competency-unpacker

これはレビュー時に保存された抜粋です。完全で最新の内容は外部ソースを確認してください。

---
# AGENT SKILLS STANDARD FIELDS (v2)
name: competency-unpacker
description: "Unpack a broad standard or competency descriptor into specific, assessable success criteria and sub-skills. Use when interpreting curriculum standards or writing learning objectives."
disable-model-invocation: false
user-invocable: true
effort: medium

# EXISTING FIELDS

skill_id: "curriculum-assessment/competency-unpacker"
skill_name: "Competency Unpacker"
domain: "curriculum-assessment"
version: "1.0"
evidence_strength: "strong"
evidence_sources:
  - "Wiggins & McTighe (1998, 2005) — Understanding by Design: backward design from desired results"
  - "Marzano & Kendall (2007) — The New Taxonomy of Educational Objectives"
  - "Heritage (2008) — Learning progressions: supporting instruction and formative assessment"
  - "Popham (2007) — The lowdown on learning progressions"
  - "Hattie (2009) — Visible Learning: success criteria and learning intentions"
input_schema:
  required:
    - field: "competency_descriptor"
      type: "string"
      description: "The standard, learning objective, or competency descriptor to unpack"
    - field: "student_level"
      type: "string"
      description: "Age/year group"
  optional:
    - field: "subject_area"
      type: "string"
      description: "The curriculum subject"
    - field: "curriculum_framework"
      type: "string"
      description: "From context engine: the specific curriculum or standards framework"
    - field: "student_profiles"
      type: "array"
      description: "From context engine: prior attainment data, common gaps"
    - field: "assessment_purpose"
      type: "string"
      description: "Why the competency is being unpacked — for planning, for assessment design, for reporting"
output_schema:
  type: "object"
  fields:
    - field: "observable_indicators"
      type: "array"
      description: "Specific, observable behaviours that demonstrate the competency"
    - field: "prerequisite_knowledge"
      type: "array"
      description: "What students must already know or be able to do before attempting this"
    - field: "common_misconceptions"
      type: "array"
      description: "Typical misunderstandings that interfere with demonstrating this competency"
    - field: "success_criteria"
      type: "object"
      description: "Success criteria at multiple levels — beginning, developing, secure, extending"
chains_well_with:
  - "backwards-design-unit-planner"
  - "criterion-referenced-rubric-generator"
  - "learning-progression-builder"
  - "formative-assessment-technique-selector"
  - "curriculum-knowledge-architecture-designer"
  - "kud-knowledge-type-mapper"
  - "scope-and-sequence-designer"
teacher_time: "3 minutes"
tags: ["competency", "standards", "success-criteria", "unpacking", "curriculum"]
---

# Competency Unpacker

## What This Skill Does

Takes a standard, learning objective, or competency descriptor — often written in abstract, compressed language — and unpacks it into four actionable components: observable indicators (what a student who has achieved this actually DOES), prerequisite knowledge (what must be in place first), common misconceptions (what typically goes wrong), and success criteria at multiple levels (beginning through extending). The output transforms opaque curriculum language into concrete, assessable, teachable components. AI is specifically valuable here because competency descriptors are deliberately compressed — a single sentence like "analyse how writers use language and structure to achieve effects" contains multiple skills, knowledge domains, and levels of sophistication that must be unpacked before they can be taught or assessed.

## Evidence Foundation

Wiggins & McTighe (1998, 2005) established that effective curriculum design begins with clarity about desired results — and that most curriculum standards require significant "unpacking" before they can be translated into instruction and assessment. A standard that says "students will understand