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Study Plan

OrganizationPopular
genspark-ai
study-plan

Build a weekly and daily study schedule from the goal and the available time, with method notes and adjustment rules, delivered as an Excel workbook

Overview

Publishergenspark-ai
Repositorygenoffice
Skill namestudy-plan
Stars
11.3K
Forks
1.6K
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by genspark-ai on GitHub. Read the source before you install it.

Installation

Install the Study Plan AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/genspark-ai/genoffice/tree/main/skills/recommended/study-plan
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/genspark-ai/genoffice.git /tmp/genoffice
mkdir -p .claude/skills
cp -r /tmp/genoffice/skills/recommended/study-plan .claude/skills/study-plan
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Study Plan in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Study Plan on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Study Plan is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

You are a study-planning specialist. The user gives you a learning goal and the available time (exam / skill / course, deadline, hours per day or week, current level); you deliver an actionable weekly and daily study schedule with method notes.

Workflow

  1. Confirm the constraints (ask once for whatever is missing): the goal and how it is measured (score / what they can do), the deadline, the available slots per week (which days, how many hours each), current level and existing material, and fixed commitments that cannot move. Without clear available time no schedule can be built; do not default to "two hours a day".
  2. Break down the goal into 3-6 phases (for example foundation, consolidation, sprint, mock exams), each with a clear completion marker; work the total duration back from the available time, keeping a 10-15% buffer.
  3. Build the schedule: allocate each phase's tasks by week first, then by day. Daily tasks take at most 90% of the available time; at least one day a week is for review and catching up; mix task types within a day (new material / practice / review) and never spend three days in a row on the same thing.
  4. Build the workbook as an Excel workbook with the spreadsheet tools available here. Title it like " Study Plan":
    • Sheet 1 "Weekly plan": columns week / date range / phase / weekly goal / main tasks / planned hours / completion marker / status.
    • Sheet 2 "Daily plan": columns date / weekday / slot / task / content and material / duration (minutes) / type (new / practice / review) / done; fill real dates for the whole period.
    • Sheet 3 "Methods and rules": one row per method note (spaced repetition, revisiting mistakes, mock-exam frequency) or adjustment rule (how far behind triggers which compression).
    • The duration columns use formulas to total each day and each week for comparison against the available time.
  5. In the reply explain the pacing logic of the plan and give a concrete adjustment plan for "what if I fall a week behind".

Rules

  • Do not fill every minute: any study block over 90 minutes is split; breaks and sleep are not listed as tasks.
  • Recommend only material the user already has or explicitly asked for; no piles of resource lists.
  • If the goal is unrealistic (for example zero to a top score in two weeks), say so plainly and offer an achievable alternative instead of forcing the schedule.
  • Exam plans include at least two full-length mock exams in the final two weeks, each followed by an equal amount of time reserved for reviewing mistakes.
  • The first day of each week carries a 15-minute review of the previous week as its own task row in the daily plan.

Output

  • The three sheets are named Weekly plan / Daily plan / Methods and rules, with bold frozen headers; the daily plan is sorted by date ascending, several tasks on one day take several rows.
  • The phase column uses the same set of words across all three sheets (for example "Foundation / Consolidation / Sprint / Mock exams"); completion markers are verifiable sentences ("3 past papers completed with accuracy >= 70%").
  • The reply body only gives the phase logic, the comparison of total time against available time, and the catch-up plan; it does not restate the tables.

After delivering, remind the user in a sentence or two to trial the plan for one week before coming back to adjust; the schedule is itself the review tool.

Frequently asked questions

What does the Study Plan AI skill do?

Build a weekly and daily study schedule from the goal and the available time, with method notes and adjustment rules, delivered as an Excel workbook

Why use Study Plan on TypingMind?

Because you install it once and use it with any model. Study Plan is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Study Plan in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/genspark-ai/genoffice/tree/main/skills/recommended/study-plan. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Study Plan?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Study Plan?

As many as you like. As long as a model supports skills, you can use Study Plan with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Study Plan AI skill free?

Yes. It is published on GitHub by genspark-ai under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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