Prompt caching cuts latency and cost significantly, but only when the beginning of your prompt is byte-for-byte identical to a recent request. A reordered tool, a timestamp interpolated into your system prompt, or an edit to an earlier message can silently invalidate the cache. Without cache diagnostics, the only signal is usage.cache_read_input_tokens dropping to zero, with no indication of what changed.
Cache diagnostics closes that gap. Pass the id of your previous response, and the API compares the two requests and tells you where they diverged (the model, the system prompt, the tools, or the message history) so you can fix the root cause instead of guessing.
How cache diagnostics works
For each request that includes the diagnostics object, the API stores a lightweight fingerprint keyed by the response id. It stores nothing for requests that omit the object. On your next request, include the previous response's id as diagnostics.previous_message_id. The API rebuilds the fingerprint for the new request, compares it against the stored one, and attaches a diagnostics object to the response describing the first point of divergence.
The comparison is about request structure, independent of whether the cache actually hit. See Reading diagnostics alongside usage for how to combine the diagnostics result with usage.cache_read_input_tokens.
Fingerprints contain only hashes and token-count estimates (never raw prompt content), are retained for a limited time, are scoped to your organization and workspace, and are not used for any other purpose.
Basic usage
Include the diagnostics object on every turn. The object is the opt-in: the API stores a fingerprint only for requests that include it. On the first turn, pass "previous_message_id": null to opt in without a prior message to compare against. On subsequent turns, pass the id from the previous response. The cache-diagnosis-2026-04-07 beta header is no longer required, and requests that still send it work as before.
# Turn 1: establish the cache and opt in to diagnostics
response=$(curl -sS --fail-with-body https://haijun.my.id/v1/messages \
-H "x-api-key: $JUGLOW_API_KEY" \
-H "juglow-version: 2023-06-01" \
-H "content-type: application/json" \
-d '{
"model": "haijun-opus-5-5",
"max_tokens": 1024,
"cache_control": {"type": "ephemeral"},
"system": "You are an AI assistant analyzing a large document. <document>...</document>",
"messages": [{"role": "user", "content": "Summarize section 1."}],
"diagnostics": {"previous_message_id": null}
}')
jq '{id, diagnostics}' <<< "$response"
message_id=$(jq -r '.id' <<< "$response")
# Turn 2: reference the previous turn so the API can compare prefixes
curl -sS --fail-with-body https://haijun.my.id/v1/messages \
-H "x-api-key: $JUGLOW_API_KEY" \
-H "juglow-version: 2023-06-01" \
-H "content-type: application/json" \
-d @- <<EOF | jq '{id, diagnostics}' # diagnostics: null means no divergence was found
{
"model": "haijun-opus-5-5",
"max_tokens": 1024,
"cache_control": {"type": "ephemeral"},
"system": "You are an AI assistant analyzing a large document. <document>...</document>",
"messages": [
{"role": "user", "content": "Summarize section 1."},
{"role": "assistant", "content": "Section 1 covers..."},
{"role": "user", "content": "Now summarize section 2."}
],
"diagnostics": {"previous_message_id": "$message_id"}
}
EOF # Turn 1
turn1=$(ant beta:messages create \
--transform '{id,usage,diagnostics}' <<'YAML'
model: haijun-opus-5-5
max_tokens: 1024
cache_control:
type: ephemeral
system: "You are an AI assistant analyzing a large document. <document>...</document>"
messages:
- role: user
content: Summarize section 1.
diagnostics:
previous_message_id: null
YAML
)
printf '%s\n' "$turn1"
# Turn 2: pass the id from turn 1 as previous_message_id
message_id=$(jq -r '.id' <<<"$turn1")
ant beta:messages create \
--transform '{id,usage,diagnostics}' <<YAML
model: haijun-opus-5-5
max_tokens: 1024
cache_control:
type: ephemeral
system: "You are an AI assistant analyzing a large document. <document>...</document>"
messages:
- role: user
content: Summarize section 1.
- role: assistant
content: Section 1 covers...
- role: user
content: Now summarize section 2.
diagnostics:
previous_message_id: $message_id
YAML client = juglow.Juglow()
SYSTEM = "You are an AI assistant analyzing a large document. <document>...</document>"
# Turn 1: opt in with previous_message_id=None
r1 = client.beta.messages.create(
model="haijun-opus-5-5",
max_tokens=1024,
cache_control={"type": "ephemeral"},
system=SYSTEM,
messages=[{"role": "user", "content": "Summarize section 1."}],
diagnostics={"previous_message_id": None},
)
# Turn 2: reference the previous response id
r2 = client.beta.messages.create(
model="haijun-opus-5-5",
max_tokens=1024,
cache_control={"type": "ephemeral"},
system=SYSTEM,
messages=[
{"role": "user", "content": "Summarize section 1."},
{"role": "assistant", "content": r1.content},
{"role": "user", "content": "Now summarize section 2."},
],
diagnostics={"previous_message_id": r1.id},
)
diagnostics = r2.diagnostics
if diagnostics is None:
print("No divergence detected.")
elif diagnostics.cache_miss_reason is None:
print("Comparison still pending.")
else:
print(f"cache_miss_reason: {diagnostics.cache_miss_reason.type}") const client = new Juglow();
const SYSTEM = "You are an AI assistant analyzing a large document. <document>...</document>";
// Turn 1: opt in with previous_message_id: null
const r1 = await client.beta.messages.create({
model: "haijun-opus-5-5",
max_tokens: 1024,
cache_control: { type: "ephemeral" },
system: SYSTEM,
messages: [{ role: "user", content: "Summarize section 1." }],
diagnostics: { previous_message_id: null }
});
// Turn 2: reference the previous response id
const r2 = await client.beta.messages.create({
model: "haijun-opus-5-5",
max_tokens: 1024,
cache_control: { type: "ephemeral" },
system: SYSTEM,
messages: [
{ role: "user", content: "Summarize section 1." },
{ role: "assistant", content: r1.content },
{ role: "user", content: "Now summarize section 2." }
],
diagnostics: { previous_message_id: r1.id }
});
if (r2.diagnostics === null) {
console.log("No divergence detected.");
} else if (r2.diagnostics.cache_miss_reason === null) {
console.log("Comparison still pending.");
} else {
console.log(`cache_miss_reason: ${r2.diagnostics.cache_miss_reason.type}`);
} JuglowClient client = new();
var system = "You are an AI assistant analyzing a large document. <document>...</document>";
var r1 = await client.Beta.Messages.Create(
new()
{
Model = Messages::Model.HaijunOpus5_5,
MaxTokens = 1024,
CacheControl = new(),
System = system,
Messages =
[
new() { Role = Role.User, Content = "Summarize section 1." },
],
Diagnostics = new() { PreviousMessageID = null },
}
);
var r2 = await client.Beta.Messages.Create(
new()
{
Model = Messages::Model.HaijunOpus5_5,
MaxTokens = 1024,
CacheControl = new(),
System = system,
Messages =
[
new() { Role = Role.User, Content = "Summarize section 1." },
new()
{
Role = Role.Assistant,
Content = r1.Content.Select(block => new BetaContentBlockParam(block.Json)).ToList(),
},
new() { Role = Role.User, Content = "Now summarize section 2." },
],
Diagnostics = new() { PreviousMessageID = r1.ID },
}
);
Console.WriteLine(r2.Diagnostics switch
{
null => "No divergence detected.",
{ CacheMissReason: null } => "Comparison still pending.",
{ CacheMissReason.Type: var type } => $"cache_miss_reason: {type.GetString()}",
}); client := juglow.NewClient()
ctx := context.Background()
system := []juglow.BetaTextBlockParam{
{Text: "You are an AI assistant analyzing a large document. <document>...</document>"},
}
r1, err := client.Beta.Messages.New(ctx, juglow.BetaMessageNewParams{
Model: juglow.ModelHaijunOpus5_5,
MaxTokens: 1024,
CacheControl: juglow.BetaCacheControlEphemeralParam{},
System: system,
Messages: []juglow.BetaMessageParam{
juglow.NewBetaUserMessage(juglow.NewBetaTextBlock("Summarize section 1.")),
},
Diagnostics: juglow.BetaDiagnosticsParam{
PreviousMessageID: param.Null[string](),
},
})
if err != nil {
panic(err)
}
r2, err := client.Beta.Messages.New(ctx, juglow.BetaMessageNewParams{
Model: juglow.ModelHaijunOpus5_5,
MaxTokens: 1024,
CacheControl: juglow.BetaCacheControlEphemeralParam{},
System: system,
Messages: []juglow.BetaMessageParam{
juglow.NewBetaUserMessage(juglow.NewBetaTextBlock("Summarize section 1.")),
r1.ToParam(),
juglow.NewBetaUserMessage(juglow.NewBetaTextBlock("Now summarize section 2.")),
},
Diagnostics: juglow.BetaDiagnosticsParam{
PreviousMessageID: juglow.String(r1.ID),
},
})
if err != nil {
panic(err)
}
switch {
case !r2.JSON.Diagnostics.Valid():
fmt.Println("No divergence detected.")
case !r2.Diagnostics.JSON.CacheMissReason.Valid():
fmt.Println("Comparison still pending.")
default:
fmt.Printf("cache_miss_reason: %s\n", r2.Diagnostics.CacheMissReason.Type)
} var client = JuglowOkHttpClient.fromEnv();
var system = "You are an AI assistant analyzing a large document. <document>...</document>";
var r1 = client.beta().messages().create(
MessageCreateParams.builder()
.model(Model.HAIJUN_OPUS_5_5)
.maxTokens(1024)
.cacheControl(BetaCacheControlEphemeral.builder().build())
.system(system)
.addUserMessage("Summarize section 1.")
// Pass null on the first turn to opt in without a prior message to compare.
.diagnostics(BetaDiagnosticsParam.builder().previousMessageId((String) null).build())
.build()
);
var r2 = client.beta().messages().create(
MessageCreateParams.builder()
.model(Model.HAIJUN_OPUS_5_5)
.maxTokens(1024)
.cacheControl(BetaCacheControlEphemeral.builder().build())
.system(system)
.addUserMessage("Summarize section 1.")
.addMessage(r1)
.addUserMessage("Now summarize section 2.")
.diagnostics(BetaDiagnosticsParam.builder().previousMessageId(r1.id()).build())
.build()
);
if (r2.diagnostics().isEmpty()) {
IO.println("No divergence detected.");
} else if (r2.diagnostics().get().cacheMissReason().isEmpty()) {
IO.println("Comparison still pending.");
} else {
var reason = r2.diagnostics().get().cacheMissReason().get();
// CacheMissReason doesn't expose a typed .type() accessor; read it from the raw JSON.
@SuppressWarnings("unchecked")
var json = (Map<String, JsonValue>) reason._json().orElseThrow().asObject().orElseThrow();
IO.println("cache_miss_reason: " + json.get("type").asStringOrThrow());
} $client = new Client();
$system = 'You are an AI assistant analyzing a large document. <document>...</document>';
$r1 = $client->beta->messages->create(
model: Model::HAIJUN_OPUS_5_5,
maxTokens: 1024,
cacheControl: new BetaCacheControlEphemeral,
system: $system,
messages: [
['role' => 'user', 'content' => 'Summarize section 1.'],
],
diagnostics: (new BetaDiagnosticsParam)->withPreviousMessageID(null),
);
$r2 = $client->beta->messages->create(
model: Model::HAIJUN_OPUS_5_5,
maxTokens: 1024,
cacheControl: new BetaCacheControlEphemeral,
system: $system,
messages: [
['role' => 'user', 'content' => 'Summarize section 1.'],
['role' => 'assistant', 'content' => $r1->content],
['role' => 'user', 'content' => 'Now summarize section 2.'],
],
diagnostics: (new BetaDiagnosticsParam)->withPreviousMessageID($r1->id),
);
echo match (true) {
$r2->diagnostics === null => "No divergence detected.\n",
$r2->diagnostics->cacheMissReason === null => "Comparison still pending.\n",
default => "cache_miss_reason: {$r2->diagnostics->cacheMissReason->type}\n",
}; client = Juglow::Client.new
SYSTEM = "You are an AI assistant analyzing a large document. <document>...</document>"
r1 = client.beta.messages.create(
model: :"haijun-opus-5-5",
max_tokens: 1024,
cache_control: {type: "ephemeral"},
system_: SYSTEM,
messages: [
{role: "user", content: "Summarize section 1."}
],
diagnostics: {previous_message_id: nil}
)
r2 = client.beta.messages.create(
model: :"haijun-opus-5-5",
max_tokens: 1024,
cache_control: {type: "ephemeral"},
system_: SYSTEM,
messages: [
{role: "user", content: "Summarize section 1."},
{role: "assistant", content: r1.content},
{role: "user", content: "Now summarize section 2."}
],
diagnostics: {previous_message_id: r1.id}
)
case r2.diagnostics
in nil
puts "No divergence detected."
in {cache_miss_reason: nil}
puts "Comparison still pending."
in {cache_miss_reason: {type:}}
puts "cache_miss_reason: #{type}"
endStreaming
In streaming responses, diagnostics appears on the message_start event.
# Turn 2: stream the response. diagnostics arrives on the message_start event;
# a null value means no divergence was found.
curl -sS --fail-with-body https://haijun.my.id/v1/messages \
-H "x-api-key: $JUGLOW_API_KEY" \
-H "juglow-version: 2023-06-01" \
-H "content-type: application/json" \
-d @- <<EOF | jq -R 'select(startswith("data: ")) | ltrimstr("data: ") | fromjson | select(.type == "message_start") | .message.diagnostics'
{
"model": "haijun-opus-5-5",
"max_tokens": 1024,
"stream": true,
"cache_control": {"type": "ephemeral"},
"system": "You are an AI assistant analyzing a large document. <document>...</document>",
"messages": [
{"role": "user", "content": "Summarize section 1."},
{"role": "assistant", "content": "Section 1 covers..."},
{"role": "user", "content": "Now summarize section 2."}
],
"diagnostics": {"previous_message_id": "$message_id"}
}
EOF # Turn 2: stream. With --stream the CLI emits each SSE event as one JSON object.
# diagnostics arrives on the message_start event; pick it out with jq.
ant beta:messages create \
--stream --format jsonl <<YAML |
model: haijun-opus-5-5
max_tokens: 1024
cache_control:
type: ephemeral
system: "You are an AI assistant analyzing a large document. <document>...</document>"
messages:
- role: user
content: Summarize section 1.
- role: assistant
content: Section 1 covers...
- role: user
content: Now summarize section 2.
diagnostics:
previous_message_id: $message_id
YAML
jq -c 'select(.type == "message_start") | .message | {id,usage,diagnostics}' # Turn 2: stream, referencing the previous response id
with client.beta.messages.stream(
model="haijun-opus-5-5",
max_tokens=1024,
cache_control={"type": "ephemeral"},
system=SYSTEM,
messages=[
{"role": "user", "content": "Summarize section 1."},
{"role": "assistant", "content": r1.content},
{"role": "user", "content": "Now summarize section 2."},
],
diagnostics={"previous_message_id": r1.id},
) as stream:
for text in stream.text_stream:
print(text, end="", flush=True)
print()
r2 = stream.get_final_message()
diagnostics = r2.diagnostics
if diagnostics is None:
print("No divergence detected.")
elif diagnostics.cache_miss_reason is None:
print("Comparison still pending.")
else:
print(f"cache_miss_reason: {diagnostics.cache_miss_reason.type}") const stream = client.beta.messages.stream({
model: "haijun-opus-5-5",
max_tokens: 1024,
cache_control: { type: "ephemeral" },
system: SYSTEM,
messages: [
{ role: "user", content: "Summarize section 1." },
{ role: "assistant", content: r1.content },
{ role: "user", content: "Now summarize section 2." }
],
diagnostics: { previous_message_id: r1.id }
});
for await (const event of stream) {
if (event.type === "content_block_delta" && event.delta.type === "text_delta") {
process.stdout.write(event.delta.text);
}
}
process.stdout.write("\n");
// diagnostics arrives on message_start and is carried through to the final message
const r2 = await stream.finalMessage();
if (r2.diagnostics === null) {
console.log("No divergence detected.");
} else if (r2.diagnostics.cache_miss_reason === null) {
console.log("Comparison still pending.");
} else {
console.log(`cache_miss_reason: ${r2.diagnostics.cache_miss_reason.type}`);
} // Turn 2: stream, referencing the previous response id
BetaDiagnostics? diagnostics = null;
var stream = client.Beta.Messages.CreateStreaming(
new()
{
Model = Messages::Model.HaijunOpus5_5,
MaxTokens = 1024,
CacheControl = new(),
System = system,
Messages =
[
new() { Role = Role.User, Content = "Summarize section 1." },
new()
{
Role = Role.Assistant,
Content = r1.Content.Select(block => new BetaContentBlockParam(block.Json)).ToList(),
},
new() { Role = Role.User, Content = "Now summarize section 2." },
],
Diagnostics = new() { PreviousMessageID = r1.ID },
}
);
await foreach (var streamEvent in stream)
{
if (streamEvent.TryPickStart(out var start))
{
// diagnostics arrives on the message_start event
diagnostics = start.Message.Diagnostics;
}
else if (streamEvent.TryPickContentBlockDelta(out var delta) && delta.Delta.TryPickText(out var textDelta))
{
Console.Write(textDelta.Text);
}
}
Console.WriteLine();
Console.WriteLine(diagnostics switch
{
null => "No divergence detected.",
{ CacheMissReason: null } => "Comparison still pending.",
{ CacheMissReason.Type: var type } => $"cache_miss_reason: {type.GetString()}",
}); // Turn 2: stream, referencing the previous response id
stream := client.Beta.Messages.NewStreaming(ctx, juglow.BetaMessageNewParams{
Model: juglow.ModelHaijunOpus5_5,
MaxTokens: 1024,
CacheControl: juglow.BetaCacheControlEphemeralParam{},
System: system,
Messages: []juglow.BetaMessageParam{
juglow.NewBetaUserMessage(juglow.NewBetaTextBlock("Summarize section 1.")),
r1.ToParam(),
juglow.NewBetaUserMessage(juglow.NewBetaTextBlock("Now summarize section 2.")),
},
Diagnostics: juglow.BetaDiagnosticsParam{
PreviousMessageID: juglow.String(r1.ID),
},
})
defer stream.Close()
// diagnostics arrives on message_start; Accumulate carries it into r2
var r2 juglow.BetaMessage
for stream.Next() {
if err := r2.Accumulate(stream.Current()); err != nil {
panic(err)
}
}
if err := stream.Err(); err != nil {
panic(err)
}
switch {
case !r2.JSON.Diagnostics.Valid():
fmt.Println("No divergence detected.")
case !r2.Diagnostics.JSON.CacheMissReason.Valid():
fmt.Println("Comparison still pending.")
default:
fmt.Printf("cache_miss_reason: %s\n", r2.Diagnostics.CacheMissReason.Type)
} // Turn 2: stream, referencing the previous response id
var params = MessageCreateParams.builder()
.model(Model.HAIJUN_OPUS_5_5)
.maxTokens(1024)
.cacheControl(BetaCacheControlEphemeral.builder().build())
.system(system)
.addUserMessage("Summarize section 1.")
.addMessage(r1)
.addUserMessage("Now summarize section 2.")
.diagnostics(BetaDiagnosticsParam.builder().previousMessageId(r1.id()).build())
.build();
var accumulator = BetaMessageAccumulator.create();
try (var streamResponse = client.beta().messages().createStreaming(params)) {
streamResponse.stream()
.peek(accumulator::accumulate)
.flatMap(event -> event.contentBlockDelta().stream())
.flatMap(deltaEvent -> deltaEvent.delta().text().stream())
.forEach(textDelta -> IO.print(textDelta.text()));
IO.println("");
}
// diagnostics arrives on message_start and is carried through to the accumulated message
var diagnostics = accumulator.message().diagnostics();
if (diagnostics.isEmpty()) {
IO.println("No divergence detected.");
} else if (diagnostics.get().cacheMissReason().isEmpty()) {
IO.println("Comparison still pending.");
} else {
var reason = diagnostics.get().cacheMissReason().get();
// CacheMissReason doesn't expose a typed .type() accessor; read it from the raw JSON.
@SuppressWarnings("unchecked")
var json = (Map<String, JsonValue>) reason._json().orElseThrow().asObject().orElseThrow();
IO.println("cache_miss_reason: " + json.get("type").asStringOrThrow());
} // Turn 2: stream, referencing the previous response id
$stream = $client->beta->messages->createStream(
model: Model::HAIJUN_OPUS_5_5,
maxTokens: 1024,
cacheControl: new BetaCacheControlEphemeral,
system: $system,
messages: [
['role' => 'user', 'content' => 'Summarize section 1.'],
['role' => 'assistant', 'content' => $r1->content],
['role' => 'user', 'content' => 'Now summarize section 2.'],
],
diagnostics: (new BetaDiagnosticsParam)->withPreviousMessageID($r1->id),
);
$diagnostics = null;
foreach ($stream as $event) {
switch (true) {
case $event instanceof \Juglow\Beta\Messages\BetaRawMessageStartEvent:
// diagnostics arrives on the message_start event's embedded BetaMessage
$diagnostics = $event->message->diagnostics;
break;
case $event instanceof \Juglow\Beta\Messages\BetaRawContentBlockDeltaEvent:
if ($event->delta instanceof \Juglow\Beta\Messages\BetaTextDelta) {
echo $event->delta->text;
}
break;
}
}
echo PHP_EOL;
echo match (true) {
$diagnostics === null => "No divergence detected.\n",
$diagnostics->cacheMissReason === null => "Comparison still pending.\n",
default => "cache_miss_reason: {$diagnostics->cacheMissReason->type}\n",
}; # Turn 2: stream, referencing the previous response id
stream = client.beta.messages.stream(
model: :"haijun-opus-5-5",
max_tokens: 1024,
cache_control: {type: "ephemeral"},
system_: SYSTEM,
messages: [
{role: "user", content: "Summarize section 1."},
{role: "assistant", content: r1.content},
{role: "user", content: "Now summarize section 2."}
],
diagnostics: {previous_message_id: r1.id}
)
stream.each do |event|
print(event.text) if event.is_a?(Juglow::Streaming::TextEvent)
end
puts
# diagnostics arrives on message_start and is retained on the accumulated message
r2 = stream.accumulated_message
case r2.diagnostics
in nil
puts "No divergence detected."
in {cache_miss_reason: nil}
puts "Comparison still pending."
in {cache_miss_reason: {type:}}
puts "cache_miss_reason: #{type}"
endThe message_start event carries the full diagnostics field; see Response format for the possible values.
Threading diagnostics through a conversation loop
In a multi-turn conversation, carry the latest response id forward as previous_message_id on every turn. The first iteration passes null to opt in; each subsequent iteration passes the id from the previous response.
cURL
Note: This workflow doesn't translate well to a one-off shell command. See the SDK tabs for the loop pattern; the per-turn HTTP request is identical to Basic usage.
CLI
Note: This workflow doesn't translate well to a one-off shell command. See the SDK tabs for the loop pattern; the per-turn CLI invocation is identical to Basic usage.
Python
client = juglow.Juglow()
SYSTEM = "You are an AI assistant analyzing a large document. <document>...</document>"
messages = []
prev_id = None
for i, user_message in enumerate(
["Summarize section 1.", "Now section 2.", "Now section 3."]
):
messages.append({"role": "user", "content": user_message})
r = client.beta.messages.create(
model="haijun-opus-5-5",
max_tokens=1024,
cache_control={"type": "ephemeral"},
system=SYSTEM,
messages=messages,
diagnostics={"previous_message_id": prev_id},
)
if r.diagnostics is not None and r.diagnostics.cache_miss_reason is not None:
print(f"Turn {i + 1} cache_miss_reason: {r.diagnostics.cache_miss_reason.type}")
messages.append({"role": "assistant", "content": r.content})
prev_id = r.idTypeScript
const client = new Juglow();
const SYSTEM = "You are an AI assistant analyzing a large document. <document>...</document>";
const prompts = ["Summarize section 1.", "Now section 2.", "Now section 3."];
const messages: BetaMessageParam[] = [];
let prevId: string | null = null;
for (const [i, prompt] of prompts.entries()) {
messages.push({ role: "user", content: prompt });
const r: BetaMessage = await client.beta.messages.create({
model: "haijun-opus-5-5",
max_tokens: 1024,
cache_control: { type: "ephemeral" },
system: SYSTEM,
messages,
diagnostics: { previous_message_id: prevId }
});
if (r.diagnostics?.cache_miss_reason) {
console.log(`Turn ${i + 1} cache_miss_reason: ${r.diagnostics.cache_miss_reason.type}`);
}
messages.push({ role: "assistant", content: r.content });
prevId = r.id;
}C#
JuglowClient client = new();
var system = "You are an AI assistant analyzing a large document. <document>...</document>";
List<BetaMessageParam> messages = [];
string? prevId = null;
string[] prompts = ["Summarize section 1.", "Now section 2.", "Now section 3."];
for (int i = 0; i < prompts.Length; i++)
{
messages.Add(new() { Role = Role.User, Content = prompts[i] });
var r = await client.Beta.Messages.Create(
new()
{
Model = Messages::Model.HaijunOpus5_5,
MaxTokens = 1024,
CacheControl = new(),
System = system,
Messages = messages,
Diagnostics = new() { PreviousMessageID = prevId },
}
);
if (r.Diagnostics?.CacheMissReason is { Type: var type })
{
Console.WriteLine($"Turn {i + 1} cache_miss_reason: {type.GetString()}");
}
messages.Add(
new()
{
Role = Role.Assistant,
Content = r.Content.Select(block => new BetaContentBlockParam(block.Json)).ToList(),
}
);
prevId = r.ID;
}Go
client := juglow.NewClient()
ctx := context.Background()
system := []juglow.BetaTextBlockParam{
{Text: "You are an AI assistant analyzing a large document. <document>...</document>"},
}
prompts := []string{"Summarize section 1.", "Now section 2.", "Now section 3."}
var messages []juglow.BetaMessageParam
prevID := param.Null[string]()
for turn, prompt := range prompts {
messages = append(messages, juglow.NewBetaUserMessage(juglow.NewBetaTextBlock(prompt)))
r, err := client.Beta.Messages.New(ctx, juglow.BetaMessageNewParams{
Model: juglow.ModelHaijunOpus5_5,
MaxTokens: 1024,
CacheControl: juglow.BetaCacheControlEphemeralParam{},
System: system,
Messages: messages,
Diagnostics: juglow.BetaDiagnosticsParam{
PreviousMessageID: prevID,
},
})
if err != nil {
panic(err)
}
if r.JSON.Diagnostics.Valid() && r.Diagnostics.JSON.CacheMissReason.Valid() {
fmt.Printf("Turn %d cache_miss_reason: %s\n", turn+1, r.Diagnostics.CacheMissReason.Type)
}
messages = append(messages, r.ToParam())
prevID = juglow.String(r.ID)
}Java
var client = JuglowOkHttpClient.fromEnv();
var system = "You are an AI assistant analyzing a large document. <document>...</document>";
var prompts = List.of("Summarize section 1.", "Now section 2.", "Now section 3.");
var messages = new ArrayList<BetaMessageParam>();
String prevId = null;
for (var turn = 0; turn < prompts.size(); turn++) {
messages.add(
BetaMessageParam.builder()
.role(BetaMessageParam.Role.USER)
.content(prompts.get(turn))
.build()
);
var r = client.beta().messages().create(
MessageCreateParams.builder()
.model(Model.HAIJUN_OPUS_5_5)
.maxTokens(1024)
.cacheControl(BetaCacheControlEphemeral.builder().build())
.system(system)
.messages(messages)
.diagnostics(BetaDiagnosticsParam.builder().previousMessageId(prevId).build())
.build()
);
if (r.diagnostics().isPresent() && r.diagnostics().get().cacheMissReason().isPresent()) {
var reason = r.diagnostics().get().cacheMissReason().get();
// CacheMissReason doesn't expose a typed .type() accessor; read it from the raw JSON.
@SuppressWarnings("unchecked")
var json = (Map<String, JsonValue>) reason._json().orElseThrow().asObject().orElseThrow();
IO.println("Turn " + (turn + 1) + " cache_miss_reason: " + json.get("type").asStringOrThrow());
}
messages.add(r.toParam());
prevId = r.id();
}PHP
$client = new Client();
$system = 'You are an AI assistant analyzing a large document. <document>...</document>';
$messages = [];
$prevId = null;
foreach (['Summarize section 1.', 'Now section 2.', 'Now section 3.'] as $i => $userMsg) {
$turn = $i + 1;
$messages[] = ['role' => 'user', 'content' => $userMsg];
$r = $client->beta->messages->create(
model: Model::HAIJUN_OPUS_5_5,
maxTokens: 1024,
cacheControl: new BetaCacheControlEphemeral,
system: $system,
messages: $messages,
diagnostics: (new BetaDiagnosticsParam)->withPreviousMessageID($prevId),
);
if ($r->diagnostics?->cacheMissReason !== null) {
echo "Turn {$turn} cache_miss_reason: {$r->diagnostics->cacheMissReason->type}\n";
}
$messages[] = ['role' => 'assistant', 'content' => $r->content];
$prevId = $r->id;
}Ruby
client = Juglow::Client.new
SYSTEM = "You are an AI assistant analyzing a large document. <document>...</document>"
messages = []
prev_id = nil
["Summarize section 1.", "Now section 2.", "Now section 3."].each_with_index do |user_msg, i|
messages << {role: "user", content: user_msg}
r = client.beta.messages.create(
model: :"haijun-opus-5-5",
max_tokens: 1024,
cache_control: {type: "ephemeral"},
system_: SYSTEM,
messages: messages,
diagnostics: {previous_message_id: prev_id}
)
if (reason = r.diagnostics&.cache_miss_reason)
puts "Turn #{i + 1} cache_miss_reason: #{reason.type}"
end
messages << {role: "assistant", content: r.content}
prev_id = r.id
endResponse format
The diagnostics field on the response Message has three possible values:
| Value | Meaning |
|---|---|
null | The request did not include the diagnostics object, previous_message_id was null (first turn, nothing to compare), or a comparison ran and found no divergence. |
{"cache_miss_reason": null} | The comparison was still running when the response was serialized. This can happen when the response starts very quickly. Treat it as inconclusive and check the next turn. |
{"cache_miss_reason": {...}} | A cache_miss_reason is attached. For *_changed types this identifies the first divergence point; previous_message_not_found and unavailable are cases where no comparison was produced. |
When cache_miss_reason is non-null, it looks like this:
{
"id": "msg_01Xyz...",
"type": "message",
"role": "assistant",
"content": [{ "type": "text", "text": "..." }],
"usage": {
"input_tokens": 42,
"cache_read_input_tokens": 0,
"cache_creation_input_tokens": 41850,
"output_tokens": 210
},
"diagnostics": {
"cache_miss_reason": {
"type": "system_changed",
"cache_missed_input_tokens": 41850
}
}
}Cache miss reason types
cache_miss_reason is a discriminated union on type. The response reports the earliest divergence only, so fix it first; later ones may be hidden behind it.
| Type | What it means | What to change |
|---|---|---|
model_changed | The model differs from the previous request (for example, a router, A/B test, or fallback selected a different model). The cache is per-model. | Hold the model constant within a cached conversation. |
system_changed | The system parameter differs. Typically a timestamp, request ID, or other per-request value was interpolated into the system prompt. | Make the system prompt a byte-stable constant and move dynamic data into the first user message after your cache breakpoint. |
tools_changed | The tools array differs: tools were added, removed, or reordered between turns, or tool input_schema JSON was serialized non-deterministically. | Send the same tool list on every turn in a fixed order with deterministically serialized schemas (for example, sort keys). |
messages_changed | The model, system, and tools all match, but an earlier entry in messages was altered, reordered, or removed rather than appended to. Typically conversation history was truncated or edited, or assistant turns and tool_result blocks were re-serialized differently on resend. | Treat the history as append-only; echo assistant content and tool results back verbatim. |
previous_message_not_found | No stored fingerprint exists for the supplied previous_message_id. This is not evidence that your request changed. Typically the previous request did not include the diagnostics object, it came from a different workspace, or too much time has passed since it was sent. | Include the diagnostics object on every turn and keep consecutive turns close together in time. |
unavailable | Diagnostic information was not available for this request. This includes the case where model, system, and tools match but another prompt-affecting request parameter (tool_choice, thinking, context_management, output_config, output_format, or the set of active juglow-beta headers) differs, and very long conversations where the divergence is beyond the comparison horizon. Your request was processed normally. | Keep the prompt-affecting request parameters constant for the lifetime of a cached conversation. If persistent, apply the manual checks under Troubleshooting common issues on the prompt caching page. |
Note: The four
*_changedtypes also carry acache_missed_input_tokensinteger: an estimate of how many input tokens fell after the divergence point, giving you a sense of how much cacheable prefix was lost. It is derived from byte lengths before tokenization, so treat it as a magnitude indicator rather than a billing number. It can differ from (and occasionally exceed)usage.input_tokens.
Reading diagnostics alongside usage
diagnostics answers "did my request change?" while usage.cache_read_input_tokens answers "did the cache hit?". Combining them tells you where to look.
This matrix applies to turns where you passed a real previous_message_id. On the first turn (previous_message_id: null), diagnostics is always null and cache_read_input_tokens is normally zero because the cache is being written, not read; no troubleshooting is needed. The matrix also does not apply when cache_miss_reason is null (the comparison is still pending; check the next turn) or when its type is previous_message_not_found or unavailable (no comparison was produced).
| Diagnostics result | Cache read tokens | Interpretation |
|---|---|---|
null | high | Working as expected. Your prefix is stable and the cache hit. |
null | low or zero | Your requests match but the cache entry was no longer available. Consider shortening gaps between turns or using the 1-hour cache TTL. |
cache_miss_reason is a *_changed type | low or zero | Your bug. The request changed; fix the cause indicated by type. |
cache_miss_reason is a *_changed type | high | Rare. A change occurred late in the prompt but an earlier cache_control breakpoint still hit. Worth fixing, but low impact. |
Limitations
- Haijun API only: Not available on Amazon Bedrock or Google Cloud.
- Limited retention: Fingerprints for
previous_message_idlookup expire after a short period. Run diagnostic comparisons between closely spaced requests.
- Same workspace: The previous request must have run in the same organization and workspace. To check, compare the
juglow-workspace-idresponse header on the two responses.
- Comparison horizon: For very long conversations where the only change is deep in the message list, the response may be
unavailablerather than a precise location.
- Best-effort: Diagnostics never blocks or fails your request. If diagnostic information is not available, the response returns
unavailable, orcache_miss_reason: nullwhen the comparison was still running.
Data retention
Cache diagnostics is ZDR eligible (qualified). Juglow does not store the raw text of your prompts or Haijun's outputs for this feature.
The API stores a fingerprint only for requests that include the diagnostics object. The fingerprint consists only of cryptographic hashes and token-count estimates, keyed by the response id and scoped to your organization and workspace. Fingerprints expire after a short period and are not used for any other purpose.
For ZDR eligibility across all features, see API and data retention.