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Input: the answers file

Loaded by step 1  ·  Source of truth survey/sections/*.json  ·  Never invent a field ID

The agent receives one JSON object: the SurveyJS response data for a completed questionnaire, keyed by field ID.

{
  "client_full_name": "…",
  "client_dob": "1974-03-09",
  "health_conditions": ["High cholesterol", "Thyroid disorder"],
  "nut_ffq": { "Fresh fruit": "Daily", "Red meat & offal": "Occasionally" },
  "meas_weight": 78, "meas_weight__unit": "kg"
}

What the shapes mean

The value's JSON type follows from the question's SurveyJS type. Reading a value with the wrong expectation is the most common way to corrupt a menu silently, so the mapping is worth knowing.

SurveyJS type JSON value Example
text, comment string "Two 20-minute sessions"
text with inputType: "number" number 78
text with inputType: "date" YYYY-MM-DD string "1974-03-09"
boolean the valueTrue / valueFalse string — "Yes" / "No", not true / false "Yes"
radiogroup, dropdown one choice string "2–3 L"
checkbox array of choice strings ["Wine", "Beer"]
rating number within rateMin–rateMax 4
matrix object, row label → column label { "Eggs": "Daily" }
paneldynamic array of objects [{ "product_name": "…", "dosage": "…" }]
expression number, computed by SurveyJS 26.99
file, signaturepad ignore — not menu input

Booleans are strings

"health_surgeries": "Yes" is a string. Every boolean field in this questionnaire declares valueTrue: "Yes", so a truthiness test on the raw value passes for "No" as well. Compare to "Yes" explicitly.

Absence

Most fields are optional, and an unanswered field is simply absent from the object — not null, not "". Three further rules:

  1. clearInvisibleValues: "onHiddenContainer" is set on the survey. A conditional field whose trigger never fired is removed from the data, so its absence is meaningful: it means the question was never asked, not that it was skipped.
  2. Absent is not zero. A missing nut_caffeine means unknown, not caffeine-free. Never substitute a default and then reason from it as though the client had said it.
  3. Absence is recorded, not resolved. Where a missing field changes the menu, the menu says so — see the Assumptions section in the JSON schema.

Units

Three fields are paired with a __unit companion, and one pair is pre-converted for you by the survey's calculatedValues:

Value Unit field Pre-converted
meas_height meas_height__unit (cm / in) meas_height_cm
meas_weight meas_weight__unit (kg / lb) meas_weight_kg
meas_weight_self meas_weight_self__unit —
test_squat_est_1rm test_squat_est_1rm__unit —
test_deadlift_est_1rm test_deadlift_est_1rm__unit —

Prefer meas_height_cm and meas_weight_kg. They exist precisely so the agent never does unit conversion itself. If they are absent, fall back to the raw field plus its unit field, and convert with 1 in = 2.54 cm, 1 lb = 0.453592 kg.

meas_bmi and meas_whr are expression fields — SurveyJS computes them. Do not recompute; if present, use them.

The sections, and what step 1 wants from each

Full field lists are in the JSON. This is the orientation.

Section Fields Menu-relevant?
1. About you client_* Yes — age, gender, occupation, work activity
2. Health & medical history parq_*, health_* Yes — screening, conditions, supplements, allergies, alcohol, smoking
3. Systems review sys_* Yes — digestive symptoms, menstrual status, red flags
4. Injuries & movement inj_* Rarely — only via nut_eating_limitation
5. Activity & training history act_* Yes — activity factor
6. Goals & motivation goal_* Yes — direction of the energy adjustment, obstacles
7. Nutrition & hydration nut_* Yes — the richest section; pattern, FFQ, cooking, hydration
8. Sleep, stress & recovery life_* Yes — meal timing, shift work, energy crashes
9. Measurements & assessments meas_*, screen_*, test_* Yes — height, weight, BP, waist
10. Preferences & logistics pref_* Some — budget, travel, accessibility
11. Consent & sign-off consent_*, sign_* Gate only — see below

Section 11 is not menu content, but it is a precondition. Before step 3 runs:

  • consent_accuracy must be "Yes" — otherwise the answers are not warranted accurate and nothing should be derived from them.
  • consent_data_processing must be "Yes".
  • consent_clearance_confirm — where any PAR-Q trigger fired, this must be "Yes". If a trigger fired and this is absent or "No", that is a stop condition, not a caveat. See step 2.

A missing consent is not something to work around, note as an assumption, or proceed past. It stops the run.

Section 9 may be empty

Section 9 is filled by the coach at a baseline appointment, so a questionnaire completed by the client alone will have no meas_* values at all. Height and weight are the only two the menu genuinely requires, and section 9 offers a self-reported fallback for weight in meas_weight_self. How to proceed when even that is missing is covered in step 3.