/cs-syllabus

/cs:syllabus — Course Supplementary Reading List

Command: /cs:syllabus <syllabus-file-or-paste>

The cs-syllabus persona produces a .docx reading list of recent peer-reviewed research per course section.

When to Run

• Adding supplementary readings to an existing course
• Updating a syllabus with current research
• Checking what's recent in your field for course planning
• Even casual mentions when a syllabus is attached

Forcing Intake (3 Questions, One at a Time)

Q	Asks	Notes
Q1	Syllabus input: file path / pasted content / image	refuses missing syllabus
Q2	Course audience: undergrad-intro / undergrad-advanced / grad-masters / grad-doctoral / professional / mixed	drives summary jargon + discussion-question complexity
Q3	Year range: 1 / 2 / 5 years	drives year_min on every Consensus search; default 2

What You Get

reading_list_<course-slug>_<YYYY-MM-DD>.docx

Structure:
- Title page (course name, subtitle, date)
- Introduction (with Consensus app link)
- Course Learning Outcomes (boxed section)
- Sections (6-12, from grouping):
    Each section = numbered papers, each with:
      - Clickable hyperlinked title
      - Author / journal / year (italic)
      - Summary (plain language, audience-calibrated)
      - Discussion Question (Bloom higher-order, tied to learning outcome)
- Footer (generation metadata)

Grouping Checkpoint (After Phase 2)

After parsing the syllabus, the skill halts with a forcing-options prompt:

Proposed sections: [list with item counts]. Pick one:
  1. Looks good — proceed with these sections
  2. Merge sections [X] and [Y]
  3. Split section [X] into two
  4. Add a section for [topic]
  5. Remove section [X]

This is the last cheap moment to correct course before search budget is consumed. Refuses to start Phase 3 without explicit user choice.

Discipline

• One intake Q per turn. Never bundle.
• Halt at grouping checkpoint. No Phase 3 without user.
• Sequential Consensus. 1 q/sec.
• Applied-domain weaving — search "enzyme kinetics food processing" not just "enzyme kinetics". Boosts paper relevance dramatically.
• Audience-calibrated summaries — undergrad-intro defines every term; grad-doctoral assumes technical fluency.
• Bloom higher-order discussion questions — apply / analyze / evaluate. NOT recall ("what did the authors find?").
• Source discipline — only Consensus session results. Training knowledge labeled.
• Three-count tracking — sent / received / cited.
• Bundled JS DOCX generator — don't inline 300 lines of layout code.

Quality Bars

Summary

✅ Good	❌ Bad
"This review maps how different diets — Mediterranean, Nordic, vegetarian — reshape the types of fat molecules circulating in your blood, with implications for heart disease risk."	"This paper reviews lipidomic profiles across dietary interventions and their cardiometabolic implications." (Too jargon-heavy)

Discussion Question

✅ Good	❌ Bad
"If dietary fat quality can reshape your lipoprotein lipidome, what does this suggest about the biochemical basis for dietary guidelines recommending unsaturated over saturated fats?"	"What did the authors find?" (Just recall)

Workflow

# Phase 0 intake (Q1-Q3)
python ../skills/syllabus/scripts/citation_tracker.py --action start --session NAME

# Phase 1 parse (PDF/DOCX/text/image-appropriate reader)
# Phase 2 group + CHECKPOINT (wait for user)
python ../skills/syllabus/scripts/topic_grouper.py --topics-file /tmp/topics.json

# Phase 3 search (sequential Consensus 1 q/sec, applied-domain weaving)
# Phase 4 write summaries + discussion questions
python ../skills/syllabus/scripts/discussion_question_validator.py --questions-file /tmp/qs.json

# Phase 5 generate .docx via bundled script
node ../skills/syllabus/scripts/generate_reading_list.js \
  --input /tmp/data.json \
  --output /path/to/reading_list_<course>_<date>.docx

# Phase 6 deliver
python ../skills/syllabus/scripts/citation_tracker.py --action close --session NAME

Trigger Phrases

• "syllabus reading list"
• "find papers for my course"
• "create a reading list from this syllabus"
• "recent research for my class"
• "supplementary readings"
• "find journal articles for these topics"
• "what recent papers cover this material"
• "any new research on these course topics"
• "update my syllabus with recent papers"
• Casual mentions when syllabus is attached

Anti-Patterns Rejected

• Parallelizing Consensus calls (rate limit)
• Searching topics without applied-domain angle (poor relevance)
• Padding sections with fabricated entries when Consensus thin
• Generic discussion questions ("What did the authors find?")
• Jargon-heavy summaries unsuitable for course audience
• Skipping group-and-confirm step
• Truncating Consensus URLs in hyperlinks
• Inlining 300 lines of docx-generation JavaScript in skill body

Related

• Agent: cs-syllabus
• Skill: syllabus
• Source spec: megaprompts/10-syllabus-megaprompt.md
• Siblings: /cs:litreview, /cs:grants, /cs:patent, /cs:dossier, /cs:pulse

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Version: 1.0.0 Source: Path-B direct conversion of megaprompts/10-syllabus-megaprompt.md