Skill detail
syllabus
Finds scholarly readings for a course, but is limited to syllabus-based reading lists.
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SKILL.md
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--- name: syllabus description: "Generates a curated supplementary reading list from any course syllabus using Consensus academic search. Grill-me intake (syllabus input format + course audience + year range) plus a grouping forcing-options checkpoint before any search runs — so the reading list matches the course's level and recency need. Parses the syllabus to extract topics and learning outcomes, searches Consensus for recent peer-reviewed papers per topic, and produces a professionally formatted .docx with clickable Consensus links, plain-language summaries calibrated to audience level, and Bloom-higher-order discussion questions tied to course learning goals. Use when the user uploads a syllabus, course outline, or curriculum document and wants supplementary readings (e.g., 'create a reading list from this syllabus', 'find recent papers for my course') — even casual mentions with a syllabus attached should trigger this skill." license: MIT metadata: source_spec: "megaprompts/10-syllabus-megaprompt.md" build_pattern: "Path B (direct conversion)" research_pack_convention: "Agent Integrity Rules verbatim per PR #657 audit; bundled-JS-DOCX-generator variant" version: 1.0.0 --- # Syllabus — Course Supplementary Reading List > **Portability:** Requires a Consensus MCP connection, Node.js with `docx` package, and file reading capability for the syllabus. Works in Claude Code CLI natively. In Claude.ai with Consensus MCP + Code Execution + file upload, the workflow is supported. For an instructor or student with a course syllabus, produce a professional supplementary reading list as `.docx` containing recent peer-reviewed papers per course section. ## Architectural Pattern: Bundled Script This skill uses a **bundled JavaScript helper script** for DOCX generation rather than inlining the 300+ lines of layout code: - DOCX generation logic is reusable + complex - Better separation of concerns: skill = orchestration + intelligence; script = mechanical document assembly - Token-efficient: skill doesn't re-derive layout each run - Easier to maintain and version The bundled script is at `scripts/generate_reading_list.js`. The skill orchestrates the pipeline + invokes the script with JSON input. ## Agent Integrity Rules (Research-Pack Convention) Locked verbatim per PR #657 audit. - **Only use what Consensus returns.** Every paper title, author, journal, year, URL must come from this session's tool calls. Training-knowledge papers labeled `[Not from Consensus — model knowledge]` and excluded. - **Confirm before moving on.** A search isn't complete until response received and inspected. - **Track three counts.** Queries sent / papers received / papers cited. Surface in audit summary. - **Surface gaps, don't fill them.** Section with one paper + note about limited results > section padded with fabrications. ## Phase 0: Grill-Me Intake (3 forcing questions) ### Q1 (root) — Syllabus input > **Provide the syllabus — pick one:** > > 1. File path (PDF, DOCX, text) — I'll read it > 2. Pasted content — paste below > 3. Image of a printed syllabus — attach the image > > *Why I'm asking:* Each format needs a different reader (PDF / DOCX parser / vision). Picking upfront prevents wasted attempts. Forcing choice. Refuse to start without a syllabus. ### Q2 (depends on Q1) — Course audience > **Course audience — pick one:** > > 1. Undergraduate (intro level) > 2. Undergraduate (advanced / upper division) > 3. Graduate (Masters / early PhD) > 4. Graduate (doctoral / advanced) > 5. Professional / continuing education > 6. Mixed > > *Why I'm asking:* Audience dictates summary jargon level and discussion-question complexity. Undergrad summaries define every term; grad summaries assume technical fluency. Discussion questions for undergrads test analysis; for grads test critique and extension. See [`references/audience_calibration.md`](references/audience_calibration.md) for the canon. ### Q3 (depends on Q1) — Year range > **Year rRead the full source on GitHub (opens external page)