Self-Regulation Scaffold Generator Agent Skill

Generate scaffolds supporting student self-regulation across planning, monitoring, and evaluation phases.

Context cost
5.2k tokensestimated from the bundle, loaded when it triggers
Bundle
1 file · 20.7 kBtext throughout, nothing executable
Licence
not declarednone named by its author
Last change
—v1.0
Servers it uses
Noneruns standalone

What it does

Generate scaffolds supporting student self-regulation across planning, monitoring, and evaluation phases. Use when students struggle to manage their own learning during extended or independent tasks.

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.

documentationexecutive-functionindependencemetacognitionmonitoringscaffoldingself-regulation

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.md20.7 kB · preview
--- # AGENT SKILLS STANDARD FIELDS (v2) name: self-regulation-scaffold-generator disable-model-invocation: false user-invocable: true effort: medium # EXISTING FIELDS skill_id: "self-regulated-learning/self-regulation-scaffold-generator" skill_name: "Self-Regulation Scaffold Generator" domain: "self-regulated-learning" version: "1.0" evidence_strength: "strong" evidence_sources: - "Zimmerman (2000) — Attaining self-regulation: a social cognitive perspective" - "Zimmerman (2002) — Becoming a self-regulated learner: an overview" - "Pintrich (2000) — The role of goal orientation in self-regulated learning" - "Dignath & Büttner (2008) — Components of fostering self-regulated learning among students: a meta-analysis (effect size ~0.69)" - "Panadero (2017) — A review of self-regulated learning: six models and four directions for research" input_schema: required: - field: "task_description" type: "string" - field: "student_level" type: "string" - field: "task_duration" type: "string" optional: - field: "srl_phase_focus" type: "string" - field: "student_profiles" type: "array" - field: "previous_srl_instruction" type: "string" - field: "subject_area" type: "string" output_schema: type: "object" fields: - field: "scaffolds" type: "object" - field: "student_handout" type: "string" - field: "teacher_moves" type: "array" - field: "fading_plan" type: "string" chains_well_with: - "metacognitive-prompt-library" - "goal-setting-protocol-designer" - "agency-scaffold-generator" - "feedback-quality-analyser" teacher_time: "4 minutes" tags: ["self-regulation", "metacognition", "scaffolding", "independence", "executive-function"] ---
70# Self-Regulation Scaffold Generator
71
72## What This Skill Does
73
74Produces phase-appropriate self-regulated learning scaffolds — structured supports for goal-setting, strategy selection, progress monitoring, and reflection — calibrated to a specific task and student age/maturity level. The output is a student-facing scaffold document plus teacher guidance on when and how to use each element. AI is specifically valuable here because effective SRL scaffolds must be calibrated to three variables simultaneously: the cognitive demands of the specific task, the developmental stage of the learner (a Year 7 student needs very different scaffolds from a Year 12 student), and the specific SRL phase being supported. Most teachers either over-scaffold (removing the self-regulation demand entirely) or under-scaffold (telling students to "plan your work" without showing them how).
75
76## Evidence Foundation
77
78Zimmerman (2000, 2002) established the cyclical model of self-regulated learning comprising three phases: forethought (goal-setting, strategic planning, self-efficacy beliefs), performance (self-monitoring, strategy use, attention control), and self-reflection (self-evaluation, causal attribution, adaptation). Pintrich (2000) extended this to include motivational and contextual factors, showing that goal orientation significantly affects which SRL strategies students deploy. Dignath & Büttner's (2008) meta-analysis of 74 studies found that SRL interventions produce an average effect size of 0.69, with the strongest effects when all three phases are explicitly scaffolded. Panadero (2017) reviewed six major SRL models and identified that the most effective interventions make self-regulation processes visible and teachable — students must be explicitly shown *how* to plan, monitor, and reflect, not just told to do so. Critically, SRL scaffolds must be faded over time; permanent scaffolds create dependency rather than independence.
79
80## Input Schema
81
82The teacher must provide:
83- **Task description:** The specific learning task. *e.g. "Write a persuasive essay arguing for or against school uniforms (800 words, due Friday)" / "Complete a group science investigation into factors affecting plant growth over 3 weeks"*
84- **Student level:** Year group and SRL maturity. *e.g. "Year 7, novice self-regulators" / "Year 11, developing — can plan but struggle with monitoring"*
85- **Task duration:** How long students have. *e.g. "3 lessons plus homework" / "6-week project"*
86
87Optional (injected by context engine if available):
88- **SRL phase focus:** Which phase to emphasise (forethought, performance, or reflection)
This is a preview of SKILL.md. Download or install the skill to get the whole thing.
In the file
SKILL.md2,932 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.

≈740
always loaded
The name and description, so the model knows the skill exists and when to reach for it.
4,435
on trigger
The instruction body, read only when the skill fires.
2.6%
of a 200k window
Ten skills this size would take about 26% of the window before you open a file.
050k100k150k200k context window

5.2k 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, 20.7 kB on disk. A bundle is text throughout: the instructions the model reads, plus the templates it fills in.

  • SKILL.md20.7 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.

# Self-Regulation Scaffold Generator · 5.2k tokens when loaded · macOS, Linux mkdir -p .claude/skills && t=$(mktemp -d) && curl -fsSL -o "$t/bundle.tar.gz" https://mcprush.com/api/skills/garethmanning-self-regulation-scaffold-generator/bundle.tar.gz && tar -xzf "$t/bundle.tar.gz" -C "$t" && [ -d "$t/self-regulation-scaffold-generator" ] && { [ ! -e .claude/skills/self-regulation-scaffold-generator ] || { mv .claude/skills/self-regulation-scaffold-generator "$t/.previous" && echo "Previous copy moved to $t/.previous"; }; } && mv "$t/self-regulation-scaffold-generator" .claude/skills/ && echo "Installed .claude/skills/self-regulation-scaffold-generator"
On Windows, or any OS with Node 20+
npx mcprush@latest skill add garethmanning/self-regulation-scaffold-generator

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

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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