Outdoor Learning Sequence Designer Agent Skill

Design a structured outdoor learning sequence embedding curriculum objectives in an available outdoor space.

Context cost
5.9k tokensestimated from the bundle, loaded when it triggers
Bundle
1 file · 23.5 kBtext throughout, nothing executable
Licence
Apache-2.0the author’s own terms
Last change
—v1.0
Servers it uses
Noneruns standalone

What it does

Design a structured outdoor learning sequence embedding curriculum objectives in an available outdoor space. Use when planning lessons in school grounds, parks, or local natural environments.

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.

documentationeefexperientialfieldworknatureoutdoor-learningoutside-classroomrickinson

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.md23.5 kB · preview
--- # AGENT SKILLS STANDARD FIELDS (v2) name: outdoor-learning-sequence-designer disable-model-invocation: false user-invocable: true effort: medium # EXISTING FIELDS skill_id: "environmental-experiential-learning/outdoor-learning-sequence-designer" skill_name: "Outdoor Learning Sequence Designer" domain: "environmental-experiential-learning" version: "1.0" evidence_strength: "moderate" evidence_sources: - "Education Endowment Foundation (2019) — Outdoor Adventure Learning systematic review" - "Rickinson, Dillon, Teamey, Morris, Choi, Sanders & Benefield (2004) — A Review of Research on Outdoor Learning" - "Waite (2011) — Children learning outside the classroom: from birth to eleven" - "Beames, Higgins & Nicol (2012) — Learning Outside the Classroom: theory and guidelines for practice" - "Mannion, Mattu & Wilson (2015) — Teaching, learning and play in the outdoors" input_schema: required: - field: "learning_objective" type: "string" - field: "outdoor_space" type: "string" optional: - field: "student_level" type: "string" - field: "subject_area" type: "string" - field: "class_size" type: "string" - field: "time_available" type: "string" - field: "weather_constraints" type: "string" - field: "risk_factors" type: "string" output_schema: type: "object" fields: - field: "outdoor_sequence" type: "object" - field: "learning_design" type: "object" - field: "safety_framework" type: "object" - field: "indoor_outdoor_continuity" type: "object" chains_well_with: - "ecological-inquiry-anchor-designer" - "place-based-inquiry-anchor" - "biophilic-learning-environment-designer" - "awe-wonder-experience-designer" teacher_time: "4 minutes" tags: ["outdoor-learning", "EEF", "Rickinson", "outside-classroom", "fieldwork", "nature", "experiential"] ---
73# Outdoor Learning Sequence Designer
74
75## What This Skill Does
76
77Designs a structured outdoor learning sequence where the outdoor element serves a specific curriculum learning objective — not as a reward, a change of scene, or a general wellbeing activity, but as a learning experience that exploits what the outdoor environment uniquely offers. The critical principle from Rickinson et al.'s (2004) review is that outdoor learning is most effective when it has clear learning intentions, is connected to indoor learning (preparation before, follow-up after), and involves students in active inquiry using the outdoor environment as a primary resource. The output includes the complete sequence (indoor preparation, outdoor activity, indoor follow-up), a learning design explaining why the outdoor element serves the objective better than an indoor alternative, a safety framework, and indoor-outdoor continuity planning. AI is specifically valuable here because designing effective outdoor learning requires simultaneously considering curriculum alignment (what are students learning?), environmental opportunities (what does this specific space offer?), practical logistics (safety, weather, timing), and pedagogical design (how to structure the activity for maximum learning) — a multi-dimensional planning challenge.
78
79## Evidence Foundation
80
81The Education Endowment Foundation (2019) conducted a systematic review of outdoor adventure learning, finding moderate but consistent positive effects on academic outcomes (particularly for disadvantaged pupils) and stronger effects on non-cognitive outcomes including self-confidence, self-efficacy, motivation, and teamwork. Critically, the EEF found that structured outdoor learning with clear learning objectives produced better outcomes than unstructured outdoor time. Rickinson et al. (2004) produced the most comprehensive review of outdoor learning research, identifying three key contexts: fieldwork and outdoor visits (linked to school subjects), outdoor adventure education (residential, team-building), and school grounds and community projects. They found that well-designed fieldwork improved long-term memory of subject content, developed practical inquiry skills, and increased engagement — but that poorly designed outdoor activities (unclear purpose, weak connection to curriculum) produced little learning benefit beyond enjoyment. Waite (2011) focused on younger children, showing that outdoor environments naturally support active, sensory, exploratory learning that is constrained by indoor classrooms. Beames, Higgins & Nicol (2012) proposed a "pedagogy of place" for outdoor learning, arguing that the physical environment should be the starting point for planning — not the curriculum content mapped onto an outdoor location, but the learning opportunities the location itself offers. Mannion, Mattu & Wilson (2015) documented effective outdoor learning in Scottish schools, emphasising that the best outdoor learning sequences include three phases: anticipation (preparation), encounter (the outdoor experience), and recollection (reflection and follow-up).
82
83## Input Schema
84
85The teacher must provide:
86- **Learning objective:** What students will learn. *e.g. "Measuring angles and distances — Year 7 Mathematics" / "Understanding habitats and adaptation — Year 4 Science" / "Descriptive writing using sensory detail — Year 6 English" / "Map skills and compass use — Year 8 Geography"*
87- **Outdoor space:** What's available. *e.g. "School playing field — flat grass area, some trees around the perimeter, a pond in the conservation area" / "Local woodland — 15-minute walk from school, paths, stream, varied terrain" / "School playground — tarmac, benches, some planters, view of the local area"*
88
89Optional (injected by context engine if available):
90- **Student level:** Year group
91- **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.md3,381 words
Files1
LicenceApache-2.0
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.

≈790
always loaded
The name and description, so the model knows the skill exists and when to reach for it.
5,085
on trigger
The instruction body, read only when the skill fires.
2.9%
of a 200k window
Ten skills this size would take about 29% of the window before you open a file.
050k100k150k200k context window

5.9k 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, 23.5 kB on disk. A bundle is text throughout: the instructions the model reads, plus the templates it fills in.

  • SKILL.md23.5 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. The Apache-2.0 licence covers the templates and examples as well as the instructions.

Install

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

# Outdoor Learning Sequence Designer · 5.9k tokens when loaded · macOS, Linux mkdir -p .claude/skills && t=$(mktemp -d) && curl -fsSL -o "$t/bundle.tar.gz" https://mcprush.com/api/skills/outdoor-learning-sequence-designer/bundle.tar.gz && tar -xzf "$t/bundle.tar.gz" -C "$t" && [ -d "$t/outdoor-learning-sequence-designer" ] && { [ ! -e .claude/skills/outdoor-learning-sequence-designer ] || { mv .claude/skills/outdoor-learning-sequence-designer "$t/.previous" && echo "Previous copy moved to $t/.previous"; }; } && mv "$t/outdoor-learning-sequence-designer" .claude/skills/ && echo "Installed .claude/skills/outdoor-learning-sequence-designer"
On Windows, or any OS with Node 20+
npx mcprush@latest skill add hashgraph-online/outdoor-learning-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/outdoor-learning-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/outdoor-learning-sequence-designer/bundle.tar.gz && tar -xzf "$t/bundle.tar.gz" -C "$t" && [ -d "$t/outdoor-learning-sequence-designer" ] && { [ ! -e ~/.claude/skills/outdoor-learning-sequence-designer ] || { mv ~/.claude/skills/outdoor-learning-sequence-designer "$t/.previous" && echo "Previous copy moved to $t/.previous"; }; } && mv "$t/outdoor-learning-sequence-designer" ~/.claude/skills/ && echo "Installed ~/.claude/skills/outdoor-learning-sequence-designer" (macOS, Linux) — or add --global to the npx line. The curl line replaces .claude/skills/outdoor-learning-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
Referencehashgraph-online/outdoor-learning-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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