Turn a syllabus into a recommended reading list

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What you get

A ready-to-distribute reading list: 15–25 recent peer-reviewed papers grouped under your course’s own topic sections, each with a clickable link, a plain-language summary written for students, and a discussion question tied to a stated learning outcome. Plus an audit log showing exactly which searches produced it. Consensus ships this as a packaged skill. The workflow below is what it does, so you can run it as-is, adapt it, or build it into your own tooling.

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Who it’s for

Faculty refreshing a course, curriculum designers, and corporate training teams who need current research rather than last year’s list.

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Before anything else: check the tool is attached

The workflow is gated on Consensus actually being callable — not installed, not authorized elsewhere, but present in this conversation. Verify before parsing the syllabus, and if it is missing, stop and ask the user to attach it with the + button or by tagging @Consensus. Do not fall back to web search or model knowledge for paper discovery; the whole point is verifiable citations.

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Phase 1 — Parse the syllabus

Extract two things from the uploaded file (PDF, DOCX, image, or pasted text):

1. Course topics — the ordered list of units. These become the reading list’s sections.
2. Learning outcomes — the course-level goals. These drive the discussion questions.

If the syllabus states no explicit outcomes, infer 3–5 from the course description and topic list. Group closely related topics — “Protein Structure” and “Protein Function” become one section. Aim for 6–12 sections: enough granularity to be useful, not so many that the document fragments. Present the grouping and confirm it before searching.

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Phase 2 — Search per section

Write the full query plan first and record its total count. The phase is complete only when every planned query has produced an actual response and appears in the audit log. A zero-result response counts as complete; an intended call does not. Query design is where this workflow succeeds or fails:

• Include the core topic plus an applied angle. For a biochemistry course with a nutrition focus, don’t search enzyme kinetics — search enzyme kinetics food processing applications.
• If the course has an obvious applied domain, weave it into every query. That is what surfaces papers bridging theory and application, which make far better supplementary reading than narrow primary research.
• Keep queries to 4–8 words. Longer queries dilute relevance.

Set year_min to the current year minus one by default. Run searches sequentially — send, wait, confirm, then send the next. See rate limits for the per-tier ceiling. Selection criteria, in priority order:

1. Relevance to the course topic
2. Reviews and meta-analyses over narrow primary research — they give students a broader entry point
3. Higher citation counts
4. Clear connection to the course’s applied domain

Select 1–3 papers per section, targeting 15–25 total.

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Phase 3 — Write summaries and questions

Base every summary only on what the search returned — title, abstract, metadata. If a result lacks enough context for a meaningful summary, say so rather than inventing detail. One-sentence summary, written for undergraduates. Define technical terms in parentheses; the summary should make a student want to read the paper.

Good: “This review maps how different diets — Mediterranean, Nordic, and vegetarian — reshape the types of fat molecules circulating in your blood, with implications for heart disease risk.” Bad: “This paper reviews lipidomic profiles across dietary interventions and their cardiometabolic implications.” — too jargon-heavy for the audience.

Discussion question tying the paper to a learning outcome, pushing past recall into apply, analyze, or evaluate.

Good: “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?” Bad: “What did the authors find?” — pure recall.

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Phase 4 — Build the document

An editable Word document, not a PDF, so the instructor can cut sections into their own materials:

• Title block: course title, generation date, publication-year range
• A short introduction stating the readings came from Consensus results in this session
• A Course Learning Outcomes section
• Numbered papers under each confirmed topic heading
• Per paper: clickable title linked to its full Consensus URL, authors, journal, year, plain-language summary, discussion question
• A Search Audit Log

Render the finished document to page images and inspect every page for overflow, clipping, broken links, and orphaned headings before delivering.

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Audit requirements

Follow the grounding rules. For this workflow specifically, the audit log carries one row per section: section, query, filters as sent, papers found, papers returned, papers selected, status. Then the totals — queries sent, papers returned, papers cited — plus any detected plan cap and any failure. Report the same numbers in your closing message, not just in the document:

Search summary: Ran 12 queries across 10 sections. Consensus returned 34 papers. Selected 18 for the list. No failures. Sections with limited results: “Nitrogen Metabolism” returned only 1 relevant paper — worth supplementing manually.

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What to check before you trust it

• Check for padding. A section with three recommendations where the field published little is the failure mode. Sparse sections should be flagged, not filled.
• Read the summaries as a student would. If they read like abstracts, the audience instruction was ignored.
• Verify the level. Recent frontier papers are often unsuitable for an introductory course regardless of relevance.
• Confirm access before assigning anything students must read. Add open_access=true when students lack broad institutional access.
• Non-English courses: search in English since Consensus indexes English-language papers, and note the course language in the document.

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