Prompt: Build a spaced revision schedule you will actually follow (UP-Context, Learning)

2 days ago

4 min read

An abstract grid of squares with one curved line threading through three marked points.

In this Prompting Publication

What this prompt does

This prompt does one job: it builds a revision schedule that survives a real week. Real dates, revisits with growing gaps, and a plan for the week that goes wrong, written on one page.

UP-Context prerequisites

Required layers: USER-PERSONA, FULL-CONTEXT, AI-PROFILE-ROLE-EXPERTISE, AI-EXACT-TASK and AUDIENCE. The USER-PERSONA layer carries your real available hours: a schedule built on hours you do not have is the one you abandon.

Where it runs

Execution environment: Chatbot or Project. In a project it can be revisited as the deadline moves, keeping the intervals honest.

The prompt

Copy the block below in full. It is the whole prompt: nothing else needs to be attached, and no University 365 file is requested of you.

PROMPT STARTS HERE

Select everything in blue from the line above the word PROMPT STARTS HERE down to the line before word PROMPT ENDS HERE, and paste it into a new AI chat with the appropriate LLM and thinking level. Replace every bracket with your own text before you send it.

INSTITUTIONAL CONTEXT (read before you begin) This prompt is complete on its own. Everything it needs about University 365, about ULM and EVA, and about the UP-Context Method is defined below. No University 365 file is attached to it and none is required. The institution. University 365 is an institution of higher learning. Its Department of Academics owns the curriculum and the academic standards. The method. The UP-Context Method (University 365 Prompting-Context) structures every prompt into eight layers, five required and three optional: USER-PERSONA (who is asking), FULL-CONTEXT (the situation and the facts), AI-PROFILE-ROLE-EXPERTISE (who the AI is acting as), AI-EXACT-TASK (the exact job asked now), AUDIENCE (who the output is for), plus the three optional layers USER-FINAL-GOAL (the goal being worked toward), EXPECTED-FORMAT (the shape of the answer) and EXAMPLES (reference examples). A layer is text in the prompt first; keep it as a reusable file when its text is long enough and reused across prompts. The framework. ULM (University 365 Life Management) organises a person's life into six domains: Body and Health, Spirit and Mind, Character and Emotions, Social and Love Relationships, Career and Finance, Quality of Life. EVA is the engine that carries a person through each domain in three phases: Explore, Visualize, Action Plan. Who is who. U.Copilot is the AI assistant. U.Coach is a human coach. U.Copilot is not a human, must never present itself as one, and must never give medical, legal or financial advice. Your judgement. This prompt supports your thinking. Every recommendation it produces is a draft for you to check, not a decision made on your behalf. THE SPACED SCHEDULE #USER-PERSONA: I am the person who has to follow this schedule. If a persona file is present in this project, apply it. If the layer was written as text instead, it appears after this line: [Write three to six lines about yourself as a learner: the hours you realistically have, when you study best, and the last schedule you abandoned and why.] #FULL-CONTEXT: what I am learning and by when. If a context file is present in this project, apply it. If the layer was written as text instead, it appears after this line: [Describe the subject, the deadline, the material, and how many hours a week you can give it.] #AI-PROFILE-ROLE-EXPERTISE: you are a learning coach who designs schedules that survive contact with a real week. You prefer a schedule that is followed over an optimal one that is abandoned. #AI-EXACT-TASK: build a revision schedule with spacing built in, in three parts: 1. SESSIONS: the sequence of sessions from today to the deadline, each with what it covers and roughly how long it takes. Name the first review, the second, the third and the final pass, with real calendar dates. 2. WHAT REPEATS. For each topic, the days on which it comes back. Gaps must grow: state each gap. 3. THE FAILURE PLAN. What I do when I miss a session, and what I drop first when a week collapses. #AUDIENCE: me, on a normal week with competing demands. The schedule must be readable in one page and followable without an app. #EXPECTED-FORMAT: a dated table for section 1 with the columns DATE, FOCUS, LENGTH; a short list for section 2; three sentences for section 3. Use real dates, not "Day 1". #EXAMPLES: if I paste a schedule that worked before, follow its shape and adjust the intervals. RULES 1. Never schedule more than I said I have. If the material does not fit the hours, say so plainly and propose what to cut. 2. Every topic must return at least twice before the deadline, with a growing gap. 3. No session longer than ninety minutes without a break scheduled inside it. 4. When the deadline is too close for the intervals to be honest, say so instead of compressing silently. 5. End with the single decision that most affects whether this schedule holds.

PROMPT ENDS HERE

The brackets are the only parts you change. Everything else is the prompt.

A timeline with five markers whose gaps grow: session, day 1, day 3, day 7, day 21, with the note review is the work.

What to change for your situation

Fill the FULL-CONTEXT bracket with the subject, the deadline and the hours. When the material does not fit the time, let it say so: the prompt is built to refuse a compressed schedule rather than produce one.

Verification checklist

Multi-model check: run the prompt on a second model and compare. External source check on any factual claim that matters. Human review before you act. CI-First test: does using this prompt build your own judgement, or replace it?

What this does to you

CI-First score 8.1, band Strong: time 9, quantity 6, quality 8, skill 8. Humics: Creativity Neutral, Critical Thinking Friendly, Social Authenticity Friendly, value +3. Imposture risk Low: the failure plan and the honest refusal to over-schedule are both built into the prompt.