A precision-engineered tool for converting fragmented university timetables into verified, error-free calendar files.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install course-schedule-export
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 course-schedule-export 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 Course Schedule Export?
The course-schedule-export skill is a specialized utility designed for students and educators who need to transform messy academic schedules into structured calendar formats. Unlike basic converters, this tool prioritizes data integrity and technical correctness by employing a multi-round verification process. It handles complex academic nuances such as odd/even week rules, period-time mappings, and conflicting source materials.
By leveraging the Openclaw Skills framework, this skill ensures that no course data is silently ignored or incorrectly inferred. It bridges the gap between unstructured inputs—like OCR text from screenshots or manual pastes—and standardized .ics files compatible with Apple Calendar, Google Calendar, and Outlook.
Course Schedule Export Use Cases
- Normalizing university timetables from mixed sources like PDFs, Excel sheets, and screenshots.
- Aligning recurring course groups with specific week-1 anchor dates and semester boundaries.
- Resolving complex parity rules such as 9-16 even or 5-11 odd week sequences.
- Merging consecutive class periods into single calendar events based on matching metadata.
- Cross-checking supplemental lab or weekend session notices against a primary schedule.
How Course Schedule Export Works
- Input Gathering: The skill collects authoritative sources, including the timetable, period-time tables, and week-1 anchor dates.
- Manifest Creation: It builds a normalized schedule manifest using a strict schema to capture course names, locations, and recurrence rules.
- Source Preservation: Literal meanings from the source are preserved, expanding ranges and parity rules without unsafe guessing.
- Verification Round 1: A two-way coverage check is performed using internal scripts to ensure every non-empty cell is accounted for.
- Ambiguity Resolution: The agent polls the user in small batches to resolve specific blockers like missing timezones or conflicting week notations.
- Verification Round 2: A final pass ensures that user-provided answers haven't introduced new inconsistencies.
- ICS Generation: The skill executes a Python script to generate a standard-compliant .ics file.
Course Schedule Export Setup
To use this skill within the Openclaw Skills environment, ensure you have the necessary reference schemas and scripts available in your local workspace.
# Navigate to your skills directory
cd skills/course-schedule-export
# Ensure the manifest and coverage scripts are executable
chmod +x scripts/check_manifest_coverage.py
chmod +x scripts/generate_ics.py
# Prepare your source files (PDF, JPG, or TXT) in the input folder
Course Schedule Export Data Schema & Taxonomy
The skill organizes data through a strict taxonomy defined in the following references:
| File Type | Purpose | Key Metadata |
|---|---|---|
manifest-schema.md |
Normalization | Course name, location, recurrence, source provenance |
coverage-schema.md |
Verification | Source entry mapping, manifest course group IDs |
.ics |
Final Export | Summaries, week rules, teacher info, and alerts |
Course Schedule Export Advanced Features
- Multi-source priority handling: Automatically prioritizes machine-readable exports over OCR screenshots.
- Two-way coverage enforcement: Uses
check_manifest_coverage.pyto prevent data loss during normalization. - Deterministic recurrence: Supports both recurring semester-based rules and one-off dated sessions within a single export.
- Standard-library dependency: Core generation scripts rely solely on the Python standard library for maximum portability.
- Conflict visibility: Keeps disagreeing claims from multiple sources visible until manually resolved by the user.
SKILL.md
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