Template Authoring

Template Authoring

Conflict Resolution

When guides conflict, apply this priority (highest first):

1. Rules and syntax specifications
2. Idioms and structural constraints
3. Principles
4. Convenience

Step 1: Load Guides (MANDATORY)

Before any template work, load the authoritative guides:

guide_get("openehr://guides/templates/principles")
guide_get("openehr://guides/templates/rules")

Load additional guides as needed:

• guide_get("openehr://guides/templates/oet-syntax") — OET authoring syntax
• guide_get("openehr://guides/templates/oet-idioms-cheatsheet") — common OET patterns
• guide_get("openehr://guides/templates/cgem-framework") — full CGEM dataset-splitting framework (Step 6)
• guide_get("openehr://guides/templates/opt-structure") / guide_get("openehr://guides/templates/web-template") — runtime forms (OPT, web template) when discussing deployment or FLAT/STRUCTURED paths

Step 2: Research Before Creating

Search for existing templates first:

ckm_template_search("<use-case>")

If creating a new template, search for archetypes to include:

ckm_archetype_search("<concept>")

When CKM comes up empty, published-on-GitHub project content is a secondary channel — repositories tagged with the openehr-content topic (search topic:openehr-content, ~14 repos: freshEHR, Apperta-CKM projects, regional programmes, individual modellers). CKM holds relatively few templates, so this is more often useful for templates than for archetypes. Treat finds as leads, not governed artefacts: unlike CKM there is no editorial review, no reliable lifecycle_state, and no integrity guarantee, so cite the repo and commit you looked at, never present a find as "published". This needs web access (WebSearch/WebFetch/gh), which this skill does not hold — ask the main session to run the search.

Step 3: Use-Case Specificity

Templates target particular clinical workflows. Define the use-case clearly:

• What clinical scenario does this template serve? (e.g., discharge summary, vital signs form, medication reconciliation)
• What data points are required vs optional?
• Who will use it? (clinician, nurse, admin)

Step 4: Archetype Aggregation

Selecting Archetypes

• Choose archetypes that precisely fit the use-case
• Minimize archetype count — each should serve a clear purpose
• Prefer well-established CKM archetypes over custom ones

COMPOSITION Structure

Templates are rooted in a COMPOSITION archetype. Nest entry archetypes (OBSERVATION, EVALUATION, INSTRUCTION, ACTION) and CLUSTER archetypes within it.

Use type_specification_get to verify COMPOSITION structure when needed.

Step 5: The Narrowing Principle

Templates constrain archetypes — they NEVER expand:

• Mandatory stays mandatory: Cannot make required fields optional
• Optional can become mandatory: Can set min=1 on optional fields
• Optional can be excluded: Set max=0 to hide fields
• Value sets only narrow: Can restrict coded text options, never add new ones
• Cardinality only narrows: Can reduce max occurrences, never increase beyond archetype definition
• Tightening unconstrained RM attributes is allowed: constraining an RM attribute the archetype left open is still narrowing

A template's four jobs (Archetype Technology Overview): composition (fill slots), element choice (remove/mandate/leave optional), narrowing, and setting defaults.

Defaults vs assumed values

Set a default value (OET: default="..." on a <Rule>) where the use case fixes or strongly implies a single value (e.g. setting, patient position). Defaults appear in the recorded data; archetype-level assumed values are semantic fallbacks for omitted optional items and do not appear in the data — never confuse the two.

Step 6: CGEM Framework

Use CGEM (freshEHR's analysis method — a design aid, not an openEHR specification) to decide how a dataset splits across templates, and to set each template's composition category. Load guide_get("openehr://guides/templates/cgem-framework") for the definitions, mapping table and caveats:

Applying it: inventory the datapoints → categorise each C/G/E/M → group same-category datapoints into candidate templates → set each template's category to match → decide reuse (Global Background is usually already modelled and often only read by the form; Event templates are prime reuse candidates) → confirm Managed Response items genuinely need INSTRUCTION/ACTION + ISM and downgrade the rest to simple records.

Three things to state explicitly in any split report:

• Four CGEM categories, three category codes — Managed Response is not a COMPOSITION.category; it is an event (or persistent) composition distinguished by its INSTRUCTION/ACTION entries and the ISM.
• 451 episodic is normative but unevenly implemented — confirm the target platform supports it; persistent plus governance conventions is the common fallback.
• One form commonly spans several compositions across several categories, so a single form rarely means a single template.

Step 6b: Template from a form (inverse workflow)

When the starting point is a clinical form to implement rather than a template design, load references/template-from-form.md and follow it: parse the form into a field inventory, run the CGEM dataset split (Step 6) first, then sketch each implied template — archetypes to aggregate, RM entry type per field group, narrowing notes. Step 1's mandatory guide loads still apply in this mode (plus the CGEM guide — the reference covers it). The output is a design sketch, never OET XML; once the user confirms the sketch, continue at Step 8b to emit the file.

Step 7: Terminology in Templates

• Prefer DV_CODED_TEXT over free text where possible
• Constrain value sets to the local clinical context
• Use terminology_resolve to verify openEHR terminology bindings inherited from archetypes — openEHR terminology only; it errors on external codes, so check SNOMED CT / LOINC / ICD bindings against the archetype's own term_bindings rubrics instead

Step 8: The four serialisations

One design intent, four serialisations at three layers — not interchangeable, and only OET is hand-authorable:

OET (or .t.json) + archetypes  ──►  OPT  ──►  web template

.t.json is not a web template — it sits at the source layer with slots intact, while a web template is flattened runtime JSON with aqlPath/inputs. Both come from Better, at opposite ends of the pipeline; "the Better template" is ambiguous, so always name which one.

For when each format is hand-authorable vs tool-generated and what checksums each carries, load guide_get("openehr://guides/templates/serialization-formats"); for the runtime forms in depth, guide_get("openehr://guides/templates/opt-structure") and guide_get("openehr://guides/templates/web-template"). Reference syntax guides:

guide_get("openehr://guides/templates/oet-syntax")
guide_get("openehr://guides/templates/oet-idioms-cheatsheet")

Step 8b: Emit the OET

Produce a real, slot-correct OET — not just a design sketch. (The from-form mode in Step 6b produces the sketch; this step turns a confirmed design into the file.) Following templates/oet-syntax:

1. Root <template> with a root COMPOSITION archetype reference and a fresh <id> (see UID note below).
2. A <Content> entry per included archetype, nested to mirror the COMPOSITION → SECTION → ENTRY → CLUSTER structure.
3. <Rule path="…"> elements for each narrowing constraint (min/max, limitToList, unit hardening, hide_on_form, label overrides, default="…" for use-case-fixed values) — respecting the narrowing principle (Step 5).
4. A trailing <Context> if the design needs composition context (e.g. /context/setting fixed to a code).

There is no automated OET/OPT validator available, so validate manually against the loaded templates/oet-syntax guide and the Step 9 checklist; state any unconfirmed constraint rather than asserting validity.

Step 9: Quality Review

Run through the quality checklist:

guide_get("openehr://guides/templates/checklist")

Verify:

• Clear use-case definition
• Appropriate archetype selection
• Narrowing principle respected (no expansions)
• Required fields marked correctly
• Excluded fields set to max=0
• Terminology constraints appropriate for context
• Value sets verified (quantity constraints, unit hardening, "limit to list" coded text)
• Defaults set where the use case fixes a single value (setting, patient position); no assumed-value confusion
• Annotations and UI hints appropriate (hide_on_form, contextual label overrides)
• Valid OET syntax

Output

Generate valid OET files. Use the Write tool to create .oet files in the appropriate project location.

Identifiers and checksums

• A new template needs a fresh uid — mint a random UUID (v4). If a shell is available, uuidgen (or python3 -c 'import uuid; print(uuid.uuid4())') works; otherwise generate the UUID directly (this skill has no Bash tool, so don't assume shell access).
• Do not hand-write build checksums (MD5-CAM-*, build_uid) — they are tool-computed; a missing/stale checksum is advisory and never blocks authoring the OET.