aql-authoring

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This skill should be used when the user asks to "write an AQL query", "optimize an AQL query", "review AQL", or "query openEHR data" — the multi-step authoring/optimization workflow for AQL (Archetype Query Language) over openEHR clinical data. For a one-off explanation of an existing query or a single AQL keyword/operator (no authoring), the `/openehr-explain` command suffices.

Cadasto By Cadasto schedule Updated 6/9/2026

name: aql-authoring description: > This skill should be used when the user asks to "write an AQL query", "optimize an AQL query", "review AQL", or "query openEHR data" — the multi-step authoring/optimization workflow for AQL (Archetype Query Language) over openEHR clinical data. For a one-off explanation of an existing query or a single AQL keyword/operator (no authoring), the /openehr-explain command suffices. argument-hint: "" allowed-tools: - Read - Glob - Grep - mcp__openehr-assistant__guide_get - mcp__openehr-assistant__ckm_archetype_get - mcp__openehr-assistant__ckm_template_get - mcp__openehr-assistant__type_specification_get - mcp__openehr-assistant__examples_search - mcp__openehr-assistant__examples_get

AQL Authoring

The inline syntax below is a quick crib. The aql/syntax guide loaded in Step 1 is authoritative — if they ever disagree, follow the guide.

Step 1: Load Guides (MANDATORY)

Before writing or reviewing any AQL query, load the authoritative guides:

guide_get("aql/principles")
guide_get("aql/syntax")
guide_get("aql/idioms-cheatsheet")

Consult worked examples (when applicable)

When the user asks for a query to adapt, or when the clinical question matches a common pattern (cohort selection, pagination with total count, time-window filtering, cross-composition joins, terminology value-set matching, "latest per EHR", ISM-state filtering), try examples_search(kind="aql") before drafting. The curated AQL examples are under openehr://examples/aql/{name} and include pattern metadata and related-spec links — reuse and adapt rather than invent. Skip this step if the question is clearly novel or the user already provided the skeleton.

Step 2: Understand the Data Model

AQL queries operate on archetypes. Before writing a query:

  1. State assumptions about deployed templates/archetypes — verify path endpoints and RM types against the deployed template, not display labels
  2. Identify which archetypes contain the data you need
  3. Load the archetype to understand its path structure:
    ckm_archetype_get("<archetype-id>")
    
  4. Use type_specification_get if you need to understand RM type details

Step 3: AQL Syntax

Basic Structure

SELECT <paths>
FROM EHR e
  CONTAINS COMPOSITION c[openEHR-EHR-COMPOSITION.<name>.v1]
    CONTAINS OBSERVATION o[openEHR-EHR-OBSERVATION.<name>.v1]
WHERE <conditions>
ORDER BY <paths>

Containment

Define the archetype hierarchy using CONTAINS:

FROM EHR e
  CONTAINS COMPOSITION c
    CONTAINS OBSERVATION o[openEHR-EHR-OBSERVATION.blood_pressure.v2]

Path Syntax

Navigate archetype structure using at-codes:

o/data[at0001]/events[at0006]/data[at0003]/items[at0004]/value/magnitude

EHR Predicates

Filter by patient:

FROM EHR e[ehr_id/value = $ehr_id]

Parameterized Queries

Use $parameter syntax for reusable queries:

WHERE o/data[at0001]/events[at0006]/time/value > $start_date

Step 4: Common Patterns

Latest Composition by Type

SELECT c
FROM EHR e[ehr_id/value = $ehr_id]
  CONTAINS COMPOSITION c[openEHR-EHR-COMPOSITION.encounter.v1]
ORDER BY c/context/start_time/value DESC
LIMIT 1

Observations in Date Range

SELECT o/data[at0001]/events[at0006]/data[at0003]/items[at0004]/value/magnitude AS systolic
FROM EHR e[ehr_id/value = $ehr_id]
  CONTAINS COMPOSITION c
    CONTAINS OBSERVATION o[openEHR-EHR-OBSERVATION.blood_pressure.v2]
WHERE c/context/start_time/value >= $start_date
  AND c/context/start_time/value <= $end_date

Aggregates

SELECT
  COUNT(o) AS count,
  AVG(o/data[at0001]/events[at0006]/data[at0003]/items[at0004]/value/magnitude) AS avg_systolic
FROM EHR e
  CONTAINS COMPOSITION c
    CONTAINS OBSERVATION o[openEHR-EHR-OBSERVATION.blood_pressure.v2]
GROUP BY e/ehr_id/value

Step 5: Optimization

  • Use specific archetype node IDs in containment (avoid unqualified CONTAINS OBSERVATION o)
  • Avoid SELECT * — select only needed paths
  • Place most selective WHERE conditions first
  • Use parameterized queries for repeated execution
  • Consider index-friendly patterns (ehr_id, composition time, archetype node IDs)
  • Do not assume engine-specific behavior beyond the AQL specification

Step 6: Review

Run through the AQL checklist:

guide_get("aql/checklist")

Verify:

  • Correct containment hierarchy matching the archetype structure
  • Valid archetype paths (matching at-codes from the archetype definition)
  • Proper use of aliases for readability
  • Parameters used for variable values
  • Results ordered meaningfully
  • Query is optimized for the CDR
Install via CLI
npx skills add https://github.com/Cadasto/openehr-assistant-plugin --skill aql-authoring
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