catalog-search

name	catalog-search
description	Search for a Technion faculty catalog PDF, discover all degree tracks, extract each into JSON, and validate. Use when asked to find, search for, or batch-extract Technion catalogs.
allowed-tools	Read, Write, Edit, Bash(uv run *), Bash(cd *), Glob, Grep, WebSearch, WebFetch, Agent, TeamCreate, SendMessage

Technion Catalog Search & Batch Extraction

Search the internet for a Technion faculty catalog PDF, discover all degree tracks within it, extract each track into a JSON catalog, and validate the results — all orchestrated automatically.

When to Use

Use this skill when asked to:

• Find and extract a Technion catalog (e.g., "Computer Science 2024-2025")
• Extract all tracks from a faculty catalog
• Batch-process a catalog into multiple JSON files

This skill orchestrates the other two skills:

• catalog-extractor — extracts a single track into JSON
• catalog-validation — validates a JSON catalog against the source PDF

IMPORTANT — Unbiased validation: Validation must run in a separate, fresh conversation (new thread / new Copilot chat) with no history from the extraction phase. This ensures the validator independently checks the JSON against the PDF without being influenced by extraction decisions, assumptions, or shortcuts.

Step 1: Find the Catalog PDF URL

Given a faculty name and academic year (e.g., "Computer Science 2024-2025"), search the web to find the official Technion catalog PDF.

Search Strategy

All searches MUST be conducted in Hebrew and scoped to site:technion.ac.il. English queries return wrong results. Follow this order strictly:

Strategy A: Direct site browsing (try first)

1. Navigate to the faculty's known undergraduate website (see table below).

2. Use web_fetch to load the page and look for links containing "קטלוג" or "תוכנית לימודים" or PDF links.

3. The catalog PDF is usually linked from the main undergraduate page or a "תוכניות לימודים" sub-page.

   Faculty	Undergraduate Site
   Computer Science	https://undergraduate.cs.technion.ac.il/
   Electrical Engineering	https://ece.technion.ac.il/

   Faculty catalog PDFs are typically hosted under wp-content/uploads/ on the faculty's undergraduate site or on the Technion undergraduate portal (ugportal.technion.ac.il).

   Technion Undergraduate Portal (all faculties): https://ugportal.technion.ac.il/ — has a catalog page with links to ALL faculty PDFs for each year. URL pattern: ugportal.technion.ac.il/wp-content/uploads/YYYY/MM/<number>-<hebrew-faculty-name>-תשפ״<letter>.pdf

Strategy B: Hebrew web search (if Strategy A fails)

Search in Hebrew using these query patterns (most specific first):

1. קטלוג <faculty-hebrew> <year> site:technion.ac.il

   • Example: קטלוג מדעי המחשב 2024-2025 site:technion.ac.il

2. הפקולטה ל<faculty-hebrew> תוכנית לימודים <hebrew-year-abbrev> site:technion.ac.il

   • Example: הפקולטה למדעי המחשב תוכנית לימודים תשפה site:technion.ac.il

3. <faculty-hebrew> קטלוג <hebrew-year-abbrev> filetype:pdf site:technion.ac.il

   • Example: מדעי המחשב קטלוג תשפה filetype:pdf site:technion.ac.il

Do NOT use English-language queries — they consistently return incorrect catalogs from other sources.

Faculty name mapping

Faculty (English)	Faculty (Hebrew)	Search term	Faculty code
Computer Science	מדעי המחשב	מדעי המחשב	ComputerScience
Electrical Engineering	הנדסת חשמל ומחשבים	הנדסת חשמל ומחשבים	ElectricalEngineering
Data & Decision Science	מדעי הנתונים וההחלטות	מדעי הנתונים	DataAndDecisionScience
Medicine	רפואה	רפואה	Medicine

Hebrew year mapping

Academic Year	Hebrew Year	Hebrew Abbreviation (for URLs/search)
2023-2024	תשפ"ד	תשפד
2024-2025	תשפ"ה	תשפה
2025-2026	תשפ"ו	תשפו
2026-2027	תשפ"ז	תשפז

Strategy C: Fallback

If Strategies A and B don't find a direct PDF link:

1. Search for the faculty's undergraduate page: <faculty-hebrew> טכניון לימודי הסמכה site:technion.ac.il
2. Browse the page for links to "תוכנית לימודים" or "קטלוג"
3. Follow links until you find the PDF

Verify the URL

Confirm the URL ends in .pdf and is accessible. Use web_fetch to download a small portion and verify it's a valid PDF (starts with %PDF).

Example

For "Computer Science 2024-2025" (מדעי המחשב):

1. Strategy A: Fetch https://undergraduate.cs.technion.ac.il/ and look for PDF links containing "קטלוג" or "תשפה"
2. Strategy B (if needed): Search קטלוג מדעי המחשב 2024-2025 site:technion.ac.il
3. Expected result: https://undergraduate.cs.technion.ac.il/wp-content/uploads/2024/12/23-הפקולטה-למדעי-המחשב-תשפ״ה-.pdf (URL-encoded)

Step 2: Extract PDF and Discover Tracks

Once you have the PDF URL:

1. Extract the raw text:

   uv run --project packages/catalog-extractor extract_pdf.py "<pdf_url>" --output raw_text.txt
   

2. Read the extracted text and identify all degree tracks/programs in the PDF. Look for section headers that indicate different tracks:

Known Tracks

CS Faculty

Track (Hebrew)	Track (English)	File Name Pattern	Faculty
מדמח תלת שנתי	CS 3-year	ComputerScience3years{year}.json	ComputerScience
מדמח ארבע שנתי	CS 4-year	ComputerScience4years{year}.json	ComputerScience
הנדסת תוכנה	Software Engineering	ComputerScienceSoftwareEngineerCourse{year}.json	ComputerScience
מגמת סייבר	Cyber Security	ComputerScienceCyberSecurity{year}.json	ComputerScience
למידה וניתוח מידע	Data Analysis	ComputerScienceDataAnalysis{year}.json	ComputerScience
ביואינפורמטיקה	Bioinformatics	ComputerScienceBioinformatics{year}.json	ComputerScience
הנדסת מחשבים	Computer Engineering	ComputerScienceComputerEngineering{year}.json	ComputerScience

EE Faculty

Track (Hebrew)	Track (English)	File Name Pattern	Faculty
הנדסת חשמל	Electrical Engineering	ElectricalEngineering{year}.json	ElectricalEngineering
הנדסת מחשבים ותוכנה	Computer & Software Eng	ElectricalEngineeringComputerSoftware{year}.json	ElectricalEngineering
הנדסת חשמל ומתמטיקה	EE + Math	ElectricalEngineeringMath{year}.json	ElectricalEngineering

How to Identify Tracks in the PDF

• Look for "סה"כ נ.ז" or "יש לצבור X נקודות" (total credits) markers — each track has its own total

• Look for track names in headers (e.g., "המסלול בהנדסת חשמל", "מדמח תלת שנתי")

• Look for credit totals that distinguish tracks:

  • CS 3-year: ~120 credits
  • CS 4-year: ~155 credits
  • CS Software Engineering: ~159.5 credits
  • EE main: ~157.5 credits
  • EE Computer & Software Eng: ~159.5 credits
  • EE + Math: ~162 credits

• Present the discovered tracks to the user and confirm which ones to extract (or extract all).

Step 3: Extract Each Track (via Teammate Agents)

IMPORTANT: Use TeamCreate to spawn teammate agents for extraction — do NOT use regular background agents. Teammates provide a shared task list, the user can cycle through them with Shift+Down, and they can coordinate via SendMessage.

For each track found in Step 2, spawn a teammate that runs the catalog-extractor skill:

1. Determine the track parameters:

   • name: Hebrew catalog name (e.g., "מדמח תלת שנתי 2024-2025")
   • output: File path following the naming convention: packages/docs/{Faculty}{Track}{Year}.json
   • reference: Use the most recent existing catalog of the same track as a reference (if available in packages/docs/)

2. Spawn extraction teammates — one per track, all in parallel. Each teammate prompt MUST include:

   • A pointer to read .claude/skills/catalog-extractor/SKILL.md for extraction guidelines
   • The PDF URL or raw text path (/tmp/<name>_raw.txt)
   • The reference catalog path
   • The output file path
   • The relevant line range in the raw text for this track's section

   Create an agent team. Spawn an extractor teammate for each track:
   - Extractor-4yr: "Read .claude/skills/catalog-extractor/SKILL.md for guidelines. Extract the 4-year track. Raw text at /tmp/cs_raw.txt lines 418-3044. Reference: packages/docs/ComputerScience4years2024-2025.json. Output: packages/docs/ComputerScience4years2025-2026.json"
   - Extractor-3yr: "Read .claude/skills/catalog-extractor/SKILL.md for guidelines. Extract the 3-year track ..."
   - (one per track)
   

3. Each teammate should start from the reference catalog and update it based on the new PDF, following the catalog-extractor skill guidelines (from the SKILL.md file) to fill in:

   • total_credit
   • Bank credit values
   • credit_overflows (follow patterns for track type)
   • Complex rules (Chains, SpecializationGroups)
   • catalog_replacements and common_replacements

Reference File Selection

When extracting a track, use the most recent existing catalog of the same track type as a reference:

Look for the most recent existing catalog of the same track type in packages/docs/ using glob patterns like {Faculty}{Track}*.json. For example:

• CS 4-year → ComputerScience4years*.json
• EE main → ElectricalEngineering*.json

If no reference exists for a track (first extraction for that faculty), omit --reference and build from scratch using the raw text. This is expected for new faculties.

Step 4: Validate Each Track (Agent Team)

CRITICAL: Context Isolation via Agent Teams

Validation MUST run with no history from the extraction phase to prevent bias. Use agent teams to spawn a validator teammate — each teammate gets a completely fresh context window with zero extraction history.

How to do this:

After all tracks are extracted in Steps 1-3, create an agent team for validation:

1. Spawn a validator teammate for each extracted catalog. Each prompt MUST include a pointer to read .claude/skills/catalog-validation/SKILL.md for validation guidelines:

   Create an agent team. Spawn a validator teammate for each catalog:
   - Validator-3yr: "Read .claude/skills/catalog-validation/SKILL.md for guidelines. Validate packages/docs/ComputerScience3years2025-2026.json against <pdf_url>. Run uv run --project packages/catalog-validation validate_all.py ... --verbose. Fix any ERRORs and re-validate until clean."
   - Validator-4yr: "Read .claude/skills/catalog-validation/SKILL.md for guidelines. Validate packages/docs/ComputerScience4years2025-2026.json against <pdf_url> ..."
   - (one per catalog)
   

2. Each teammate runs independently — they read the JSON and PDF with fresh eyes, no extraction context leaking in. They can fix ERRORs autonomously and re-validate.

3. Wait for all validators to complete, then collect their findings.

4. Cross-check between tracks: After all tracks are validated individually, do a quick sanity check:

   • חובה (mandatory) courses for 3-year should be a subset of 4-year (4-year has more requirements)
   • Common replacements should be consistent across tracks of the same year
   • Credit overflows should follow the standard patterns for each track type

Monitoring Validation

• Press Shift+Down to cycle through validator teammates
• Press Ctrl+T to see the shared task list
• Send direct messages to steer a teammate: Message Validator-3yr: "The שרשרת מדעית warning is a false positive, skip it"

Step 5: Summary Report

After processing all tracks, produce a summary:

## Catalog Extraction Summary

Faculty: Computer Science
Year: 2024-2025
Source PDF: <url>

| Track | Output File | Total Credits | Status | Errors | Warnings |
|---|---|---|---|---|---|
| 3-year | ComputerScience3years2024-2025.json | 120 | Valid | 0 | 2 |
| 4-year | ComputerScience4years2024-2025.json | 160 | Valid | 0 | 1 |
| Software Eng | ComputerScienceSoftwareEngineerCourse2024-2025.json | 159.5 | Valid | 0 | 3 |
| Data Science | ComputerScienceDataScienceAndEngineering2024-2025.json | 145 | 1 Warning | 0 | 1 |

Error Handling

• PDF not found: Report that the catalog could not be found. Suggest the user provide the URL directly.
• Track not recognized: If a track section doesn't match known patterns, ask the user whether to attempt extraction.
• Extraction failures: If a track fails extraction, skip it and continue with others. Report the failure in the summary.
• Validation failures: If errors persist after 2 fix attempts, flag the track for manual review and move on.

Full Example

User: "Extract all Computer Science catalogs for 2024-2025"

Phase 1 — Search & Extract via Teammate Agents (Steps 1-3)

1. Browse https://undergraduate.cs.technion.ac.il/ for PDF links -> find the catalog PDF
2. Extract PDF text -> discover tracks: 3-year, 4-year, Software Engineering, Data Science
3. Create an agent team with one extractor teammate per track (all run in parallel)
4. Each extractor reads its reference catalog + relevant PDF sections, builds updated JSON

Phase 2 — Validate via Agent Team (Step 4, same conversation)

4. Create an agent team with one validator teammate per extracted catalog
5. Each validator runs in a fresh context — reads the JSON and PDF independently, fixes errors, re-validates
6. Wait for all validators to finish, collect findings
7. Cross-check between tracks for consistency
8. Produce summary report