INDICATORS REFERENCE
Wellness Intelligence Indicators
Wellness Intelligence covers 200 indicators across 4 wellness groups. Each signal has a stable slug and code for programmatic access. Representative signals are shown publicly; the complete reference is available to customers.
Showing 4 representative indicators of 200. The complete taxonomy is available to customers.
Request access| # | Indicator | Slug | code | Wellness Group |
|---|---|---|---|---|
| 001 | wellness checkin | wellness_checkin |
mental_emotional.wellness_checkin |
Mental Emotional |
| 002 | sleep quality good | sleep_quality_good |
physical_health.sleep_quality_good |
Physical Health |
| 003 | social connection | social_connection |
social_support.social_connection |
Social Support |
| 004 | task creation | task_creation |
tools_productivity.task_creation |
Tools Productivity |
No indicators found matching your search.
Browse by Wellness Group
Alternatively, explore indicators grouped by their parent wellness group:
1
Mental Emotional
mental_emotional
60 Indicators
Mental Emotional
mental_emotional
The complete signal list for this wellness group is available to customers. Request access to view it.
2
Physical Health
physical_health
70 Indicators
Physical Health
physical_health
The complete signal list for this wellness group is available to customers. Request access to view it.
3
Social Support
social_support
20 Indicators
Social Support
social_support
The complete signal list for this wellness group is available to customers. Request access to view it.
4
Tools Productivity
tools_productivity
50 Indicators
Tools Productivity
tools_productivity
The complete signal list for this wellness group is available to customers. Request access to view it.
Reading Wellness Intelligence output
What you can safely infer from a result - and what you must not.
Intended task
Turn check-in and journal text into documented wellbeing signals - sleep, stress, coping, help-seeking - that a wellness product can route on.
Input requirements
text- the only field analyzed; up to 4,096 Unicode code points. Over the limit is rejected withinput_too_long, never truncated.language- must be a language this analyzer supports. Unsupported codes are rejected with400 unsupported_language, never analyzed as a different language.analyzers- include"wellness"; up to 2 analyzers per request, one billed run each.- No context beyond
text- no user IDs, history, profiles, or attachments are read or inferred. - Very short check-ins carry little signal - "tired" alone can return a weak or empty result.
Ordinary positive
“I have slept badly three nights running and keep skipping meals - I feel completely drained.”
Safe inference: The check-in touches sleep, stress, and nutrition - enough to route a recovery-focused suggestion rather than a generic tip.
Confusing negative · Insufficient context
“My doctor said my results were normal but I still feel exhausted.”
What happens: Wellbeing signals can fire on the fatigue language - but the text also mentions a clinical finding the analyzer cannot evaluate. The signal describes wellbeing language in the text; it does not weigh medical content.
Why it's tricky: Wellness text often brushes against clinical claims. A sleep or stress signal is a content-routing hint - it is never a diagnosis, and concerning content should follow your own escalation policy rather than the signal alone.
What you can safely infer
- Which documented wellbeing topics the text touches, and at what strength.
- That results are reproducible - the same check-in on the same pinned configuration returns the same signals.
What you must not infer
- ✕A diagnosis or clinical status - wellness signals are not medical assessment.
- ✕That a user is at risk, or safe - escalation decisions belong to your own safety policy and human review.
- ✕That flat or empty results mean the user is well - thin text is thin evidence, not a clean bill of health.
Boundary: Wellness signals are not diagnoses. They describe wellbeing language in the text for product routing - suggestions, check-ins, content matching - never a clinical assessment.
Using Indicators in API Responses
When you call /v1/analyze, the response includes matched indicators with signal-match scores. Each signal is identified by its code and includes a level field (“category” or “label”). A score expresses signal-match strength under a particular analyzer configuration. It is not a probability that the signal or a downstream action is correct. Validate action thresholds on representative labeled data.
{
"language": "en",
"language_source": "declared",
"signals": [
{
"analyzer": "wellness",
"code": "physical_health",
"label": "Physical Health",
"score": 0.93,
"level": "category"
},
{
"analyzer": "wellness",
"code": "sleep_quality_poor",
"label": "Poor sleep quality",
"score": 0.91,
"level": "label",
"parent": "physical_health"
},
{
"analyzer": "wellness",
"code": "difficulty_falling_asleep",
"label": "Difficulty falling asleep",
"score": 0.88,
"level": "label",
"parent": "physical_health"
}
],
"meta": {
"analyzers": [
{
"name": "wellness",
"status": "completed",
"applicability": "analyzable",
"assessment": "signals_detected",
"signal_count": 3,
"billed": true
}
]
},
"usage": {
"analyzer_runs": 1
},
"verification": {
"configuration": "sqcfg_WJ0XM1NX",
"fingerprint": "fp_8a72...19f",
"input_commitment": "ic_31bd...a42",
"signature": "sig_ed25519_4c1f...e2a",
"key_id": "edk_af4f218e"
}
}Quickstart Guide
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