/exam-forecast

name: exam-forecast
description: >
  Analyze past exams from the same professor to surface patterns — subject
  weighting, recurring issue-spot traps, favored hypo types, policy-vs-doctrine
  mix — and forecast likely emphases for the upcoming exam. Use when the user
  says "what's on the exam", "analyze past exams", "predict the exam", or
  shares past exams.
argument-hint: "[class name, with past exams shared or paths to them]"

/exam-forecast

1. Load `~/.claude/plugins/config/claude-for-legal/law-student/CLAUDE.md` → class, professor, exam format, syllabus. 2. Apply the workflow below. 3. Intake past exams (PDF, paste, or paths). Confirm sample size. 4. Analyze each past exam: format, subject coverage, question style, fact-pattern density, recurring traps. 5. Cross-exam pattern analysis — what's stable, what varies. 6. Combine with current syllabus to produce forecast: subject weights, format, hobby horses, study emphasis. 7. Write `~/.claude/plugins/config/claude-for-legal/law-student/exam-forecasts/[class]/forecast-[YYYY-MM-DD].md`. Framed as weighting heuristic, not prediction.

---

Purpose

Every professor's exam has fingerprints. The same hypo structures recur. The same traps come back. The same subject ratios repeat. Students who have prior exams study smarter; students who don't, study harder. This skill analyzes the prior exams you have and surfaces the patterns.

Not magic. A forecast, not a prediction. The skill cannot tell you what's on the exam — it can tell you what's been on past exams and what's likely to recur based on syllabus coverage.

Confidence discipline

• Pattern analysis (what subjects appeared, how many questions per topic, how often policy vs. rule-application) — confident where the exams are clearly in front of me.
• Inference about likely emphasis on upcoming exam — `[UNCERTAIN]` is the default; these are forecasts, not certainties. Explicitly frame as "based on the [N] past exams you shared, [topic] appeared in [M]. Your upcoming exam may emphasize it, or the professor may rotate — use this as a weighting for review time, not a prediction."
• If only 1-2 past exams are available, say so explicitly — any pattern inferred from 1 exam is noise.
• If the professor is new (no past exams available), skill can't forecast. Say so; fall back to syllabus-based "these are the subjects covered" only.

Load context

• `~/.claude/plugins/config/claude-for-legal/law-student/CLAUDE.md` → current classes, exam formats, syllabus if captured
• User-provided past exams (PDF, pasted text, paths)
• Optional: syllabus for the current class (for "what's been covered to date")

**If the uploaded past exams have a professor's name, use it to match patterns** (same-professor exams are the highest-signal input). **If not, match on subject and structure.** Don't ask the user to type in the professor's name — use what's in the materials. If the user volunteers it in conversation that's fine; don't prompt for it.

Workflow

Step 1: Intake

• Which class are we forecasting for?
• How many past exams from this professor are available?
• Are they from the same course, or different courses by the same professor?
• Are any of them the take-home / open-book / different-format variants, vs. the typical format for your upcoming exam?
• Syllabus for your current class?

If fewer than 3 past exams: flag as thin sample. Pattern inference is weaker. If exams are across different courses: some patterns transfer (question style, policy vs. doctrine ratio); subject-specific patterns don't.

Step 2: Read each past exam

For each past exam:

• Format (number of questions, length, time limit, open/closed book)
• Subject coverage (which topics tested, in what proportion)
• Question style (issue-spotter, single-issue deep, policy essay, short-answer MBE-style, mix)
• Fact pattern density (fact-heavy hypos, sparse facts with doctrinal focus, or policy prompts with no facts)
• Recurring traps (e.g., professor always hides the jurisdictional issue in an otherwise-clean fact pattern; professor always asks about the exception rather than the rule)
• Policy vs. doctrine ratio
• Unusual structures (essays + MBE hybrid, moot court scenario, etc.)

Step 3: Cross-exam pattern analysis

Roll up what's consistent across exams:

**Stable patterns (appeared in most/all past exams):**

• Subject weights (e.g., "consideration and modification account for 30% of exam points consistently")
• Question style (e.g., "always one long issue-spotter + two short-answer hypos")
• Professor hobby horses (e.g., "always tests third-party beneficiaries even when it's a minor topic in class")

**Variable patterns (appeared in some but not all):**

• Policy essays (e.g., "appeared in 2 of 4 past exams — usually when the semester covered a policy-heavy topic late")
• Open-book vs. closed-book differences
• Take-home vs. in-class differences

**Absent patterns worth noting:**

• Topics covered in class that have NEVER been tested in past exams — don't skip these, but don't weight them heavily either
• Topics tested in past exams that aren't in your current syllabus — probably not coming back

Step 4: Forecast for the upcoming exam

**Header — required, first line of the forecast, both in-chat and in the saved file.** Per plugin config `## Outputs`, every study output carries the verbatim study-notes header. The forecast is a study output. Do not omit, rephrase, or relocate the header. The header is not a disclaimer the student can ask to drop; it is the output's identity and prevents the forecast from being mistaken for a predicted exam or for legal advice:

STUDY NOTES — NOT LEGAL ADVICE

Combine pattern analysis with current syllabus:

STUDY NOTES — NOT LEGAL ADVICE

# Exam Forecast — [class / professor] — [date]

**Past exams analyzed:** [N]
**Sample confidence:** [thin (<3) / moderate (3-5) / strong (6+)]
**Caveats:** [e.g., "one of the past exams was an open-book final; your up