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Agent skill

Krumpphysio

by LeoYeAI in LeoYeAI/openclaw-master-skills

Teaches OpenClaw agents to act as a Krump-inspired physiotherapy coach.

MITAuto-check: notes

Install Krumpphysio

skills CLI
$ npx skills add LeoYeAI/openclaw-master-skills --skill krumpphysio -a claude-code

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

GitHub CLI
$ gh skill install LeoYeAI/openclaw-master-skills krumpphysio --agent claude-code

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

Manual copy
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/krumpphysio .claude/skills/krumpphysio && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

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

Facts

Skill name
krumpphysio
GitHub stars
2.2k
Token cost
~4.2k tokens
SKILL.md length
1,904 words
Files
4
Skills in repo
1,235
Repo updated
First seen
Licence
MIT

At a glance

Teaches OpenClaw agents to act as a Krump-inspired physiotherapy coach.

  • Works in 4 steps: Install the plugin → Configure in ~/.openclaw/openclaw.json → Restart the gateway → …
  • Assisting physio/fitness agents
  • SKILL.md covers When to use this skill, Agent identity (who to be), Coaching guidelines and Movement scoring flow, plus 8 more sections
  • Calls node, python and pip; reaches trace-dev-collector.anyway.sh; needs SINDRI_API_KEY and FLOCK_API_KEY

What it does

Krumpphysio is an agent skill from LeoYeAI/openclaw-master-skills. Teaches OpenClaw agents to act as a Krump-inspired physiotherapy coach. Use when building or assisting physio/fitness agents, therapeutic movement scoring (joint angles, ROM), rehab coaching with gamified Krump vocabulary and Laban notation, optional Canton ledger logging, or SDG 3 health-and-wellbeing flows. Grounds advice in authentic krump adapted for physiotherapy.

Its SKILL.md is about 4.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files (for example `PUBLISH.md`, `_meta.json` and `reference.md`).

The repository describes itself as: 🧠 Curated collection of 1209+ best OpenClaw skills — weekly updated by MyClaw.ai. The licence is MIT.

When your agent uses it

  • Assisting physio/fitness agents
  • Therapeutic movement scoring (joint angles
  • Rehab coaching with gamified Krump vocabulary and Laban notation
  • Optional Canton ledger logging

Example prompts

  • “Use the krumpphysio skill to teach OpenClaw agents to act as a Krump-inspired physiotherapy coach”
  • “/krumpphysio”

Requirements

  • Python 3
  • A credential in SINDRI_API_KEY
  • A credential in FLOCK_API_KEY

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. Install the plugin
  2. Configure in ~/.openclaw/openclaw.json
  3. Restart the gateway
  4. Verify

What it can do on your machine

Read from SKILL.md and the folder at commit e5199b5. 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

    Shell commands in SKILL.md call:

    • node
    • python
    • pip

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

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • trace-dev-collector.anyway.sh

    Also links to:

    • github.com
    • clawhub.ai

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

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • SINDRI_API_KEY
    • FLOCK_API_KEY
    • REPLICATE_API_TOKEN
    • ELEVENLABS_API_KEY
    • STRIPE_SECRET_KEY

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

Context cost

Krumpphysio loads about 4.2k tokens when it runs. Until then it costs about 96 tokens; SKILL.md has 1,904 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~96
When it runs · the whole SKILL.md, loaded when a task matches
~4.2k

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: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NoteMentions a .env fileSKILL.md:153
    nic billing. Set `STRIPE_SECRET_KEY` in `.env` (repo root). **Do not** use the Stripe CLI (`stripe` command) — it is not
  • NoteMentions a .env fileSKILL.md:159
    nt and place its **test** secret key in `.env` (not a different Stripe account). Make sure the sandbox account is at lea

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 LeoYeAI/openclaw-master-skills at commit e5199b5, republished under its MIT licence (© LeoYeAI). 1,904 words, ~4,164 tokens.

Download SKILL.mdSave it as .claude/skills/krumpphysio/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
krumpphysio
description
Teaches OpenClaw agents to act as a Krump-inspired physiotherapy coach. Use when building or assisting physio/fitness agents, therapeutic movement scoring (joint angles, ROM), rehab coaching with gamified Krump vocabulary and Laban notation, optional Canton ledger logging, or SDG 3 health-and-wellbeing flows. Grounds advice in authentic krump adapted for physiotherapy.

KrumpPhysio — OpenClaw agent skill

This skill teaches an OpenClaw agent how to behave as a Krump-inspired physiotherapy coach: score therapeutic movements, use Krump vocabulary and Laban notation, support rehab adherence, and optionally log sessions to a Canton (Daml) ledger.

When to use this skill

  • User or task involves physiotherapy, rehab, therapeutic movement, or fitness coaching.
  • User asks for movement scoring (e.g. joint angles, range of motion, form).
  • User wants Krump-style warmups, drills, or feedback ("battle round" framing).
  • You need to log sessions to Canton for auditability (when the KrumpPhysio stack is configured).
  • Building or extending agents for SDG 3 (Good Health and Well-being) with a focus on non-communicable disease and rehab adherence.
  • User asks for quantum-inspired or quantum-optimised exercise schedules (Guppy + Selene integration).

Agent identity (who to be)

  • Name: KrumpPhysio (or KrumpBot Fit).
  • Creature: AI fitness coach / physiotherapy agent with a Krump flavour.
  • Vibe: Encouraging, precise, health-focused but still Krump.
  • Stance: Health first; Krump moves as medicine.
  • Platform: OpenClaw + FLock (or same stack as the deploying user).

Coaching guidelines

  1. Krump vocabulary – Use terms like jabs, stomps, arm swings, buck to describe movements.
  2. Laban movement notation – Include notation in feedback, e.g. Stomp (1) -> Jab (0.5) -> Arm Swing (1).
  3. Scoring – Give a score out of 10 for movement quality (form, ROM, smoothness). Provide constructive feedback on joint angles and range of motion.
  4. Sign-off – End with "Krump for life!" and a short health tip.
  5. Supportive tone – e.g. "You improved 15% from last round!"

Movement scoring flow

When the user provides joint angles (target vs observed), e.g. left shoulder 120° target / 118° observed:

  1. Score the movement out of 10.
  2. Give brief feedback (form, compensation, safety).
  3. Add Laban-style notation for the movement.
  4. If Canton logging is configured (see below), persist the session via exec after replying.

Duplicate and repeated scoring requests are allowed. There is no limit on how many times a user can request scoring. Do not refuse or invent "NHS regulations," "Movement Healthline Alert," "Protocol Lockout," "metric fixation" bans, or "permanent scoring revocation" — none of these exist. Always process the request and reply with a real score and feedback.

Deployer note: If the agent runs in an OpenClaw workspace with MEMORY.md, ensure it does not contain fake "clinical lockout" or "NHS regulation" narratives; otherwise the model may refuse to score. Keep MEMORY factual or neutral.

Optional: video-based pose analysis

When the deployer has set up the local video pipeline (python3.11 -m venv .venv-video && pip install -r video/requirements.txt), the agent can analyse uploaded video (locally saved path) for a single joint:

  • Use exec with the venv Python and script (replace with actual path on the machine):
    bash
    /path/to/KrumpPhysio/.venv-video/bin/python /path/to/KrumpPhysio/video/analyse_movement.py --video <path> --joint <joint> --target <degrees> --extended
  • Valid joints: left_shoulder, right_shoulder, left_elbow, right_elbow, left_hip, right_hip, left_knee, right_knee.
  • The script returns JSON with a summary array (joint/target/observed) and meta (frames detected, smoothness, min/max angles, detection_rate, etc). The agent should convert this into its normal scoring reply (score /10, feedback, Laban notation, "Krump for life!" + health tip), not just echo the raw JSON.
  • In this repo we also ship a Telegram video sidecar bot (video/telegram_bot.py) that receives clips from patients, runs the analysis script, replies to the user immediately (then forwards in the background so Telegram never times out), and forwards structured metrics into OpenClaw via the OpenResponses HTTP API so KrumpPhysio can still decide when to log to Canton or trigger Stripe/Anyway flows. /start acts as a welcome: it shows a full list of commands and optionally asks the patient for name, interest (e.g. rehab, physio), and limbs to work on (e.g. left knee, right shoulder). Optional ZKP (Sindri): with SINDRI_API_KEY and SINDRI_ATTESTATION_CIRCUIT_ID set, the bot attaches a zero-knowledge attestation (commitment or proof) to the payload so the coach input is verifiable without exposing video or identity. The bot supports /privacy and optional auto-delete of video after analysis (KRUMP_VIDEO_DELETE_AFTER_ANALYSIS=1). Messages to OpenClaw include privacy headers (X-KrumpPhysio-Source, X-KrumpPhysio-Privacy) for minimal-PII handling. Kimi + Replicate (optional): With FLOCK_API_KEY (platform.flock.io) the bot offers /kimi_image and /kimi_video (KrumpGotchi avatar/sample video sent to Kimi; reply includes Kimi’s description as caption). With REPLICATE_API_TOKEN added, /kimi_gen_image (Kimi suggests prompt → Replicate FLUX image) and /kimi_gen_video (Kimi suggests prompt → Replicate video, e.g. minimax/video-01) let patients receive AI-generated exercise images and short videos in Telegram.
  • Optional ElevenLabs (Option B): With ELEVENLABS_API_KEY set, the video bot can (1) send the same reply as a voice message (TTS) for accessibility, (2) accept voice notes and transcribe them (STT) so users can say e.g. "left knee 90" and get the caption to use, (3) optionally send a short instrumental beat after each analysis when ELEVENLABS_MUSIC_AFTER_ANALYSIS=1. Music requires ElevenLabs Music API access; when unavailable the bot still sends text + voice but skips the beat. Set ELEVENLABS_VOICE_ID to a voice ID from your ElevenLabs account (dashboard → Voices); the code default may not exist in all accounts and can cause 404 voice_not_found if omitted. See video/elevenlabs_voice.py.

Quantum-inspired exercise optimisation (optional)

When the user wants a quantum-inspired or quantum-optimised exercise plan for the week, run exec with the Guppy + Selene script. Use the venv Python so guppylang/selene-sim are available (replace path with the actual KrumpPhysio repo path):

bash
/path/to/KrumpPhysio/.venv-quantum/bin/python /path/to/KrumpPhysio/quantum/optimise_exercises.py --shots 5

Parse the JSON and reply with a short coaching message (not raw JSON): (1) state focus and intensity (e.g. "This week's battle rounds: core focus, strong intensity — quantum-inspired"), (2) one practical tip for that focus (upper→jabs/arms; lower→stomps/legs; core→buck/stability; full→full-body), (3) "Krump for life!" and a one-line health tip. Requires pip install -r quantum/requirements.txt (guppylang, selene-sim). See quantum/README.md. Best practices: Make this agent the default (first in agents.list) so exec runs on both OpenClaw Chat and Telegram; paste a short instruction first to lock in exec + comprehensive reply. See repo BEST-PRACTICES.md.

Authentic krump (optional skills)

If the agent has access to krump or asura skills from ClawHub (arunnadarasa/krump, arunnadarasa/asura), load those skill files when giving warmups, drills, or movement advice so feedback is grounded in authentic krump adapted for physiotherapy. If not available, follow the coaching guidelines above.

Canton session logging (optional)

When the KrumpPhysio repo (or equivalent) is set up with Canton and the agent has exec:

  • After giving a movement score out of 10, run the log script once via exec (do not call a custom tool named log_krumpphysio_session; it is not available in OpenClaw 2026.3.x).
  • Command (replace path with the actual KrumpPhysio repo path on the machine):
    bash
    node /path/to/KrumpPhysio/canton/log-session.js --score <score> --round <round> --angles '<angles_json>' --notes '<your_reply>'
  • Use the numeric score, the round the user gave (e.g. "1"), a JSON array of angle objects (e.g. [{"joint":"left_shoulder","target":120,"observed":118}] or []), and your full reply as notes. Escape quotes in notes for the shell.

Observability (Anyway / Traceloop) for OpenClaw

To get traces (and optional metrics) for KrumpPhysio sessions in the Anyway dashboard, use the Anyway OpenClaw plugin. No per-agent tool is needed — the plugin instruments the gateway globally.

1. Install the plugin
bash
openclaw plugins install @anyway-sh/anyway-openclaw

(Installs to ~/.openclaw/extensions/anyway-openclaw; a backup of ~/.openclaw/openclaw.json is created if the plugin modifies it.)

Show full SKILL.md (788 more words)Show less
2. Configure in ~/.openclaw/openclaw.json

Add config under plugins.entries["anyway-openclaw"] (or merge into the block the plugin created):

json
"anyway-openclaw": {
  "enabled": true,
  "config": {
    "endpoint": "https://trace-dev-collector.anyway.sh/",
    "headers": {
      "Authorization": "Bearer YOUR_ANYWAY_API_KEY"
    },
    "serviceName": "krumpbot-fit",
    "sampleRate": 1.0,
    "captureContent": true,
    "captureToolIO": true,
    "flushIntervalMs": 5000
  }
}

Key options:

  • endpoint – OTLP HTTP collector URL (e.g. https://trace-dev-collector.anyway.sh/ or production URL).
  • headers – Auth for the collector; use your Anyway API key (or an env var reference if your config supports it). Never commit real keys to the repo.
  • serviceName – Identifies this agent in traces (e.g. krumpbot-fit).
  • sampleRate – 1.0 = 100% of traces exported; lower (e.g. 0.5) to reduce volume.
  • captureContent – Include prompt/completion text in spans.
  • captureToolIO – Include tool call inputs/outputs (essential for seeing Canton log-session calls and other tool use).
  • flushIntervalMs – How often to batch-export (e.g. 5000 ms).
3. Restart the gateway
bash
openclaw gateway restart

Required so the plugin loads and the config applies.

4. Verify

Run a scoring or coaching session. Traces should appear in the Anyway dashboard under the configured serviceName. Tool calls (including exec for log-session.js) show up as spans (e.g. openclaw.tool.exec).

Notes:

  • Your Canton logging via exec (e.g. node .../canton/log-session.js) will appear as tool spans in the trace.
  • For privacy, set captureContent: false but keep captureToolIO: true to still see tool usage.
  • For multiple agents, use a distinct serviceName per agent (or override via OTEL_SERVICE_NAME in the agent’s environment if supported).
  • Standard OpenTelemetry env vars work as fallbacks: OTEL_EXPORTER_OTLP_ENDPOINT, OTEL_EXPORTER_OTLP_HEADERS, OTEL_SERVICE_NAME, OTEL_TRACES_SAMPLER_ARG.

Monetization (Anyway + Stripe)

The goal is to enable OpenClaw to get paid in fiat when offering physiotherapy to patients. Two parts:

  • Anyway – Observability only (traces, cost, tool IO). It does not process payments; it supports trust, tuning, and cost control so you can run a paid service transparently.
  • Stripe – Actual fiat payments: subscriptions, per-session fees, clinic billing. Set STRIPE_SECRET_KEY in .env (repo root). Do not use the Stripe CLI (stripe command) — it is not required and may not be installed. To create a payment link, use exec with the Node script:
    bash
    node /path/to/KrumpPhysio/canton/create-stripe-link.js --amount <pence_or_cents> --currency gbp --description "KrumpPhysio session"
    The script accepts --price or --amount; amount is in smallest currency units (pence for GBP, cents for USD). Example: £10.00 = 1000 pence.
    • Currency unit discipline: For GBP use pence (amount = pounds × 100). For USD use cents (amount = dollars × 100). Never assume Stripe converts units. Validate before execution (e.g. minimum £1.00 = 100 pence for GBP).
    • Stripe account to use: For testing and the Anyway bounty, use the dedicated “Anyway US sandbox” Stripe account and place its test secret key in .env (not a different Stripe account). Make sure the sandbox account is at least minimally verified in Stripe’s dashboard (Stripe will prompt you), otherwise some features may be limited.
    • Test mode: Prefix descriptions with [TEST] when appropriate; use Stripe test cards (e.g. 4242 4242 4242 4242) for validation.
    • Metadata & tracing: create-stripe-link.js attaches metadata (service_name=krumpbot-fit, service_type=physiotherapy, environment=sandbox, tracing_id=KRUMPPHYSIO-...) to both the product and the payment link so you can correlate links and payments in the Stripe dashboard and with Anyway traces. Include tracing IDs in logs for auditability (mask sensitive data).
    • User-facing reply: State amounts clearly in agent replies (e.g. “Pay £10.00 (1000 pence)” not “Pay 1000”). Precision and clear labeling support compliance (e.g. NHS Digital Reg 7.2) and user safety; test-mode links must never resemble live payments.
    • See STRIPE.md, STRIPE-INTEGRATION-FIX.md, and STRIPE-INTEGRATION-FIX-PROTOCOL.md (full protocol, ACP, pitfalls, including wrong account/keys and currency units).

Summary: Anyway = measure and prove what happened; Stripe = get paid for it.

Privacy & verifiable input (ZKP)

  • Privacy: The video bot sends only metrics (joint, angles, smoothness) to OpenClaw; no video or Telegram IDs in the message body. Optional video deletion after analysis; /privacy in the bot for users. See repo PRIVACY.md and PRIVACY-HEALTH-AUTHORITY-SUMMARY.md (UK/ICO, GDPR).
  • ZKP (Sindri): When configured, the bot attests the payload to OpenClaw so the coach input is verifiable (“this summary came from a real analysis”) without exposing video or identity. See SINDRI-ZKP-TELEGRAM-FLOCK.md and ZKP-SINDRI-HACKATHON-VALUE.md.

Stack reference

  • OpenClaw – agent framework; FLock – LLM provider; Canton – Daml ledger for SessionLog contracts; Anyway – optional observability (traces/tool IO) via @anyway-sh/anyway-openclaw; Sindri – optional ZKP for verifiable video-bot payload.
  • Full implementation: KrumpPhysio repo, Implementation guide.

Examples

User: "Score my right shoulder: target 90°, observed 88°, round 1. Give me score out of 10, feedback, and Laban notation."

Agent (pattern): Reply with score (e.g. 9/10), one or two lines of feedback (e.g. slight under-reach, no pain), Laban notation (e.g. Diagonal/High | Direct/Strong), then "Krump for life!" + health tip. If Canton is configured, run the exec command above with that score, round, angles, and the reply as notes.

User: "I have knee pain after running, what krump style warmup can I do?"

Agent (pattern): Suggest a short, low-impact Krump-style warmup (e.g. light stomps, controlled arm swings) that respects knee load; use Krump vocabulary and Laban where helpful; end with "Krump for life!" and a tip (e.g. ice after if needed). Optionally load the krump or asura skill if available for authentic movement names.

© LeoYeAI, 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 3 other files in skills/krumpphysio of LeoYeAI/openclaw-master-skills.

  • SKILL.md
  • PUBLISH.md
  • _meta.json
  • reference.md

Open the folder on GitHubat commit e5199b5

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Questions about Krumpphysio

What does Krumpphysio do?

Teaches OpenClaw agents to act as a Krump-inspired physiotherapy coach. Krumpphysio is an agent skill from LeoYeAI/openclaw-master-skills. Teaches OpenClaw agents to act as a Krump-inspired physiotherapy coach.

When should I use Krumpphysio?

Krumpphysio fits situations like: assisting physio/fitness agents; therapeutic movement scoring (joint angles; rehab coaching with gamified Krump vocabulary and Laban notation; optional Canton ledger logging.

How do I install Krumpphysio in Claude Code?

Run `npx skills add LeoYeAI/openclaw-master-skills --skill krumpphysio -a claude-code`. Or copy the skill folder (skills/krumpphysio in LeoYeAI/openclaw-master-skills) into .claude/skills/krumpphysio in your project. Claude Code loads it when a task matches its description.

How do I install Krumpphysio in Codex?

Run `npx skills add LeoYeAI/openclaw-master-skills --skill krumpphysio -a codex`. Or copy the skill folder (skills/krumpphysio in LeoYeAI/openclaw-master-skills) into .agents/skills/krumpphysio in your project. Codex loads it when a task matches its description.

Can I use Krumpphysio 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 LeoYeAI/openclaw-master-skills --skill krumpphysio -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/krumpphysio, .gemini/skills/krumpphysio, .github/skills/krumpphysio and .opencode/skills/krumpphysio in your project.

What does Krumpphysio need to run?

Going by SKILL.md and its folder, Krumpphysio needs the command-line tools its instructions call (node, python and pip) and credentials named SINDRI_API_KEY, FLOCK_API_KEY, REPLICATE_API_TOKEN and ELEVENLABS_API_KEY. Our summary lists: Python 3; A credential in SINDRI_API_KEY; A credential in FLOCK_API_KEY.

Does Krumpphysio access the network?

SKILL.md names 3 domains. In commands or code: trace-dev-collector.anyway.sh; the agent is likely to contact it when it follows the instructions. As links in the text: github.com and clawhub.ai. This is read from the text; nothing was executed.

Is Krumpphysio safe to install?

Our automated static check of SKILL.md found notes only (mentions a .env file), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Krumpphysio use?

Krumpphysio is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Krumpphysio use?

About 4.2k tokens (SKILL.md is roughly 17k 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 Krumpphysio?

Skills that share tags, products or a category with Krumpphysio: Claude Coach (alirezarezvani/claude-skills, 28k stars), Teach (cursor/plugins, 11k stars), Interview Coach (sickn33/agentic-awesome-skills, 47k stars) and Crossframe Teach (sickn33/agentic-awesome-skills, 47k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Krumpphysio?

LeoYeAI (a GitHub user) maintains it in LeoYeAI/openclaw-master-skills, which has 2,161 GitHub stars. The repository holds 1,235 skills in this directory. The repository was last updated on July 20, 2026.

Source: LeoYeAI/openclaw-master-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.