Language Demand Analyser Agent Skill

Analyse the language demands of a classroom task to identify barriers for EAL and multilingual learners.

Context cost
5.6k tokensestimated from the bundle, loaded when it triggers
Bundle
1 file · 22.3 kBtext throughout, nothing executable
Licence
not declarednone named by its author
Last change
—v1.0
Servers it uses
Noneruns standalone

What it does

Analyse the language demands of a classroom task to identify barriers for EAL and multilingual learners. Use when adapting tasks, planning support, or assessing linguistic accessibility.

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.

academic-languagebics-calpdocumentationeallanguage-demandsscaffolding

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.md22.3 kB · preview
--- # AGENT SKILLS STANDARD FIELDS (v2) name: language-demand-analyser disable-model-invocation: false user-invocable: true effort: medium # EXISTING FIELDS skill_id: "eal-language-development/language-demand-analyser" skill_name: "Language Demand Analyser" domain: "eal-language-development" version: "1.0" evidence_strength: "strong" evidence_sources: - "Cummins (1981, 2000) — BICS/CALP framework: Basic Interpersonal Communication Skills vs. Cognitive Academic Language Proficiency" - "Gibbons (2002, 2015) — Scaffolding Language, Scaffolding Learning: teaching English language learners in the mainstream classroom" - "Schleppegrell (2004) — The Language of Schooling: a functional linguistics perspective" - "Zwiers (2014) — Building Academic Language: meeting Common Core standards across disciplines" - "Bailey & Heritage (2008) — Formative Assessment for Literacy: building reading and academic language skills across the curriculum" input_schema: required: - field: "task_description" type: "string" - field: "student_level" type: "string" - field: "subject_area" type: "string" optional: - field: "language_proficiency" type: "string" - field: "student_profiles" type: "array" - field: "task_materials" type: "string" - field: "prior_language_instruction" type: "string" output_schema: type: "object" fields: - field: "language_demand_profile" type: "object" - field: "scaffold_recommendations" type: "object" - field: "priority_actions" type: "array" - field: "teacher_language_notes" type: "string" chains_well_with: - "vocabulary-tiering-tool" - "scaffolded-task-modifier" - "academic-language-sentence-frame-generator" - "cognitive-load-analyser" teacher_time: "3 minutes" tags: ["EAL", "language-demands", "BICS-CALP", "scaffolding", "academic-language"] ---
70# Language Demand Analyser
71
72## What This Skill Does
73
74Identifies the language demands of a classroom task across four dimensions — vocabulary (Tier 1/2/3), grammar (sentence complexity, tense, voice, modality), discourse (text structure, cohesion, paragraph organisation), and genre (purpose, audience, register) — and recommends specific scaffolds for each dimension. The analysis makes visible the language that is ASSUMED by the task but rarely explicitly taught, revealing the hidden linguistic barriers that prevent EAL students from demonstrating their subject knowledge. AI is specifically valuable here because most teachers are experts in their subject content but not in the language features their tasks demand — they know what a good science conclusion looks like but may not be able to articulate the specific grammatical structures, discourse patterns, and vocabulary tiers it requires.
75
76## Evidence Foundation
77
78Cummins (1981, 2000) distinguished between Basic Interpersonal Communication Skills (BICS) — the conversational fluency that EAL students typically develop within 1–2 years — and Cognitive Academic Language Proficiency (CALP) — the academic language required for curriculum learning, which takes 5–7 years to develop. This distinction is critical because students who appear fluent in conversation may still lack the academic language needed to access curriculum tasks. Gibbons (2002, 2015) operationalised this distinction into classroom practice, showing that language demands must be identified and scaffolded explicitly — "immersion" alone is insufficient for academic language development. Schleppegrell (2004) demonstrated that school language is not simply "harder" than everyday language — it is structurally different, using nominalisation, passive voice, complex noun phrases, and abstract vocabulary in ways that everyday conversation does not. Zwiers (2014) provided a practical framework for identifying and teaching academic language across disciplines, emphasising that language demands vary by subject. Bailey & Heritage (2008) showed that language demands are present in all tasks, not just literacy tasks — a mathematics problem has language demands (reading the problem, understanding mathematical vocabulary, explaining reasoning) that are invisible to teachers but present barriers for EAL students.
79
80## Input Schema
81
82The teacher must provide:
83- **Task description:** The specific task. *e.g. "Write a conclusion for a science experiment about friction" / "Read a textbook extract and answer comprehension questions about the causes of WW1" / "Participate in a class debate about whether zoos should be banned"*
84- **Student level:** Year group. *e.g. "Year 8"*
85- **Subject area:** The subject. *e.g. "Science" / "History" / "English" / "Mathematics"*
86
87Optional (injected by context engine if available):
88- **Language proficiency:** EAL proficiency level
This is a preview of SKILL.md. Download or install the skill to get the whole thing.
In the file
SKILL.md3,010 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.

≈760
always loaded
The name and description, so the model knows the skill exists and when to reach for it.
4,815
on trigger
The instruction body, read only when the skill fires.
2.8%
of a 200k window
Ten skills this size would take about 28% of the window before you open a file.
050k100k150k200k context window

5.6k 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, 22.3 kB on disk. A bundle is text throughout: the instructions the model reads, plus the templates it fills in.

  • SKILL.md22.3 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.

# Language Demand Analyser · 5.6k 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-language-demand-analyser/bundle.tar.gz && tar -xzf "$t/bundle.tar.gz" -C "$t" && [ -d "$t/language-demand-analyser" ] && { [ ! -e .claude/skills/language-demand-analyser ] || { mv .claude/skills/language-demand-analyser "$t/.previous" && echo "Previous copy moved to $t/.previous"; }; } && mv "$t/language-demand-analyser" .claude/skills/ && echo "Installed .claude/skills/language-demand-analyser"
On Windows, or any OS with Node 20+
npx mcprush@latest skill add garethmanning/language-demand-analyser

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

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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