We run a document extraction pipeline on Gemini with a native responseSchema
attached, not a "please reply with JSON" instruction in the prompt text. Over two months, three separate production problems traced back to behaviours of that schema that are not in Google's documentation.
These are the rules we ship with now, and the measurement behind each one. The domain is anonymized (no client, no industry, role codes renamed). Every number, date, model name and error string is real.
required
array identity, then evidence, then derived. It controls emission order, and emission order controls correctness.enum
arrays are enforced. Values listed in a description
are not constrained at all.PROVIDER_EXHAUSTED
right after a prompt change means your schema is broken, not that Google is busy.required
identity, evidence, derived
Gemini emits every required
property first, in exactly the order the required
array lists them, then the optional ones. The declaration order inside properties
is ignored for the required set.
This is empirical. It is not in Google's docs. We measured it on gemini-3-flash-preview
twice, with opposite orders, reading the raw response text:
| schema | position of role_code in required
|
position in emitted JSON |
|---|---|---|
| v18 | 3rd | 3rd |
| v19 | 14th (last) | 14th |
In v18 that field was 12th in properties
and 3rd in required
. It came out 3rd. properties
is not the lever.
propertyOrdering
is the documented knob, but if you do not set it (we do not, anywhere), the required
order is what governs.
A model writing JSON does one forward pass. Whatever it has already emitted is in context. Whatever it has not is not. And an emitted token cannot be revised when a later field contradicts it.
So a field emitted early is decided with almost no self-generated evidence, and a field emitted late is decided with everything above it visible.
v18 put role_code
third in required
, after only first_name
and last_name
. Its instruction was a priority ladder:
work_history
entry (Nine CVs, all advertising the same role. Four came back with L3-OPS
, a role from a different department. All four were internally self-contradictory:
{
"role_code": "L3-OPS",
"department": "Technical",
"work_history": [{ "title": "L3-TECH", "...": "..." }]
}
Both codes are valid members of the 143-value enum, so nothing rejected the output. department
, which agreed with the correct reading in all four cases, was emitted 11th, long after the wrong token was committed. The consistency check that would have caught the error was generated downstream of the error.
Ruled out first: environment drift (schemas byte-identical), downstream mapping (the wrong code was already in the raw provider response), a missing enum value (the correct code was present, and used correctly elsewhere in the same responses), and ambiguous source documents (zero matches for any operations wording, 11 to 20 matches for technical wording per document).
Reorder required
. Nothing else. No type change, no enum change, no shape change.
v18: first_name, last_name, role_code, contacts, nationalities, date_of_birth,
work_history, certifications, documents, education, languages, address,
home_airport, department
v19: first_name, last_name, date_of_birth, nationalities, contacts,
work_history, certifications, education, documents, languages, address,
home_airport, department, role_code
Result: 9 of 9 correct, up from 5 of 9. Emitted position of role_code
moved 3 to 14, exactly as predicted.
| class | meaning | position |
|---|---|---|
| identity | copied off the document, no reasoning (first_name , date_of_birth ) |
|
| first | ||
| evidence | the substantive extracted content (work_history , certifications ) |
|
| middle | ||
| derived | a judgement about the evidence (role_code , department , any score, total or summary) |
|
| last |
Three things that come with the reorder:
Descriptions must not forward-reference. Once department
moved ahead of role_code
, its old text ("classify from the stated role_code
") became the same bug in miniature. After any reorder, re-read every description for references to fields that now come later.
Tell the model the evidence is already there. Reordering alone is silent. v19's priority 2 became: "You have ALREADY emitted the work_history array above. Read the title of its first entry and use it."
Check for over-anchoring. The goal is grounding, not echoing. Two candidates whose most recent entry was one level below the applied-for role still correctly emitted the applied-for level, because priority 1 legitimately outranks priority 2. If every derived value suddenly equals evidence[0]
, you have over-corrected.
And the trap: required
is a set to a JSON Schema validator. Reordering it is semantically inert, so a formatter that sorts the array, or a tool that round trips the JSON, silently reverts the behaviour with a diff that looks like whitespace and passes every test. Say so in the file.
Do not respond to a wrong derived field by adding more prose first. v18 already carried four bullets of correct guidance for that field and was still wrong about 44% of the time. The instruction was not being disobeyed. It was being evaluated at a token position where its input did not exist.
Gemini rejects a schema above an undocumented ceiling on the total enum-value count across the whole schema. Google publishes no number, only that "very large or deeply nested schemas may be rejected".
| total enum values | result | when |
|---|---|---|
| 467 | accepted | v9, production |
| 610 | accepted, months of clean runs | v10-revised through v14 |
| 740 | ||
| rejected | ||
| v15, 2026-08-17 | ||
| 754 | rejected, reverted | v10-initial, 2026-07-13 |
The boundary is in (610, 740]. We never bisected it.
Three checkpoints were tried with the 740 schema, one preview and two GA releases:
| model | outcome |
|---|---|
gemini-3-flash-preview |
|
| 400 invalid argument | |
gemini-3.5-flash |
|
| 400 invalid argument | |
gemini-3.6-flash |
|
| 400 invalid argument |
Identical rejection across releases spanning months. This is a property of the constrained-decoding compiler, not of a checkpoint, so waiting for a newer model is not a mitigation.
You cannot deduplicate your way under the limit. Gemini's subset has no $ref
and no $defs
(see Rule 4), so every repeated list is paid for in full. A 145-value list used in three places costs 435, not 145.
Practical consequences:
description
instead. Descriptions cost nothing against the budget. Just know they are not enforced either (Rule 3).A rough counter is worth having in CI:
// Sums every enum array in a schema, nulls included.
function countEnums(node) {
if (Array.isArray(node)) return node.reduce((n, v) => n + countEnums(v), 0);
if (node && typeof node === 'object') {
return Object.entries(node).reduce(
(n, [k, v]) => n + (k === 'enum' && Array.isArray(v) ? v.length : countEnums(v)),
0
);
}
return 0;
}
responseSchema
guarantees JSON shape and types. It does not guarantee values, with one exception.
| how you express it | enforced? |
|---|---|
"enum": ["L3-TECH", "L3-OPS"] |
|
| yes, by constrained decoding | |
allowed values listed in description |
|
| no, purely advisory | |
maxLength |
|
| no | |
| array uniqueness | no |
In July, a schema change meant constrained decoding stopped being applied for five days. Nothing failed, nothing turned red, and 75 values that do not exist in the vocabulary reached production in a field the rest of the system indexes on.
So:
If the same prompt may run on more than one provider, store the schema in the more restrictive format. Gemini's subset is the floor.
| feature | OpenAI | Gemini |
|---|---|---|
$ref / $defs |
||
| supported | ||
| not supported, inline everything | ||
$schema , $id |
||
| supported | ||
| not supported, strip | ||
oneOf |
||
| supported | ||
not supported, single type + nullable |
||
["string", "null"] |
||
| supported | ||
not supported, use nullable |
||
exclusiveMinimum |
||
| supported | ||
not supported, use minimum |
||
pattern |
||
| supported | stripped | |
format: "uri" |
||
| supported | stripped | |
nullable |
||
| not used | ||
| required for nullable fields | ||
| max nesting | no limit | 5 levels |
| property ordering | not enforced | |
required order drives emission |
Rejected:
{
"$schema": "https://json-schema.org/draft/2020-12/schema",
"type": "object",
"properties": {
"role_code": { "$ref": "#/$defs/RoleCode" },
"start_year": { "type": "integer", "exclusiveMinimum": 1900 },
"email": { "type": ["string", "null"] },
"website": { "type": "string", "format": "uri" },
"ref": { "type": "string", "pattern": "^[A-Z]{2}-\\d{4}$" }
}
}
Accepted:
{
"type": "object",
"properties": {
"start_year": { "type": "integer", "minimum": 1901 },
"email": { "type": "string", "nullable": true },
"website": { "type": "string" },
"ref": { "type": "string", "description": "Two uppercase letters, hyphen, four digits" },
"role_code": { "type": "string", "enum": ["L3-TECH", "L3-OPS"] }
},
"required": ["start_year", "email", "website", "ref", "role_code"]
}
Note role_code
is last in required
, per Rule 1.
A malformed schema does not degrade politely. On 2026-08-27 a single "type": ["string", "null"]
union in one prompt failed every execution of it until the union was removed.
This is the one that costs the most hours, because the label sends you to the wrong system.
What the provider actually returns:
400 . Request contains an invalid argument.
No field pointer, no property name, no mention of size or enums. Deterministic on every retry, every key and every service tier.
What the operator sees by the time it surfaces:
processing_error PROVIDER_EXHAUSTED: Provider capacity unavailable
error_reason_code PROVIDER_EXHAUSTED
model (empty)
The chain is 400, then an API error, then the key circuit opens, then the retry ladder exhausts, then the last event gets reported instead of the first. It reads as a transient capacity shed. It is a permanent schema defect.
Triage table:
| symptom | actual meaning |
|---|---|
PROVIDER_EXHAUSTED with an empty model field, starting right after a prompt change |
|
| schema defect, not capacity | |
| the same failure on both STANDARD and FLEX tiers | not a tier or quota problem |
| identical failure across model checkpoints | constrained-decoding compiler, not the model |
| valid JSON with out-of-vocabulary values | constrained decoding was not applied at all |
The real error survives only in a WARN line, on whichever replica ran the worker, which is usually not the replica that logged the submission. Grep all of them:
for P in $(kubectl -n <ns> get pods -o name | grep -E "^pod/ai-" | grep -v db); do
kubectl -n <ns> logs $P --since=2h \
| grep -E "invalid argument|Circuit OPEN|keys exhausted"
done
Time-to-failure tells you nothing. We saw 30s and 165s for the same rejection and briefly read the slow one as "this model accepted the schema". It had not. The difference was retry parking.
If you store parsed responses in a jsonb
column, that column loses key order. Read the raw response text instead:
const raw = require('fs').readFileSync('raw.json', 'utf8').trim();
Object.keys(JSON.parse(raw)).forEach((k, i) => console.log(`${i + 1}. ${k}`));
Compare that against your required
array. If they diverge, the ordering law has changed for your model family and needs re-measuring.
required
ordered identity, then evidence, then derived.description
references a field emitted later.required
order is deliberate and must not be sorted.$ref
, no oneOf
, no type arrays, nullable
used, 5 levels max).PROVIDER_EXHAUSTED
after a prompt change means schema first, capacity second.Two of these five rules describe limits Google does not document, and both were established by breaking production. If you are running structured output at any scale, measure them for your own model family and write your own numbers down. The alternative is rediscovering them next quarter at the same price.