A structured observation tool to help users record and identify routine-based patterns behind afternoon crashes, brain fog, and evening energy fluctuations.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install energy-crash-pattern-log
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install energy-crash-pattern-log using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Energy Crash Pattern Log?
The Energy Crash Pattern Log is a specialized tool within the Openclaw Skills ecosystem designed to transform vague feelings of fatigue into actionable data. By utilizing a 7-day observation framework, this skill enables users to systematically track energy levels alongside sleep, meal timing, caffeine intake, and workload intensity. It serves as a non-diagnostic bridge between feeling drained and understanding the lifestyle variables that may be influencing those dips.
Rather than offering medical advice, this skill focuses on neutral data collection. It provides a clear 1-5 energy scale and a comprehensive logging structure that allows users to spot protective factors or routine links. Whether you are dealing with a 3 PM slump or a late-night second wind, this Openclaw Skills resource helps you build a factual record of your daily vitality.
Energy Crash Pattern Log Use Cases
- Identifying recurring afternoon or evening energy crashes that impact work or personal productivity.
- Tracking post-meal brain fog or motivation slumps to see if they correlate with specific timing or habits.
- Documenting "wired but tired" patterns where energy spikes occur right before bedtime.
- Preparing a detailed, observation-based summary of energy patterns to share with a healthcare professional.
- Testing low-risk routine experiments, such as adjusting sunlight exposure or screen breaks, to see how they impact daily focus.
How Energy Crash Pattern Log Works
- Initial Assessment: The skill defines the specific crash window, duration, and frequency of the user's fatigue.
- Scale Calibration: It establishes a consistent 1-5 energy scale to ensure logging remains objective and simple.
- Framework Generation: A 7-day energy pattern log is created, featuring slots for hydration, stress, screen load, and movement.
- Daily Data Entry: The user records short entries at 2-4 anchor times per day to minimize tracking friction.
- Pattern Analysis: After the logging period, the skill reviews the data to identify routine links and potential protective factors.
- Experimentation: The system suggests tiny, low-risk habit adjustments based on the logged evidence.
- Reporting: If concerns persist, it generates a concise summary for a doctor-visit preparation.
Energy Crash Pattern Log Setup
To activate this skill within your environment, ensure you have the Openclaw Skills framework configured. You can initialize the observation log using the following command structure:
# Initialize the energy observation workflow
openclaw run energy-crash-pattern-log --days 7
No complex integration is required; simply provide your initial crash window details when prompted to generate your custom tracking table.
Energy Crash Pattern Log Data Schema & Taxonomy
The Energy Crash Pattern Log organizes information into a structured multi-part schema to ensure clarity and ease of review:
| Data Component | Description |
|---|---|
| Energy Snapshot | High-level summary of the crash window, frequency, and disruption level. |
| Energy Scale | A standardized 1-5 scoring system from 'Depleted' to 'Strong Energy'. |
| Observation Log | A matrix mapping time blocks to variables like Sleep, Meals, Caffeine, and Screen Load. |
| Pattern Review | A table highlighting evidence-based observations and confidence levels. |
| Experiment Menu | A list of proposed changes with specific tracking metrics. |
| Clinician Note | A formatted summary of symptoms and duration for professional review. |
Energy Crash Pattern Log Advanced Features
- Custom Logging Blocks: Flexibility to switch between hourly, morning/afternoon/evening, or custom time-block intervals.
- Clinician-Ready Export: Automatically formats raw log data into a concise summary suitable for medical consultations.
- Variable Correlation: Links external stressors, such as workload intensity and screen time, directly to energy scores.
- Low-Friction Mode: Reduces tracking requirements to 3 check-ins per day for users experiencing high burnout or overwhelm.
- Experimentation Framework: Provides a structured way to test and validate the effectiveness of small routine changes.
SKILL.md
Loading
Related Openclaw Skills
teach-gen
A powerful AI skill that converts static educational documents into interactive, animated HTML teaching pages.
Paycheck Error Review Kit
A professional administrative workflow designed to transform paycheck discrepancies into organized, evidence-backed review packets for HR or payroll departments.
Chrome AI Action
A comprehensive browser automation skill that allows AI agents to control Chrome via a Puppeteer-based bridge for navigation, interaction, and data extraction.
WebVoyager
WebVoyager is a multimodal web automation agent that utilizes visual and textual understanding to perform autonomous navigation and end-to-end task completion.
Constraint Map Planner
A strategic prompt-flow skill that deconstructs complex project blockages into clear constraint maps with hard limits, soft limits, and actionable tradeoffs.
SipSiip Wine by the Glass
A real-time wine menu and pricing query tool for restaurants and bars integrated with SipSiip smart wine dispensers.
Featured*
