curl -X POST "$BASE_URL/recommend-as" \
-H "Authorization: Bearer $ACCESS_TOKEN" \
-H "Content-Type: application/json" \
-d '{
"subjectCode": "EGN",
"learningOutcomes": [
{ "id": "lo-1", "reference": "1.4",
"text": "recognise the origins of everyday materials" }
],
"k": 10
}'
{
"success": true,
"recommendations": [
{
"id": 17,
"subject_code": "EGN",
"assessment_name": "Project-based assessment",
"description": "Students design and build to a brief over several lessons.",
"category": "Summative",
"skills_assessed": "Design, fabrication, evaluation",
"depth": "Deep",
"timing": "End of unit",
"score": 0.79
}
],
"metadata": {
"subjectCode": "EGN",
"learningOutcomeCount": 1,
"count": 10,
"timestamp": "2026-08-21T12:00:00.000Z"
}
}
Curriculum
Recommend assessments
Suggest assessment methods that suit a set of learning outcomes.
POST
/
recommend-as
curl -X POST "$BASE_URL/recommend-as" \
-H "Authorization: Bearer $ACCESS_TOKEN" \
-H "Content-Type: application/json" \
-d '{
"subjectCode": "EGN",
"learningOutcomes": [
{ "id": "lo-1", "reference": "1.4",
"text": "recognise the origins of everyday materials" }
],
"k": 10
}'
{
"success": true,
"recommendations": [
{
"id": 17,
"subject_code": "EGN",
"assessment_name": "Project-based assessment",
"description": "Students design and build to a brief over several lessons.",
"category": "Summative",
"skills_assessed": "Design, fabrication, evaluation",
"depth": "Deep",
"timing": "End of unit",
"score": 0.79
}
],
"metadata": {
"subjectCode": "EGN",
"learningOutcomeCount": 1,
"count": 10,
"timestamp": "2026-08-21T12:00:00.000Z"
}
}
The assessment counterpart to
/recommend-lo. Given the outcomes a
unit covers, returns the assessment methods that best suit them, ranked.
Where /recommend-lo matches on a topic string, this matches on the outcomes
themselves — their text is concatenated into one query and embedded, so the
suggestions follow what the unit actually teaches.
Request
string
required
Specification code for the subject, e.g.
"ENG". Same
supported set as
/recommend-lo.object[]
required
number
default:"10"
How many recommendations to return. Note the default is
10 here, against
5 for /recommend-lo.curl -X POST "$BASE_URL/recommend-as" \
-H "Authorization: Bearer $ACCESS_TOKEN" \
-H "Content-Type: application/json" \
-d '{
"subjectCode": "EGN",
"learningOutcomes": [
{ "id": "lo-1", "reference": "1.4",
"text": "recognise the origins of everyday materials" }
],
"k": 10
}'
Response
boolean
true on a successful match.object[]
Ranked assessment methods, best fit first. Each entry carries
assessment_name, description, category, skills_assessed, depth,
timing and a score.object
Echoes
subjectCode, plus learningOutcomeCount, count and an ISO
timestamp.{
"success": true,
"recommendations": [
{
"id": 17,
"subject_code": "EGN",
"assessment_name": "Project-based assessment",
"description": "Students design and build to a brief over several lessons.",
"category": "Summative",
"skills_assessed": "Design, fabrication, evaluation",
"depth": "Deep",
"timing": "End of unit",
"score": 0.79
}
],
"metadata": {
"subjectCode": "EGN",
"learningOutcomeCount": 1,
"count": 10,
"timestamp": "2026-08-21T12:00:00.000Z"
}
}
Errors
Same coded-error convention as/recommend-lo, with one extra case.
code | Status | Cause |
|---|---|---|
METHOD_NOT_ALLOWED | 405 | Anything other than POST. |
MISSING_SUBJECT_CODE | 400 | subjectCode absent. |
MISSING_LEARNING_OUTCOMES | 400 | learningOutcomes absent, not an array, or empty. |
UNSUPPORTED_SUBJECT | 400 | Not in the supported list. |
EMPTY_LEARNING_OUTCOMES | 400 | Outcomes were supplied, but every text was blank once trimmed. |
MISSING_LEARNING_OUTCOMES and EMPTY_LEARNING_OUTCOMES are different
failures. The first means you sent no outcomes; the second means you sent
outcomes whose text was empty, so there was nothing to embed.