Individual Spacing Algorithm Explainer Agent Skill

Explain and configure individual spacing algorithms using student performance data and forgetting curves.

Context cost
6.1k tokensestimated from the bundle, loaded when it triggers
Bundle
1 file · 24.4 kBtext throughout, nothing executable
Licence
not declarednone named by its author
Last change
—v1.0
Servers it uses
Noneruns standalone

What it does

Explain and configure individual spacing algorithms using student performance data and forgetting curves. Use when personalising retention schedules in adaptive learning platforms.

What this skill changes about the agent has not been set out here as a list. Its SKILL.md, shown below, says it in the author’s own words.

duolingoebbinghausforgetting-curvelindseymemoryretentionspaced-repetitionspacing

The skill itself

A skill is instructions the model reads, so you can see what you are getting: below is the start of its SKILL.md. The front matter loads with every session, the body loads when the skill triggers, and the whole file comes with the install.

SKILL.md24.4 kB · preview
--- # AGENT SKILLS STANDARD FIELDS (v2) name: individual-spacing-algorithm-explainer disable-model-invocation: true user-invocable: true effort: medium # EXISTING FIELDS skill_id: "ai-learning-science/individual-spacing-algorithm-explainer" skill_name: "Individual Spacing Algorithm Explainer" domain: "ai-learning-science" version: "1.0" evidence_strength: "strong" evidence_sources: - "Ebbinghaus (1885/1913) — Memory: A contribution to experimental psychology (forgetting curve)" - "Cepeda et al. (2006) — Distributed practice in verbal recall tasks: A review and quantitative synthesis (meta-analysis)" - "Lindsey et al. (2014) — Improving students' long-term knowledge retention through personalized review" - "Settles & Meeder (2016) — A trainable spaced repetition model for language learning (Duolingo half-life regression)" - "Pashler et al. (2007) — Organizing instruction and study to improve student learning (IES practice guide)" input_schema: required: - field: "content_to_space" type: "string" - field: "performance_data" type: "string" optional: - field: "student_level" type: "string" - field: "subject_area" type: "string" - field: "time_horizon" type: "string" - field: "available_review_slots" type: "string" - field: "system_context" type: "string" output_schema: type: "object" fields: - field: "spacing_schedule" type: "object" - field: "algorithm_explanation" type: "object" - field: "priority_ranking" type: "array" - field: "implementation_guidance" type: "object" chains_well_with: - "adaptive-hint-sequence-designer" - "formative-assessment-loop-designer" - "retrieval-practice-designer" teacher_time: "5 minutes" tags: ["spacing", "spaced-repetition", "forgetting-curve", "Ebbinghaus", "Lindsey", "Duolingo", "retention", "memory", "algorithm"] ---
69# Individual Spacing Algorithm Explainer
70
71## What This Skill Does
72
73Generates a personalised spaced repetition schedule for a specific set of knowledge items based on student performance data, and explains the algorithm logic in teacher-friendly terms. This skill does NOT execute the spacing algorithm — execution requires a system like Anki, Quizlet, SuperMemo, or Kaku's own retention engine. What this skill does is DESIGN and EXPLAIN: given what students know and what they're forgetting, it produces a concrete review schedule with clear rationale for why each interval was chosen. The core insight from spacing research is that the optimal review interval depends on the desired retention period and the item's current memory strength. Ebbinghaus (1885) established that forgetting follows a predictable curve — steep initially, then gradually flattening. Cepeda et al. (2006) demonstrated in a comprehensive meta-analysis that spacing review across time produces substantially better long-term retention than massing the same amount of practice into a single session. The practical challenge is that the optimal interval is different for every student and every item — which is where personalisation becomes essential. AI is specifically valuable here because calculating optimal intervals across dozens of items for individual students is computationally trivial for a machine but practically impossible for a teacher doing it manually.
74
75## Evidence Foundation
76
77Ebbinghaus (1885/1913) conducted the foundational experiments on forgetting, demonstrating that memory for newly learned material decays exponentially but that each subsequent review strengthens the memory trace and slows the rate of forgetting. This "forgetting curve" is the theoretical foundation for all spacing algorithms. Cepeda et al. (2006) conducted a meta-analysis of 254 studies on distributed practice, finding a robust spacing effect across a wide range of materials and age groups. They found that the optimal inter-study interval (ISI) depends on the retention interval (RI) — the time until the knowledge is needed. A rough guideline from their analysis: the optimal ISI is approximately 10-20% of the RI. So if you need knowledge for an exam in 30 days, optimal spacing is roughly every 3-6 days. Lindsey et al. (2014) moved spacing research into real classrooms, testing a personalised spacing algorithm with middle school students learning social studies. Their algorithm adjusted review intervals based on individual student performance, and they found significant improvements in long-term retention compared to massed review schedules chosen by teachers. Critically, the personalised algorithm outperformed a one-size-fits-all spacing schedule, demonstrating the value of individual calibration. Settles & Meeder (2016) developed the "half-life regression" model used in Duolingo, which predicts the probability that a student will recall a specific item at a specific time based on their individual history with that item. The model combines three variables: the number of times the item has been seen, the time since last review, and the student's accuracy on similar items. This represents the state of the art in practical, large-scale spacing algorithms. Pashler et al. (2007) translated spacing research into practical recommendations in an IES practice guide, noting that teachers rarely use spacing despite its robust evidence base — partly because it requires advance planning and partly because it feels counterintuitive (students feel more confident after massed practice, even though spaced practice produces better retention).
78
79## Input Schema
80
81The teacher must provide:
82- **Content to space:** What students need to retain. *e.g. "Year 8 biology: cell organelles and their functions — mitochondria, nucleus, cell membrane, ribosomes, chloroplasts, vacuole, cell wall" / "Key dates and causes of WWI" / "French irregular verb conjugations — être, avoir, aller, faire" / "Times tables 6-12"*
83- **Performance data:** What is known about current retention. *e.g. "End-of-topic quiz last Friday: class average 72%. Most students got mitochondria and nucleus correct but confused ribosomes with rough ER. Three students scored below 50%" / "Informal questioning suggests most students remember causes but not dates" / "Duolingo-style accuracy: être 95%, avoir 88%, aller 71%, faire 62%"*
84
85Optional (injected by context engine if available):
86- **Student level:** Year group and proficiency
87- **Subject area:** The curriculum subject
This is a preview of SKILL.md. Download or install the skill to get the whole thing.
In the file
SKILL.md3,556 words
Files1
Licencenot declared
Why you can read it

Nothing in a skill executes. The client loads the text and the model follows it, so a skill can be audited the way a runbook is — by reading it.

What it costs in context

Skills are not billed by the call. They are paid for in context: every token the instructions occupy is a token your code, your diff and your conversation cannot use. Here is what this one takes and when it takes it.

≈820
always loaded
The name and description, so the model knows the skill exists and when to reach for it.
5,280
on trigger
The instruction body, read only when the skill fires.
3.0%
of a 200k window
Ten skills this size would take about 31% of the window before you open a file.
050k100k150k200k context window

6.1k tokens, estimated from the bundle at four bytes to the token, held for the rest of the session once it triggers. Heavy. Teams tend to install this one per project rather than globally, and load it only when the job comes up.

Servers bill, skills cost

A server charges by the month. A skill charges once per session, in context, and then keeps charging it for as long as the session lives.

Before and after

The same question, put to the same model twice: once as it comes, and once with these instructions loaded.

No worked example has been published for this skill yet.

The procedure it runs

The procedure has not been set out here step by step. It is in the body of its SKILL.md: the start of it is shown above, and the whole file comes with the install.

Prose, not code

These steps are written for a model to follow, not executed by a runtime. It can still be told to skip one, and it will say so when it does.

Servers it uses

None. This skill calls no MCP servers at all.

Everything it needs is in the instructions, so it works in a project with nothing connected — the model reads the file and changes how it works with what it can already reach.

Its SKILL.md does not declare which tools it asks the agent for, so what it touches is whatever the instructions themselves ask for — read them before you install it.

What it asks for
Writes filesnot declared
Network accessnot declared

This SKILL.md carries no allowed-tools line, so neither is declared. A skill grants no permissions of its own — it can only ask for tools your client already has.

What it will not do

Every skill is narrow, and the useful ones say where they stop. These are the jobs this one is the wrong tool for.

What this skill is not for has not been published here. Nothing is implied by that: it is a section the author has not filled in.

What is in the bundle

1 file, 24.4 kB on disk. A bundle is text throughout: the instructions the model reads, plus the templates it fills in.

  • SKILL.md24.4 kB
What is not in it

No dependencies and nothing executable: a skill is text the agent reads, so the bundle is 1 file you can review in full before installing.

Install

Installing copies the bundle into your project. Nothing runs at install time — the files sit on disk until the model reads them.

# Individual Spacing Algorithm Explainer · 6.1k tokens when loaded · macOS, Linux mkdir -p .claude/skills && t=$(mktemp -d) && curl -fsSL -o "$t/bundle.tar.gz" https://mcprush.com/api/skills/individual-spacing-algorithm-explainer/bundle.tar.gz && tar -xzf "$t/bundle.tar.gz" -C "$t" && [ -d "$t/individual-spacing-algorithm-explainer" ] && { [ ! -e .claude/skills/individual-spacing-algorithm-explainer ] || { mv .claude/skills/individual-spacing-algorithm-explainer "$t/.previous" && echo "Previous copy moved to $t/.previous"; }; } && mv "$t/individual-spacing-algorithm-explainer" .claude/skills/ && echo "Installed .claude/skills/individual-spacing-algorithm-explainer"
On Windows, or any OS with Node 20+
npx mcprush@latest skill add garethmanning/individual-spacing-algorithm-explainer

Windows PowerShell says 'running scripts is disabled on this system'? Run Set-ExecutionPolicy -Scope CurrentUser RemoteSigned once, or type npx.cmd instead of npx (codex.cmd, gemini.cmd, grok.cmd likewise). PowerShell 7 needs neither. Writes to .claude/skills/individual-spacing-algorithm-explainer/ in the current project. For every project instead, run mkdir -p ~/.claude/skills && t=$(mktemp -d) && curl -fsSL -o "$t/bundle.tar.gz" https://mcprush.com/api/skills/individual-spacing-algorithm-explainer/bundle.tar.gz && tar -xzf "$t/bundle.tar.gz" -C "$t" && [ -d "$t/individual-spacing-algorithm-explainer" ] && { [ ! -e ~/.claude/skills/individual-spacing-algorithm-explainer ] || { mv ~/.claude/skills/individual-spacing-algorithm-explainer "$t/.previous" && echo "Previous copy moved to $t/.previous"; }; } && mv "$t/individual-spacing-algorithm-explainer" ~/.claude/skills/ && echo "Installed ~/.claude/skills/individual-spacing-algorithm-explainer" (macOS, Linux) — or add --global to the npx line. The curl line replaces .claude/skills/individual-spacing-algorithm-explainer/ only after the download succeeds, so files left there by another skill of the same name, or by an older release, do not mix in. A copy already there is moved aside, not deleted, and the line prints where.

Which clients pick it up on their own

A skill is a folder of text. Most of these read a skills folder and pick it up without being told; the rest take the same folder another way — an upload in the app, a parameter on an API call — and then choose it by its description just the same.

Claude Code.claude/skills/
Claude DesktopCustomize › Skills
ChatGPTSkills › Create › Upload
Cursor.cursor/skills/
VS Code.github/skills/
Codex CLI.agents/skills/
Gemini CLI.gemini/skills/
Grok Build.grok/skills/
Microsoft CopilotSkills › Upload a skill
PerplexityComputer › Skills › Upload a skill
DeepSeek Harness.dsh/skills/
Zed.agents/skills/
Devin Desktop.devin/skills/
Windsurf (legacy).windsurf/skills/
OpenAI Agents SDKInstructions or sandbox Skills
HTTP / APIa request parameter
This release
Version1.0
Publishedno release date on file
PriceFree
Referencegarethmanning/individual-spacing-algorithm-explainer

Versions

v1.0 is what is on the shelf; no release here carries a date. Instructions change more often than APIs do — a skill can be rewritten entirely without anything it depends on moving.

v1.0
  • No earlier releases have been published to the marketplace.
Pinning

The install command always fetches the release that is current the day you run it — v1.0 today — and cannot ask for an earlier one. The copy on your disk does not change until you run it again.

Reviews

—no reviews yet

Nobody has reviewed this skill yet. The rating is the mean of the reviews written here, so there is none until somebody writes the first.

Sign in to review it

A review is tied to an account so it can be answered, edited and taken down by the person who wrote it.

Sign in
Who can post

Anybody with an account, one review each. It carries the version that was current when you wrote it, and the publisher may reply once.

Publisher
Servers0
Claim this skill