Practice Problem Sequence Designer Agent Skill

Generate a scaffolded sequence of practice problems with graduated difficulty and strategic variability.

Context cost
5k tokensestimated from the bundle, loaded when it triggers
Bundle
1 file · 20.0 kBtext throughout, nothing executable
Licence
not declarednone named by its author
Last change
—v1.0
Servers it uses
Noneruns standalone

What it does

Generate a scaffolded sequence of practice problems with graduated difficulty and strategic variability. Use when creating worksheets, homework sets, or independent practice materials.

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.

desirable-difficultydocumentationpracticeproblem-designscaffoldingvariability

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.md20.0 kB · preview
--- # AGENT SKILLS STANDARD FIELDS (v2) name: practice-problem-sequence-designer disable-model-invocation: false user-invocable: true effort: medium # EXISTING FIELDS skill_id: "explicit-instruction/practice-problem-sequence-designer" skill_name: "Practice Problem Sequence Designer" domain: "explicit-instruction" version: "1.0" evidence_strength: "strong" evidence_sources: - "Rosenshine (2012) — Principles of Instruction, Principles 5 & 8: guide student practice, provide scaffolds" - "Rohrer (2009) — The effects of spacing and mixing practice problems" - "Sweller et al. (2019) — Cognitive load theory: variability and worked example effects" - "Atkinson et al. (2000) — Learning from examples: varied practice promotes transfer" - "Bjork & Bjork (2011) — Making things hard on yourself, but in a good way: desirable difficulties" input_schema: required: - field: "skill_to_practise" type: "string" - field: "student_level" type: "string" - field: "problem_count" type: "integer" optional: - field: "common_errors" type: "array" - field: "prior_examples" type: "string" - field: "student_profiles" type: "array" - field: "assessment_format" type: "string" output_schema: type: "object" fields: - field: "problem_sequence" type: "array" - field: "scaffold_reduction_plan" type: "string" - field: "differentiation_options" type: "object" - field: "monitoring_guide" type: "string" chains_well_with: - "explicit-instruction-sequence-builder" - "worked-example-fading-designer" - "interleaving-unit-planner" - "cognitive-load-analyser" teacher_time: "4 minutes" tags: ["practice", "problem-design", "scaffolding", "variability", "desirable-difficulty"] ---
70# Practice Problem Sequence Designer
71
72## What This Skill Does
73
74Designs a sequenced set of practice problems that follows principles of distributed difficulty, progressive scaffold reduction, and surface feature variation — moving students from near-transfer (problems very similar to the taught example) through to far-transfer (problems that look different but require the same underlying skill). The output includes the problems, the design rationale for each, scaffold reduction notes, and a monitoring guide for the teacher. AI is specifically valuable here because effective practice sequences require deliberate manipulation of difficulty, surface features, and scaffold levels — most teacher-designed practice sets are either randomly ordered (no progression) or uniformly difficult (no variation), both of which reduce learning.
75
76## Evidence Foundation
77
78Rosenshine (2012) identified guided and independent practice as Principles 5 and 8, emphasising that practice must be scaffolded (beginning with teacher support and gradually reducing it) and that students should achieve a high success rate (80%+) before scaffolds are removed. Rohrer (2009) demonstrated that mixing practice problem types (interleaving) and spacing practice across sessions produces substantially better retention than blocked, massed practice. Sweller et al. (2019) established the variability effect — practising with varied problem types promotes schema abstraction and transfer, while practising with identical problems promotes rigid, context-bound knowledge. Atkinson et al. (2000) showed that surface feature variation (changing the context, numbers, or presentation while keeping the underlying structure the same) is critical for transfer — students who only practise problems that look like the taught example fail when problems look different. Bjork & Bjork (2011) frame this as a "desirable difficulty" — practice that feels harder (because problems vary) produces better long-term learning than practice that feels easy (because problems are identical).
79
80## Input Schema
81
82The teacher must provide:
83- **Skill to practise:** The specific skill. *e.g. "Solving linear equations with the unknown on both sides" / "Writing a paragraph using the PEEL structure" / "Drawing and interpreting box plots"*
84- **Student level:** Year group and current level. *e.g. "Year 9, have just seen two worked examples — novice with this specific skill"*
85- **Problem count:** How many problems. *e.g. 10*
86
87Optional (injected by context engine if available):
88- **Common errors:** Known errors to design problems around
This is a preview of SKILL.md. Download or install the skill to get the whole thing.
In the file
SKILL.md2,883 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.

≈700
always loaded
The name and description, so the model knows the skill exists and when to reach for it.
4,300
on trigger
The instruction body, read only when the skill fires.
2.5%
of a 200k window
Ten skills this size would take about 25% of the window before you open a file.
050k100k150k200k context window

5k 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, 20.0 kB on disk. A bundle is text throughout: the instructions the model reads, plus the templates it fills in.

  • SKILL.md20.0 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.

# Practice Problem Sequence Designer · 5k tokens when loaded · macOS, Linux mkdir -p .claude/skills && t=$(mktemp -d) && curl -fsSL -o "$t/bundle.tar.gz" https://mcprush.com/api/skills/practice-problem-sequence-designer/bundle.tar.gz && tar -xzf "$t/bundle.tar.gz" -C "$t" && [ -d "$t/practice-problem-sequence-designer" ] && { [ ! -e .claude/skills/practice-problem-sequence-designer ] || { mv .claude/skills/practice-problem-sequence-designer "$t/.previous" && echo "Previous copy moved to $t/.previous"; }; } && mv "$t/practice-problem-sequence-designer" .claude/skills/ && echo "Installed .claude/skills/practice-problem-sequence-designer"
On Windows, or any OS with Node 20+
npx mcprush@latest skill add garethmanning/practice-problem-sequence-designer

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/practice-problem-sequence-designer/ 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/practice-problem-sequence-designer/bundle.tar.gz && tar -xzf "$t/bundle.tar.gz" -C "$t" && [ -d "$t/practice-problem-sequence-designer" ] && { [ ! -e ~/.claude/skills/practice-problem-sequence-designer ] || { mv ~/.claude/skills/practice-problem-sequence-designer "$t/.previous" && echo "Previous copy moved to $t/.previous"; }; } && mv "$t/practice-problem-sequence-designer" ~/.claude/skills/ && echo "Installed ~/.claude/skills/practice-problem-sequence-designer" (macOS, Linux) — or add --global to the npx line. The curl line replaces .claude/skills/practice-problem-sequence-designer/ 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/practice-problem-sequence-designer

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.

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