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developmental-band-translator

Tags harness-decomposed curriculum items (KUDs, LTs, criteria) with a school's developmental band metadata while preserving source voice and labels. Supply the band schema; the skill derives mapping rules from it.

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What This Skill Does

This skill tags an external curriculum — already decomposed by the curriculum harness into KUD items, learning targets, and (optionally) criteria — with a school's developmental band labels. The school's band schema is supplied as an input; the skill reads it, derives a mapping table from the source's age ranges to the school's band ranges, and applies that mapping across every item. Every item receives a school_band value, a confidence level, and diagnostic flags. The source's own band labels are preserved verbatim alongside the new school band tags, so the output can always be traced back to, and interpreted against, the original framework.

The skill is a metadata operation, not a content operation. It does not rewrite KUDs, LTs, or criteria, and it does not reinterpret the source's intent. Its only job is to answer the question: "If a teacher planning for a given school band opened this framework, which of its content is relevant to them?" The skill is deliberately conservative where a source band spans two school bands: it assigns both candidate bands, sets an ambiguity flag, and records a rationale. Downstream skills — especially the Curriculum Crosswalk skill and the human planning process — resolve these ambiguities with teacher judgement.

The skill handles three common source-structure scenarios. Most sources have an explicit band structure (Welsh CfW Progression Steps, NZ Curriculum Levels, IB PYP/MYP/DP phases) which maps cleanly with occasional boundary ambiguity. Some have a formal-but-compressed structure (UK RSHE has four Key Stage labels but only two actual age bands in the statutory document), where the skill applies the source's real 2-band structure first and records the formal label via source_band_preserved. A minority have no band structure at all (CASEL, some competency frameworks), where the skill maps by developmental descriptor rather than age and flags every item for teacher review.

Evidence Foundation

Wiggins & McTighe (2005, 2011) — Understanding by Design establishes KUD (Know / Understand / Do) as the unit-level architecture through which framework content becomes teachable, and positions curriculum alignment as a backward-design operation from stated outcomes. The Developmental Band Translator operates on exactly the KUD layer that UbD specifies, and treats school-band assignment as one step in a backward-design pipeline whose final consumer is the classroom teacher.

Vygotsky (1978) — The Zone of Proximal Development grounds the concept that developmental banding is not a pure age-partition. A learner in a given band is defined by what they can do with support, not only by their chronological age. This justifies the skill's use of both age-range and developmental-descriptor evidence when tagging, and its willingness to assign a school band from descriptor-based reasoning alone when age evidence is absent.

Heritage (2008) — Learning progressions literature reinforces that progressions are developmental trajectories, not calendars. The skill treats school bands as trajectory-waypoints. Where a source's native progression is coarser than the school's (e.g. RSHE's 2-band structure vs a 6-band school schema), the skill preserves the coarseness honestly via ambiguity flags rather than forcing false precision.

Webb (1997) — The canonical alignment framework defines four alignment dimensions: categorical concurrence, depth-of-knowledge consistency, range-of-knowledge correspondence, balance of representation. Band translation addresses primarily the range dimension (do the age spans match?) with partial touch on categorical concurrence. The skill does not claim to assess depth or balance alignment; this limit is reported in skill_flags and in Known Limitations.

Input Schema

Required inputs. The skill needs four inputs. The age-context rules below clarify the legacy age-range descriptions in the unchanged frontmatter: check a supplied override and the flat-framework exception before requesting missing native age ranges.

  • band_schema — The school or programme's developmental band definitions. Must include band labels, approximate age or grade ranges, and any named groupings. The skill reads this to build the mapping table; it does not assume any particular band system. Example: "REAL School Budapest uses Bands A–F — A (Water+Air Dragons, K–2, ages 5–7), B (Earth Dragons, G3–4, ages 7–9), C (Fire Dragons, G5–6, ages 9–11), D (Metal+Light Dragons, G7–8, ages 11–13), E (G9–10, ages 13–15), F (G11–12, ages 15–17)."
  • kud_json — The KUD file. Required fields per item: item_id, content_statement, knowledge_type, source_block_id. The skill uses source_block_id to look up the block's native band label in the progression structure.
  • lts_json — The LT file. Required fields per LT: lt_id, lt_name, lt_definition, kud_item_ids, knowledge_type. LTs inherit their band from their constituent KUD items using a max-span rule (see Prompt).
  • progression_structure_json — The progression structure. Required: band_labels and source_type; use a top-level age_range_hint or per-band approximate_age_range for age-based mapping. If native ages are absent, first check user_age_range_override and the flat-framework branch below. Request age context and halt only when neither provides a defensible mapping.

Optional inputs.

  • criterion_bank_json — If supplied, criteria are also tagged. Criteria inherit their parent LT's band unless their content narrows to a more specific age-range signal.
  • source_name — A friendly name for output metadata.
  • user_age_range_override — A user-supplied age-range mapping; it may be supplied on the first invocation or after request_age_range_context. Apply it as mapping context before the no-age check, preserving native labels and recording its user-supplied status and any conflict with native ages in skill_flags.

Worked example of required inputs. For a REAL School Budapest run against uk-statutory-rshe: band_schema = "REAL School Budapest uses Bands A–F — A (Water+Air Dragons, K–2, ages 5–7), B (Earth Dragons, G3–4, ages 7–9), C (Fire Dragons, G5–6, ages 9–11), D (Metal+Light Dragons, G7–8, ages 11–13), E (G9–10, ages 13–15), F (G11–12, ages 15–17)"; kud_json = the 279-item KUD file; lts_json = the 44-LT file; progression_structure_json = a structure declaring band_labels: ["End of Primary (Year 6)", "End of Secondary (Year 11)"], source_type: "national_statutory_curriculum", and age ranges 5–11 and 11–16 respectively.

Prompt

You are a curriculum band-translation assistant. Your task is to tag an external framework — already decomposed by the curriculum harness — with a school's developmental band labels, while preserving the source's own voice and labels completely unchanged.

School band schema

Read the supplied band_schema carefully. It defines the school's band labels, grade spans, age ranges, and any named groupings. All band assignments you produce must use the band labels exactly as defined in that schema.

Procedure

  1. Read the progression structure and choose mapping context. Preserve source_type and band_labels. First apply an explicit user_age_range_override as user-supplied mapping context, without rewriting native labels or ages; flag any conflict with native ranges for teacher review. Otherwise use native age_range_hint or per-band approximate_age_range. If neither exists and this is a competency/dispositional framework with no native age structure, use the conservative flat-framework branch below. Only if none of these routes supports mapping, emit request_age_range_context in skill_flags, do not tag anything, and stop. Do not invent ages.
  2. Build a band-mapping table for this source. Using the band_schema and the mapping context selected in step 1 (or the flat-framework descriptors), identify which school bands overlap with each source band. Where a source band's age range spans multiple school bands, list all overlapping school bands as candidates and note the ambiguity. Where the source band maps cleanly to one school band, record low ambiguity. Record this mapping table in your reasoning before proceeding; every tagging decision in steps 3–5 must trace back to it.
  3. Tag every KUD item.
    • Look up its source_block_id to find the source band.
    • Apply the band-mapping table to get candidate school bands.
    • school_band: single band as a string if unambiguous; array of bands if ambiguous.
    • band_confidence: high if single school band and source age range ≤ the school's narrowest band span; medium if two school bands; low if three or more, or if derived by developmental-descriptor inference only.
    • source_band_preserved: the exact native label from the source (e.g. "Key Stage 2", "End of Primary", "Progression Step 3").
    • source_voice_preserved: always true. If you would need to rewrite the content to make it fit a school band, do NOT rewrite — instead set this to false and add a skill flag. This field exists to prove no rewriting occurred.
    • ambiguity_flag: true if school_band is an array.
    • teacher_review_flag: true when (a) school_band spans three or more bands, (b) confidence is low, (c) source_type is a dispositional/competency framework with no age-banding (e.g. CASEL), or (d) the content statement contains developmental language that would narrow the band beyond what the source label allows, or (e) a user-supplied override conflicts with native age ranges.
    • band_rationale: one sentence explaining the assignment.
  4. Tag every LT. An LT's school band is the union of its constituent KUD items' bands (max-span rule). If any constituent is ambiguous, the LT is ambiguous. teacher_review_flag fires if any constituent has it or if the LT aggregates across three or more school bands.
  5. Tag criteria (if criterion_bank_json supplied). Each criterion inherits its parent LT's band unless its content narrows it. Same field set as LTs.
  6. Emit summary counts and skill flags. Count items per school band, ambiguity flags, teacher-review flags, and low-confidence tags. Emit a skill flag for any source where >50% of items are ambiguous (signals a structural mismatch worth reviewing).

Source-voice preservation rule (hard constraint)

You are tagging content, not rewriting it. Do not paraphrase, shorten, or "translate" content statements, LT definitions, or criterion descriptions into the school's preferred prose style. Keep source content exactly as written. The only new text you generate is band_rationale.

CASEL / flat-framework handling

If source_type indicates a competency or dispositional framework with no age structure (e.g. CASEL), and no user_age_range_override was supplied:

  • Set teacher_review_flag: true on every item. If a descriptor does not support narrowing, retain all plausible school bands, explain the uncertainty, and ask for teacher context rather than guessing a precise age.
  • Set band_confidence: low on every item.
  • Base school_band on the developmental sophistication of the descriptor, mapped to the school bands from the supplied band_schema: early-developmental content (emotion-labeling, basic self-regulation) → earliest bands in the schema; mid-developmental content (perspective-taking, collaborative problem-solving) → mid-range bands; late-developmental content (systems-level social awareness, abstract ethical reasoning) → later bands in the schema.
  • Emit skill_flag: casel_style_framework_full_teacher_review_required.

Inputs

  • band_schema: {{band_schema}}
  • source_name: {{source_name}}
  • progression_structure_json: {{progression_structure_json}}
  • kud_json: {{kud_json}}
  • lts_json: {{lts_json}}
  • criterion_bank_json: {{criterion_bank_json}}
  • user_age_range_override: {{user_age_range_override}}

Produce the band-tagged output as a single JSON object conforming to the output schema. Do not rewrite source content. Do not invent bands the source cannot support.

Example Output

Context: REAL School Budapest band schema supplied as band_schema. Source: UK DfE Statutory RSHE (July 2025), progression_structure.band_labels = ["End of Primary (Year 6)", "End of Secondary (Year 11)"], source_type = "national_statutory_curriculum".

Illustrative input excerpt (the required KUD and LT files are omitted here for space; they must be supplied in a real run):

{
  "band_schema": "REAL School Budapest uses Bands A–F — A (Water+Air Dragons, K–2, ages 5–7), B (Earth Dragons, G3–4, ages 7–9), C (Fire Dragons, G5–6, ages 9–11), D (Metal+Light Dragons, G7–8, ages 11–13), E (G9–10, ages 13–15), F (G11–12, ages 15–17). Bands are defined primarily by grade level; ages are approximate.",
  "source_name": "UK DfE Statutory RSHE, July 2025",
  "progression_structure_json": "{ \"band_labels\": [\"End of Primary (Year 6)\", \"End of Secondary (Year 11)\"], \"source_type\": \"national_statutory_curriculum\", \"age_range_hint\": { \"End of Primary (Year 6)\": \"5–11\", \"End of Secondary (Year 11)\": \"11–16\" } }"
}

Output excerpt (summary counts below cover only these three KUD items and one LT):

{
  "source_metadata": {
    "source_name": "UK DfE Statutory RSHE, July 2025",
    "source_type": "national_statutory_curriculum",
    "source_band_labels": ["End of Primary (Year 6)", "End of Secondary (Year 11)"],
    "skill_version": "1.0",
    "run_timestamp": "2026-04-20T14:05:00Z"
  },
  "band_tagged_kud": [
    {
      "item_id": "blk_0002_item_01",
      "content_statement": "Young people understand the correct terms for different parts of the body",
      "knowledge_type": "Type 1",
      "school_band": ["A", "B", "C"],
      "band_confidence": "low",
      "source_band_preserved": "End of Primary (Year 6)",
      "source_voice_preserved": true,
      "ambiguity_flag": true,
      "teacher_review_flag": true,
      "band_rationale": "Source groups all primary-age content into one band spanning ages 5–11; REAL Bands A–C cover this same range (5–7, 7–9, 9–11 respectively)."
    },
    {
      "item_id": "blk_0346_item_03",
      "content_statement": "Pupils can communicate their boundaries about physical contact and privacy needs",
      "knowledge_type": "Type 2",
      "school_band": ["A", "B", "C"],
      "band_confidence": "low",
      "source_band_preserved": "End of Primary (Year 6)",
      "source_voice_preserved": true,
      "ambiguity_flag": true,
      "teacher_review_flag": true,
      "band_rationale": "Statutory End-of-Primary expectation covering ages 5–11; maps to REAL Bands A–C."
    },
    {
      "item_id": "blk_0210_item_02",
      "content_statement": "Students understand the concepts of, and laws relating to, sexual consent",
      "knowledge_type": "Type 1",
      "school_band": ["D", "E", "F"],
      "band_confidence": "low",
      "source_band_preserved": "End of Secondary (Year 11)",
      "source_voice_preserved": true,
      "ambiguity_flag": true,
      "teacher_review_flag": true,
      "band_rationale": "End-of-Secondary covers ages 11–16; REAL Bands D (11–13), E (13–15), and F (15–17) overlap this range; the partial overlap with F is retained for teacher review."
    }
  ],
  "band_tagged_lts": [
    {
      "lt_id": "cluster_01_lt_01",
      "lt_name": "Identifying Body Parts and Privacy",
      "school_band": ["A", "B", "C"],
      "band_confidence": "low",
      "source_band_preserved": "End of Primary (Year 6)",
      "source_voice_preserved": true,
      "ambiguity_flag": true,
      "teacher_review_flag": true,
      "band_rationale": "Aggregated from 4 KUD items all tagged End of Primary; max-span = REAL Bands A–C."
    }
  ],
  "summary_counts": {
    "total_kud_items": 3,
    "total_lts": 1,
    "kud_by_band": {"A-B-C_ambiguous": 2, "D-E-F_ambiguous": 1},
    "lts_by_band": {"A-B-C_ambiguous": 1},
    "teacher_review_flagged": 4,
    "low_confidence": 4
  },
  "skill_flags": [
    "high_ambiguity_rate_structural: 100% of items are ambiguous because source has 2 bands spanning 3 school bands each. This is expected for national_statutory_curriculum sources with compressed band structures; do not treat as a quality failure. Downstream planning must resolve via teacher judgement."
  ]
}

Known Limitations

The skill does not do construct alignment. Two items tagged to the same school band are not, by that fact alone, teaching the same thing. Webb's (1997) categorical-concurrence and depth-of-knowledge dimensions are out of scope. The skill answers "is this age-relevant?" not "does this match the school's learning intentions?" The Curriculum Crosswalk skill addresses relationships between frameworks but still requires human judgement for construct alignment.

Ambiguity is not resolvable by this skill. When a source's band structure is coarser than the school's — particularly UK RSHE's 2-band structure or any framework with fewer bands than the school schema — the skill deliberately preserves the ambiguity rather than guessing. High ambiguity rates (up to 100% for RSHE against a 6-band schema) are an honest report of the source's granularity, not a quality failure. They are resolved downstream by teacher judgement, which is why teacher_review_flag exists.

Developmental-descriptor inference (CASEL case) is approximate. When a framework has no age-banding, the skill maps by descriptor using the supplied band_schema as a guide — early-developmental descriptors → earliest bands in the schema; systems-level descriptors → later bands. These are provisional descriptor-based starting points, not validated age norms or framework-specific determinations. Content tagged this way should be treated as a scaffold for teacher review, not a validated mapping.

The skill assumes harness-validated input. It does not re-validate the source decomposition. If the upstream harness produced a broken KUD or LT file (cycles in prerequisite graph, content_statement missing, etc.), the skill will pass those errors through as band-tagged nonsense. Run the harness's own validation gates before invoking this skill.

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