spaced-repetition

spaced-repetition is a skill for Claude Code, Codex from yugash007/edu-agent-skills. It costs 24 tokens per session (821 once invoked), scanned A, original, MIT.

A review scheduler that revisits learned concepts at gradually increasing time intervals. Spaced repetition is a study method that improves long-term recall by delaying reviews until information is nearly forgotten.

In plain words
What is it for?
It is for scheduling review items, adjusting the next interval based on recall quality, and coordinating due items with flashcards and stored learning records.
Why use it?
It helps prevent learned material from fading and brings overdue reviews to the front of a session.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit It is for scheduling review items, adjusting the next interval based on recall quality, and coordinating due items with flashcards and stored learning records.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/yugash007/edu-agent-skills/spaced-repetition
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add yugash007/edu-agent-skills --skill spaced-repetition
Clone the repo
git clone --depth 1 https://github.com/yugash007/edu-agent-skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for spaced-repetition

README.md
[![agentmods](https://agentmods.dev/badge/skills/yugash007/edu-agent-skills/spaced-repetition/github.svg)](https://agentmods.dev/skills/yugash007/edu-agent-skills/spaced-repetition)
Your own site
<a href="https://agentmods.dev/skills/yugash007/edu-agent-skills/spaced-repetition"><img src="https://agentmods.dev/badge/skills/yugash007/edu-agent-skills/spaced-repetition/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for spaced-repetition

Your own site · 80×15
<a href="https://agentmods.dev/skills/yugash007/edu-agent-skills/spaced-repetition"><img src="https://agentmods.dev/badge/skills/yugash007/edu-agent-skills/spaced-repetition.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 24 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 821 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00024 $0.00821
Opus 5 $0.00012 $0.00411
Sonnet 5 $0.00005 $0.00164
Haiku 4.5 $0.00002 $0.00082

Measured 12d ago against content hash 4628c27eb96d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

spaced-repetition scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/productivity/spaced-repetition/SKILL.md · 68 lines

How it starts

The opening of the file, as written. The whole thing — 68 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Purpose

Schedule review of previously-learned concepts at expanding intervals to exploit the spacing effect. Manages due dates, adjusts intervals based on recall quality, and surfaces overdue items before they decay.

Activation

  • Review session is due based on schedule. Learner initiates review. flashcards deck has due items. Sustained learning track (3+ sessions) needing interval maintenance.
  • Skip if: one-shot session with no continuity. Concept not yet learned. Learner declines scheduling.
  • Routing: overdue items take priority at session start. Coordinate with flashcards for card-level scheduling. Feed interval data to learning-memory.

Inputs

  • Flashcard/item schedule with due dates, learner's current session, items from learning-memory.

Interval Algorithm (Simplified SM2)

Each item has an interval (days) and ease factor (EF, 1.3–2.5). Initial: 1 day → 3 days → then formula.

Score Label Interval Rule EF Change
0 Failed Reset to 1 day EF -= 0.2 (min 1.3)
1 Hard Stay at current EF -= 0.1
2 Good Interval × EF No change
3 Easy Interval × EF × 1.3 EF += 0.1 (max 2.5)

Mastery threshold: EF > 2.4, interval > 60 days, 5 consecutive successes → archive.

Workflow

  1. Detect Due Items — Check next_review ≤ today. Sort by overdue duration (most overdue first). Report count.
  2. Scope Session — ≤10 due: review all. >10: prioritize by overdue + weak-area overlap, cap at 15. Report deferrals.
  3. Execute Review — Present front, wait for learner response, reveal back. Self-score: Failed/Hard/Good/Easy. Compute new interval immediately. Never reveal answer before attempt.
  4. Handle Failures — Score 0: reset to 1 day, re-test at end of current session. Failed 3 sessions in a row: flag for misconception-detector.
  5. Update Schedule — Output updated schedule. Show items due in next 7 days. Warn about upcoming review spikes.
  6. Onboard New Items — Fresh concept → add at interval=1 day. Confirm concept is understood first (not still unclear).

Read the full file on GitHub · 68 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 68 lines · 24 tokens per session scan A 4628c27eb96d

Subscribe to this mod's changes

spaced-repetition is a skill published in the GitHub repository yugash007/edu-agent-skills (7 stars, last pushed 3mo ago), licensed MIT. It adds 24 tokens to every session and 821 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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