>_ ankicli

Planning

Learning plans

Use this page when the real goal is not just card creation but learning optimization: reach a deadline, prepare for a show, a trip, or an exam, and use what you already know to focus on the highest-value material.

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When to use this

  • You have a real-world goal like travel, anime immersion, or an exam and want the agent to optimize study around it.
  • You want ankicli to support a time-bounded plan rather than just a one-off card generation task.

What the agent should know

  • These plans should take current deck coverage, obvious weak areas, and a fixed time budget into account before adding new material.
  • The best plans are adaptive: inspect what the learner already knows, prioritize high-payoff gaps, and avoid flooding the deck with low-value content.

Plan 1: Prepare for Japan in 90 days

This is a deadline-driven travel workflow. The agent should optimize for practical spoken usefulness, not abstract coverage of the whole language.

A good plan prioritizes survival phrases, restaurants, transit, hotels, emergencies, and politeness, then adapts new cards to what the learner already knows.

  • Think in weeks, not just cards: transport week, food week, hotel week, emergency week.
  • Prefer high-utility phrases over encyclopedic coverage.

Prompt for Claude, Codex, or OpenClaw

I am traveling to Japan in 3 months.
I have 1 hour a day.
Use my existing decks and what I already seem to know to build the most useful study plan possible.
Prioritize speaking and travel survival language.
Add missing cards only when they are high value.

ankicli planning baseline

ankicli --json profile list
ankicli --json --profile "User 1" collection info
ankicli --json --profile "User 1" search preview --kind notes --query 'deck:Japanese' --limit 25
ankicli --json --profile "User 1" study start --deck Japanese --limit 20

Plan 2: Study toward a specific anime

This workflow is for immersion around a specific show. The agent should bias toward vocabulary, phrases, and patterns likely to be common in that show, then compare that against existing deck coverage.

The interesting part is source-aware prioritization: teach the learner the words most likely to unlock comprehension for that actual media target.

  • A good loop is pre-watch prep, post-watch reinforcement, then selective new-card creation.
  • Only high-value missing items should become permanent cards.

Prompt for Claude, Codex, or OpenClaw

I want to watch this anime with less subtitle dependence.
Figure out what vocabulary and patterns are common in it.
Compare that against what I already know.
Make me a study plan and update my deck with only the highest-value missing items.
I can study 45 minutes a day.

ankicli planning baseline

ankicli --json --profile "User 1" search preview --kind notes --query 'deck:Japanese tag:anime' --limit 25
ankicli --json --profile "User 1" note add-tags --id 123 --tag anime-focus --dry-run
ankicli --json --profile "User 1" study start --deck Japanese --limit 15

Plan 3: Build a medical exam ramp plan

Medical students are a strong fit for goal-driven ankicli workflows because the target is usually concrete: a practical, block exam, shelf, or anatomy checkoff with a deadline.

The agent should focus on likely testable structures, common confusions, image-heavy recall, and weak areas already visible in the learner’s existing deck.

  • Best fit: anatomy, pathology, pharm, and any exam with a bounded content map and obvious high-yield material.
  • Image-heavy additions are especially useful for anatomy and practical-style exams.

Prompt for Claude, Codex, or OpenClaw

I have an anatomy practical in 6 weeks.
Use my existing deck to identify weak areas.
Prioritize image-based structures and commonly confused regions.
Build a daily 90-minute study plan.
Add or revise only the cards that will give the highest exam payoff.

ankicli planning baseline

ankicli --json --profile "User 1" search preview --kind notes --query 'deck:Anatomy' --limit 25
ankicli --json --profile "User 1" search preview --kind cards --query 'deck:Anatomy tag:weak' --limit 25
ankicli --json --profile "User 1" note update --id 456 --field Back="<img src=\"brachial-plexus.png\">\nBrachial plexus branches"

Plan 4: Use my hour a day intelligently

This is the adaptive daily-coach version of the product. The agent should allocate limited time across review, new material, and weak-area reinforcement based on a real time budget.

This is more valuable than static card generation because it turns ankicli into a study optimizer instead of just a card editor.

  • This is the best fit when the learner has limited time and needs prioritization more than raw content generation.
  • The output should feel like a daily plan, not just a pile of new cards.

Prompt for Claude, Codex, or OpenClaw

I have 1 hour a day to study.
Decide what I should work on each day based on what I already know, what I keep missing, my deadline, and the likely payoff of new cards versus review.
Do not waste time on low-value repetition.

ankicli planning baseline

ankicli --json --profile "User 1" study start --deck Default --limit 20
ankicli --json study summary
ankicli --json --profile "User 1" search preview --kind cards --query 'tag:weak' --limit 25

Plan 5: Optimize around what I already know

This is the deck-optimization version of planning. The agent inspects existing deck coverage, identifies weak areas and redundancy, then decides what to add, what to keep emphasizing, and what not to waste time on.

It is especially useful when the learner already has a large deck and the problem is prioritization, not blank-slate content creation.

  • This is ideal for advanced learners who already have a lot of material but want better prioritization.
  • The key is gap analysis plus daily-plan design, not mass new-card creation.

Prompt for Claude, Codex, or OpenClaw

Look at my current Japanese decks.
Figure out what I already know well, what I keep missing, and what high-value gaps still exist.
Reorganize my next 30 days of study for maximum progress.
Suspend or deprioritize low-value repetition and add only the most useful missing material.

ankicli planning baseline

ankicli --json --profile "User 1" collection info
ankicli --json --profile "User 1" search preview --kind notes --query 'deck:Japanese' --limit 50
ankicli --json --profile "User 1" note add-tags --id 789 --tag high-priority --dry-run

General pattern for learning plans

A good learning plan starts with a real goal, a deadline, and a time budget. The agent then uses ankicli to inspect current deck state, identify useful gaps, and support a plan that changes over time.

This is the layer where ankicli becomes more than a card tool. It becomes the safe stateful study backend for a goal-aware learning system.

  • Start with what the learner already knows, not just what they want to know.
  • Optimize for payoff under the actual time budget.

Operator baseline before any plan

ankicli --version
ankicli --json doctor env
ankicli --json doctor backend
ankicli --json profile list
ankicli --json --profile "User 1" collection info