A lightweight personal efficiency manager for college students that automatically balances class schedules, study routines, exam prep, and physical fitness without scheduling conflicts.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install student-assistant
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 student-assistant 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 Student Assistant Skill?
The Student Assistant skill is a lightweight, zero-bloat personal efficiency manager designed specifically for university students. Operating under a strict schedule-first rule, it ensures that all generated tasks, exam review plans, and fitness routines seamlessly route around your primary course blocks. This intelligent agent dynamically calculates available free time slots to eliminate scheduling overlap and reduce cognitive load.
By leveraging localized preferences and contextual parameters, it delivers practical, highly executable plans direct to the user. Whether you are searching for an available library study room, splitting heavy exam review topics into bite-sized hourly goals, or setting up a low-fatigue workout, this Openclaw Skills addition guarantees structured and concise breakdowns without unnecessary fluff.
Student Assistant Skill Use Cases
- When a student wants to import, parse, and systematically manage their weekly university course catalog.
- When searching for immediate, nearby quiet classrooms or library spaces to study based on current free periods.
- When a comprehensive, hourly-broken-down exam review roadmap is required for weak academic subjects.
- When setting up automated, low-fatigue exercise routines that adapt to seasonal weather changes.
- When an all-in-one daily schedule summary is needed to visualize classes, study periods, meals, and recovery time.
How Student Assistant Skill Works
- The user triggers the workflow by providing raw text course strings or input commands like course schedules, exam dates, or workout requests.
- The system parses the raw input text, extracts exact days, time blocks, and room locations, and saves it to a persistent schedule schema.
- It automatically calculates
freeSlotsfor every single day of the academic week to create an underlying availability matrix. - Secondary tasks such as exam review blocks and fitness plans are programmatically mapped only into these calculated free windows.
- If external skill hooks (e.g., weather utilities) are active, it factors real-time outdoor elements into the location recommendations.
- It outputs clean, emoji-structured schedules limited to 20 lines for high scannability, resolving any internal multi-booking conflicts using a strict hierarchy: Class > Review > Workout.
Student Assistant Skill Setup
To activate this skill within your Openclaw environment, clone or map the source files into your agent workspace. Ensure that the required data structures are available in your main directory.
Initialize the schema by executing the following command in your terminal:
mkdir -p memory/student && touch memory/student/schedule.json memory/student/exams.json memory/student/review-plan.json memory/student/sport-plan.json memory/student/preferences.json
Once the file architecture is ready, copy and paste your raw university timetable into your active agent interface using the default macro command.
Student Assistant Skill Data Schema & Taxonomy
The Student Assistant skill stores and processes user records locally in clean JSON schemas under the memory/student/ directory:
schedule.json: Contains core course listings (day, start/end times, name, location) and dynamically updatedfreeSlotsarrays.exams.json: Tracks upcoming university test deadlines, courses, and targeted room locations.review-plan.json: Stores granular daily review matrices, tracking parameters like target subjects, exam dates, and hourly task blocks.sport-plan.json: Holds customized weekly fitness items featuring timestamp intervals, target types, intensity levels, and environmental constraints.preferences.json: An optional dictionary detailing user-specific parameters like building choices or baseline fitness thresholds.
Student Assistant Skill Advanced Features
- Conflict Resolution Engine: Automatically overrides overlapping events by adhering to a fixed hierarchy where academic timetables override exam reviews, and exam reviews override workout routines.
- Automated Free Slot Extraction: Parses continuous raw time blocks to extract precise free gaps for spontaneous study sessions.
- Weather Skill Cross-Integration: Leverages contextual weather parameters to dynamically pivot sports recommendations between indoor facilities and outdoor tracks.
- Contextual Reference Mapping: Integrates directly with deep planning algorithms located in the references folder to optimize advanced task-splitting heuristics.
SKILL.md
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