data directory → Set up JSON data source → Configure heartbeat settings (optional,… → …
  • Analyzing training data
  • SKILL.md covers File Locations, First Use Setup, Protocol and External Sources, plus 6 more sections
  • Runs JavaScript scripts from its folder

What it does

Section 11 is an agent skill from CrankAddict/section-11. Evidence-based endurance coaching protocol (v11.70). Use when analyzing training data, reviewing sessions, generating pre/post-workout reports, planning workouts, answering training questions, or giving endurance coaching advice. Always read or fetch athlete JSON data before responding to any training question.

Its SKILL.md is about 5.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 96 other files (for example `.github/site/README.md`, `.github/site/package-lock.json` and `.github/site/package.json`).

It sits in Productivity & Automation, covering Health and fitness tracking. The repository describes itself as: Evidence-based AI coach for endurance training. Protocol-driven. Deterministic guidance for any LLM, with Intervals.icu integration. The licence is MIT.

When your agent uses it

  • Analyzing training data
  • Reviewing sessions
  • Generating pre/post-workout reports
  • Planning workouts

Example prompts

  • “/section-11”

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. Check for DOSSIER.md in the data directory
  2. Set up JSON data source
  3. Configure heartbeat settings (optional, OpenClaw)
  4. Configure data discipline rule (agentic platforms with persistent identity)

What it can do on your machine

Read from SKILL.md and the folder at commit 83e2775. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships script files (JavaScript, from the files we listed), which the agent can run.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • github.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Section 11 loads about 5.2k tokens when it runs. Until then it costs about 81 tokens; SKILL.md has 2,758 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~81
When it runs · the whole SKILL.md, loaded when a task matches
~5.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from CrankAddict/section-11 at commit 83e2775, republished under its MIT licence (© CrankAddict). 2,758 words, ~5,187 tokens.

Download SKILL.mdSave it as .claude/skills/section-11/SKILL.md (or your agent's skills folder). This skill also uses 93 other files; get the full folder from GitHub.
name
section-11
description
Evidence-based endurance coaching protocol (v11.70). Use when analyzing training data, reviewing sessions, generating pre/post-workout reports, planning workouts, answering training questions, or giving endurance coaching advice. Always read or fetch athlete JSON data before responding to any training question.

Section 11 - AI Coaching Protocol

File Locations

Data files (latest.json, history.json, intervals.json, ftp_history.json, routes.json, saved_workouts.json, DOSSIER.md, section11/) live in the athlete's data directory: a runtime-accessible location, typically something like ~/training-data/. HEARTBEAT.md lives in the agent workspace: the directory the agent runs from. These may or may not be the same directory.

The data directory is where training data is read. It is not the authority record for the dossier: the authoritative dossier copy is named in the Official dossier location field in the dossier's own header block.

Files under any examples/json-examples/ folder, including section11/examples/json-examples/, and any file ending in .example.json are fictional schema examples, never athlete data. Never use them for coaching, reports, readiness, planning or athlete metrics, and never fall back to them when a real data file is missing or stale.

First Use Setup

On first use:

  1. Check for DOSSIER.md in the data directory

    • If found, read its header block first: authority statement, Official dossier location, dossier revision, last reviewed
    • If more than one copy is reachable, do not merge them. Compare revision and last-reviewed date and ask the athlete which is official
    • If not found, check the connected source (if a connector is available)
    • If not found, check uploaded or attached files
    • If not found, check section11/DOSSIER_TEMPLATE.md
    • If not found, fetch from: https://raw.githubusercontent.com/CrankAddict/section-11/main/DOSSIER_TEMPLATE.md
    • Offer guided creation first and manual completion second. Ask only for stable private context: long-term goals, health and medication context, allergies and tested fueling, stable constraints, environment and equipment, communication preferences. Do not ask for thresholds, zones, weight or current phase. Those come from current JSON. Do not ask for planned training or the weekly schedule. Those come from current JSON and calendar data
    • Ask the athlete where the file should live, and record it as Official dossier location. Keep it in a private location: a local data directory, a private repository, or a private document store. Never place a private dossier in a public data mirror
    • Show the draft and obtain explicit approval before creating the file
  2. Set up JSON data source

    • Runtime-accessible filesystem (recommended): Athlete runs sync.py on a timer, producing latest.json, history.json, intervals.json, ftp_history.json, routes.json (when events have GPX/TCX attachments) and saved_workouts.json in the data directory. The runtime reads them directly. This may be the athlete's own machine or a provider-hosted computer; "agentic" does not mean "local". See examples/json-local-sync/SETUP.md for the full pipeline.

    Platform routing. Three surfaces, two contracts:

    SurfaceContract
    Grok (web/app), and other web-chat platformsPROJECT_INSTRUCTIONS_WEB.md
    Grok Bot, Hermes Agent, and other agentic runtimesPROJECT_INSTRUCTIONS_AGENTIC.md

    Grok Bot and Hermes Agent are experimental: the capability class fits, but the Section 11 pipeline is not validated end to end on either. Treat support as unproven rather than assured.

    • Connector or authenticated repository: the athlete's private data source reached through a platform connector, an authenticated repository, or an equivalent credentialed connection. The AI reads files directly (no URLs needed). Committing DOSSIER.md and SECTION_11.md there provides everything in one connection, and is safe only while the source is private. This delivery path supplies data only. It confers no write authority, no ability to trigger actions or workflows, and no script execution; each of those capabilities is separate and must be verified before it is used or assumed.
    • Upload or attachment: the athlete supplies the JSON files directly to the session. Uploaded files are frozen at supply time; replace them to update.
    • URL fetch: Athlete creates a repository for training data with automated sync. If the repository is public it carries JSON only; the private dossier never goes there. Record the raw URLs in the project instructions or, when a dossier is used, in its source configuration.
    • latest.json: current 7-day snapshot + 28-day derived metrics
    • history.json: longitudinal data (daily 90d, weekly 180d, monthly 3y)
    • intervals.json: per-interval segment data for recent structured sessions, plus DFA a1 session rollups when AlphaHRV recorded (14-day retention)
    • ftp_history.json: dated FTP changes (indoor/outdoor), used for staleness tracking and benchmark comparison
    • routes.json: route/terrain data for events with GPX/TCX attachments (when present)
    • saved_workouts.json: read-only mirror of the athlete's saved workouts from Intervals.icu (Saved Workouts Mirror)
    • See: https://github.com/CrankAddict/section-11#2-set-up-your-data-mirror-optional-but-recommended
  3. Configure heartbeat settings (optional, OpenClaw)

  4. Configure data discipline rule (agentic platforms with persistent identity)

    • Add to the agent's persistent configuration (SOUL.md, system prompt, custom instructions, or equivalent):
    • "Every training metric cited (watts, duration, TSS, HR, zones) must come from a JSON data read in the current response. No data read = no number. Conversation history, memory, and prior messages are not data sources."

A current JSON read is required before any numeric or prescriptive coaching. A missing or incomplete dossier limits personalization but does not block safe, data-based coaching, and unresolved dossier review items must not block unrelated coaching. Say what is missing rather than inferring it.

Protocol

Load the coaching protocol using this precedence:

  1. Check ./SECTION_11.md (data directory root)
  2. If not found, check section11/SECTION_11.md
  3. If not found, check connected repo (if GitHub connector is available)
  4. If not found, check uploaded or attached files
  5. If not found, fetch from: https://raw.githubusercontent.com/CrankAddict/section-11/main/SECTION_11.md

If both root and section11/ copies exist, prefer the root copy.

Current version: 11.70

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

Each source answers its own domain; the order is not a ranking across domains. See the Fact/source authority hierarchy in SECTION_11.md → Source Architecture Note.

  1. JSON data (always read latest.json first; read history.json only for trend, phase or longitudinal context)
  2. Protocol rules (SECTION_11.md)
  3. Athlete dossier (DOSSIER.md): stable private context only, never a current metric, from the current official copy named by its Official dossier location
  4. Interval data (intervals.json: on-demand, see below)
  5. Route/terrain data (routes.json: on-demand, when events have has_terrain: true)
  6. Saved workout inventory (saved_workouts.json): optional and on-demand for selecting, reusing, or discussing saved workouts; never a session-design authority and never a replacement for the Workout Reference Library
  7. Heartbeat config (HEARTBEAT.md)

Required Actions

  • Read or fetch latest.json before any training question. Check the data directory first, then the connected repo (if a connector is available), then uploaded or attached files, then the configured raw URLs (in the project instructions or, when a dossier is used, its source configuration).
  • Read or fetch history.json when trend analysis, phase context, or longitudinal comparison is needed. Same precedence.
  • Load intervals.json when analyzing a specific activity where has_intervals: true OR has_dfa: true. For block reports, load when any session in the block has either flag. Use for: interval compliance, pacing analysis, cardiac drift per set, recovery quality, DFA a1 session-level interpretation. Do not load for readiness, load management, or weekly summaries.
  • Load routes.json when a planned event has has_terrain: true. Use for: route analysis, terrain-adjusted pacing, pre-ride briefing, race preparation. Same precedence as other JSON files.
  • Load saved_workouts.json when selecting or reusing a saved workout, or when the athlete asks about their saved workouts. Do not load it for every training question or report. It is the preferred read path for saved workouts on every platform, because it avoids repeated API retrieval and is faster and cheaper to consume. On API-connected platforms, use the Intervals.icu API for edits, and as a read fallback when the mirror is missing, unavailable, stale, inconsistent, or lacks required data. The mirror is read-only and never grants write authority. Check refresh.status before use: ok means the snapshot was verified at refresh.last_success_at, stale means a retained older snapshot after a failed refresh, unavailable means no snapshot has ever succeeded. consistency: endpoints_disagree means the two upstream endpoints did not agree; treat folder membership as indicative. A saved workout may be prescribed only after verifying that its structure implements an applicable Workout Reference Library template or permitted variant. saved_workouts.json is never evidence of what was prescribed for a completed activity: historical compliance requires a verified Intervals.icu activity/event pairing or an authoritative prescription supplied in context, and the local JSON mirrors do not carry the prescription.
  • Before prescribing a structured session, including a familiar workout the athlete names or a saved workout proposed for reuse, identify the Workout Reference Library template it implements (Section 11 B §8). Load WORKOUT_REFERENCE.md from section11/examples/workout-library/, then the connected repo, then uploaded or attached files, then https://raw.githubusercontent.com/CrankAddict/section-11/main/examples/workout-library/WORKOUT_REFERENCE.md. If it cannot be loaded, say so rather than improvising a structure.
  • For all files (JSON data, protocol, dossier, templates): data directory → connected repo → uploaded/attached files → URL fetch. For the dossier this order only locates copies: authority belongs to the current official copy named by its Official dossier location, and conflicting copies go to the athlete.
  • No virtual math on pre-computed metrics. Use values from the JSON for CTL, ATL, TSB, ACWR, RI, zones, etc. Custom analysis from raw data is fine when pre-computed values don't cover the question.
  • Every training metric cited (in reports, recommendations, or conversation) must come from a JSON data read in the current response. Conversation history, memory, and prior messages are not data sources.
  • Stable athlete facts (tested fueling or tolerance, medication or allergies, equipment, carrying capacity, durable constraints or preferences) come from the relevant section of the current official dossier, read when the task depends on them. A JSON read does not supply them, and conversation history, memory and superseded copies are not sources for them. If no dossier is used, the official copy is unreachable, or it has no entry, say so rather than presenting a generic default as the athlete's own. An explicit current athlete statement that contradicts the dossier is resolved by clarification and a proposed dossier change, never silently.
  • When health_context.clarification_required is true in latest.json, do not recommend the planned session without addressing it. A marker in current means acknowledge the illness or injury and establish severity. A marker in recent with none current means the calendar marking stopped, not that the athlete recovered. Ask, do not assume. When source_status is partial and no marker is visible, say that health markers could not be checked completely and confirm whether illness or injury is currently relevant. A marker does not discard or replace the plan: the planned session remains the starting candidate (not presumed clearance) until severity and compatibility are established, and minor illness or injury may still allow it as written or in modified form. It is not a readiness signal, does not by itself mean skip or deload, and never relaxes an existing Skip. See Health Context in SECTION_11.md.
  • Check zone_preference in READ_THIS_FIRST and zone_basis fields on TID/zone blocks. The athlete may have configured HR-preferred zones for specific sports (e.g., running). When zone_basis is not the default "power", note this in reports.
  • Follow Section 11 C validation checklist before generating recommendations
  • Cite frameworks per protocol (checklist item #10)
Show full SKILL.md (943 more words)Show less

Write Capabilities

If push.py is available (section11/examples/agentic/push.py or in the data repo), the skill can manage the athlete's Intervals.icu calendar and training data:

  • push: write planned workouts to calendar
  • list: show planned workouts for a date range
  • move: reschedule a workout to a different date
  • delete: remove a workout from the calendar
  • set-threshold: update sport-specific thresholds (FTP, indoor FTP, LTHR, max HR, threshold pace). Only after validated test results, never from estimates
  • annotate: 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. Nothing is written without --confirm. Execution via local CLI or GitHub Actions dispatch. See examples/agentic/README.md for full usage, workout syntax, and template ID mappings.

Requires a runtime that can execute code or trigger repository actions, with verified access and configured credentials, not merely a platform labelled agentic. Web chat cannot use this. Grok Bot and Hermes Agent have the required capability class but are experimental: neither is validated end to end against the Section 11 pipeline, and capability class is not a support promise. A connector supplies data only: it confers no write authority, no ability to trigger actions or workflows, and no script execution. Each of those capabilities is separate and must be verified before it is used or assumed.

Verified-write rule. Apply an approved dossier change only against a location whose write access has actually been verified. Otherwise return the revised file and state plainly that the source was not updated. Never emit a full replacement dossier unless the complete current file is in context; with only an excerpt, return the changed section clearly labelled as a fragment.

Report Templates

Use standardized report formats. Load templates using this precedence:

  1. Check data directory reports/ directory
  2. If not found, check section11/examples/reports/
  3. If not found, check connected repo (if GitHub connector is available)
  4. If not found, check uploaded or attached files
  5. If not found, fetch from: https://raw.githubusercontent.com/CrankAddict/section-11/main/examples/reports/

Templates:

  • Pre-workout: Readiness assessment, Go/Modify/Skip recommendation: PRE_WORKOUT_REPORT_TEMPLATE.md
  • Post-workout: Session metrics, plan compliance, weekly totals: POST_WORKOUT_REPORT_TEMPLATE.md
  • Weekly: Week summary, compliance, phase context: WEEKLY_REPORT_TEMPLATE.md
  • Block: Mesocycle review, phase progression: BLOCK_REPORT_TEMPLATE.md
  • Brevity rule: Brief when metrics are normal. Detailed when thresholds are breached or athlete asks "why."

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 Section 11 operates no hosted backend. Data moves only through services the athlete explicitly configures. Any AI, runtime, model, connector, repository or storage providers actually involved have their own processing and retention terms. See the README's Privacy & Security section for the full statement.

The skill reads from: user-configured JSON data sources and DOSSIER.md at its recorded location, and HEARTBEAT.md in the agent workspace.

It writes to DOSSIER.md only to apply a change the athlete has explicitly approved, against a location whose write access has been verified, at first-use creation and at every subsequent maintenance change alike. See SECTION_11.md → Update & Version Guidance for the full lifecycle and approval rules.

It writes to HEARTBEAT.md in the agent workspace during first-use setup, following that file's own setup flow. HEARTBEAT is agent configuration, not athlete context, and is not governed by the dossier lifecycle.

Data Handling sync.py redacts athlete_id from the output (always on, unconditional). Activity names are passed through as-is. They carry coaching context (route identification, terrain association). All other training data (activities, wellness, intervals, power/HR values, dates) is passed through to the AI coach as-is.

Network behavior When running locally (files in the data directory), no network requests are needed for protocol, templates, or data. When files are not available locally, the skill fetches them from configured sources.

Credentials are sent only to the service they authenticate, and only when that service is configured: sync.py sends the Intervals.icu key in an Authorization header to Intervals.icu, and the GitHub token to GitHub when publishing or issue creation is configured. Credentials are never written into exported or published JSON. Fetched content comes from sources the athlete has explicitly configured; published content goes to services the athlete has explicitly configured. Chat retention is governed by the AI platform's terms, not by Section 11.

Recommended setup: local files The safest and simplest setup is fully local: sync.py on a timer, all files on your device. See examples/json-local-sync/SETUP.md for the complete local pipeline. If you use GitHub, use a private repository. See examples/json-auto-sync/SETUP.md for automated sync setup.

Protocol and template URLs The GitHub URLs are fallbacks for when local files aren't available. 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 with repository access configured: can read and write repositories that the agent's token or key allows
  • Running on a provider-hosted agent computer: reads and writes that computer's filesystem, which is not the athlete's machine. Where such a computer is shared across the athlete's other agents, a private dossier placed there is reachable by all of them, and deleting an agent does not necessarily remove the file

Access is entirely governed by credentials the user has already configured in their environment.

© CrankAddict, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 93 other files in the repository root of CrankAddict/section-11.

  • SKILL.md
  • .github/site/.gitignore
  • .github/site/README.md
  • .github/site/build.cjs
  • .github/site/generate-icons.cjs
  • .github/site/icons/apple-touch-icon.png
  • .github/site/icons/favicon.ico
  • .github/site/icons/favicon.svg
  • .github/site/icons/icon-192.png
  • .github/site/icons/icon-512.png
  • .github/site/icons/icon-maskable-512.png
  • .github/site/icons/site.webmanifest
  • .github/site/package-lock.json
  • .github/site/package.json
  • .github/site/pages.json
  • .github/site/site.css
  • .github/site/test.cjs
  • .github/workflows
  • … and 76 more

Open the folder on GitHubat commit 83e2775

Compare with similar skills

Section 11 next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Section 11 compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Section 11 this skillCrankAddict/section-11156—~5.2kAutomated safety check: PassMIT
Coachfelixrieseberg/claude-coach1991 repos~4.9kAutomated safety check: PassMIT
Fitness Analyzerhuifer/WellAlly-health9605 repos~1.3kAutomated safety check: PassMIT
Master Ajahn Chahxr843/Master-skill4471 repos~2kAutomated safety check: PassCC-BY-NC-SA-4.0
Mental Health Analyzerhuifer/WellAlly-health9605 repos~3.2kAutomated safety check: PassMIT
Nutrition Analyzerhuifer/WellAlly-health9605 repos~3.3kAutomated safety check: PassMIT

Similar skills

  • Coach

    felixrieseberg/claude-coach

    Create personalized triathlon, marathon, and ultra-endurance training plans.

    199 GitHub starsUsed in 1 repo~4.9k tokens
    Productivity & AutomationAuto-check passed
  • Fitness Analyzer

    huifer/WellAlly-health

    分析运动数据、识别运动模式、评估健身进展,并提供个性化训练建议。支持与慢性病数据的关联分析. An agent skill from huifer/WellAlly-health.

    960 GitHub starsUsed in 5 repos~1.3k tokens
    Productivity & AutomationAuto-check passed
  • Master Ajahn Chah

    xr843/Master-skill

    A skill your agent uses when user asks about 南传佛教, 上座部, Theravada, 巴利经典, 正念 sati, 放下, 三法印, 四念处, 出入息念 anapanasati, 戒定慧, 毗婆舍那, 森林禅林派, 巴蓬寺, 阿姜查, 杜多行, 中道, or wants teaching in 阿姜查 Ajahn Chah's voice.

    447 GitHub starsUsed in 1 repo~2k tokens
    Productivity & AutomationAuto-check passed
  • Mental Health Analyzer

    huifer/WellAlly-health

    分析心理健康数据、识别心理模式、评估心理健康状况、提供个性化心理健康建议。支持与睡眠、运动、营养等其他健康数据的关联分析。

    960 GitHub starsUsed in 5 repos~3.2k tokens
    Productivity & AutomationAuto-check passed
  • Nutrition Analyzer

    huifer/WellAlly-health

    分析营养数据、识别营养模式、评估营养状况,并提供个性化营养建议。支持与运动、睡眠、慢性病数据的关联分析. An agent skill from huifer/WellAlly-health.

    960 GitHub starsUsed in 5 repos~3.3k tokens
    Productivity & AutomationAuto-check passed
  • Ghealth

    Google-Health-API/google-health-cli

    Query Google Health API v4 — steps, heart rate, exercise, sleep, weight, SpO2, HRV, ECG, blood glucose, nutrition, and 40 total data types

    266 GitHub stars~2.3k tokensUpdated 3 mo ago
    Productivity & AutomationAuto-check passed

Questions about Section 11

What does Section 11 do?

Evidence-based endurance coaching protocol (v11.70). An agent skill from CrankAddict/section-11. Section 11 is an agent skill from CrankAddict/section-11.70).

When should I use Section 11?

Section 11 fits situations like: analyzing training data; reviewing sessions; generating pre/post-workout reports; planning workouts.

How do I install Section 11 in Claude Code?

Run `npx skills add CrankAddict/section-11 --skill section-11 -a claude-code`. Or copy the skill folder (the CrankAddict/section-11 repository) into .claude/skills/section-11 in your project. Claude Code loads it when a task matches its description.

How do I install Section 11 in Codex?

Run `npx skills add CrankAddict/section-11 --skill section-11 -a codex`. Or copy the skill folder (the CrankAddict/section-11 repository) into .agents/skills/section-11 in your project. Codex loads it when a task matches its description.

Can I use Section 11 in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add CrankAddict/section-11 --skill section-11 -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/section-11, .gemini/skills/section-11, .github/skills/section-11 and .opencode/skills/section-11 in your project.

What does Section 11 need to run?

Going by SKILL.md and its folder, Section 11 needs JavaScript for the scripts in its folder.

Does Section 11 access the network?

SKILL.md names 1 domain. As links in the text: github.com. This is read from the text; nothing was executed.

Is Section 11 safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Section 11 use?

Section 11 is published under the MIT licence (from the LICENSE file in the skill folder). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Section 11 use?

About 5.2k tokens (SKILL.md is roughly 21k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Section 11?

Skills that share tags, products or a category with Section 11: Coach (felixrieseberg/claude-coach, 199 stars), Fitness Analyzer (huifer/WellAlly-health, 960 stars), Master Ajahn Chah (xr843/Master-skill, 447 stars) and Mental Health Analyzer (huifer/WellAlly-health, 960 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Section 11?

CrankAddict (a GitHub user) maintains it in CrankAddict/section-11, which has 156 GitHub stars. The repository was last updated on October 4, 2026.

Source: CrankAddict/section-11 on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.