fix: preserve thinking block signatures and fix compaction headroom asymmetry

Two compounding bugs caused sessions to crash with 'thinking blocks cannot
be modified' when compaction fired for models with extended thinking:

1. toModelMessages() stripped providerMetadata (including cryptographic
   signatures) from message parts when the current model differed from the
   original. Anthropic's API requires signatures to be byte-identical.
   Fix: always pass providerMetadata through — the API handles filtering.

2. isOverflow() used an asymmetric buffer when limit.input was set
   (capped at 20K via COMPACTION_BUFFER) vs the full maxOutputTokens on
   the non-input path. This caused compaction to trigger too late.
   Fix: use maxOutputTokens (capped at 32K) for both paths. Also fixed
   the non-input path to respect config.compaction.reserved.

Author: gnadaban

packages/opencode/src/session/message-v2.ts

@@ -688,7 +688,12 @@ export const toModelMessagesEffect = Effect.fnUntraced(function* (
     }
 
     if (msg.info.role === "assistant") {
-      const differentModel = `${model.providerID}/${model.id}` !== `${msg.info.providerID}/${msg.info.modelID}`
+      // Only strip provider metadata when crossing provider boundaries (e.g. Anthropic → OpenAI).
+      // Metadata is provider-namespaced so a different provider ignores unknown keys, but
+      // passing it is still unnecessary. Within the same provider (e.g. compaction using a
+      // different model variant), metadata MUST be preserved — Anthropic requires thinking
+      // block signatures to be byte-identical on replay.
+      const differentProvider = model.providerID !== msg.info.providerID
       const media: Array<{ mime: string; url: string }> = []
 
       if (
@@ -710,7 +715,7 @@ export const toModelMessagesEffect = Effect.fnUntraced(function* (
           assistantMessage.parts.push({
             type: "text",
             text: part.text,
-            ...(differentModel ? {} : { providerMetadata: part.metadata }),
+            ...(differentProvider ? {} : { providerMetadata: part.metadata }),
           })
         if (part.type === "step-start")
           assistantMessage.parts.push({
@@ -746,7 +751,7 @@ export const toModelMessagesEffect = Effect.fnUntraced(function* (
               input: part.state.input,
               output,
               ...(part.metadata?.providerExecuted ? { providerExecuted: true } : {}),
-              ...(differentModel ? {} : { callProviderMetadata: providerMeta(part.metadata) }),
+              ...(differentProvider ? {} : { callProviderMetadata: providerMeta(part.metadata) }),
             })
           }
           if (part.state.status === "error") {
@@ -759,7 +764,7 @@ export const toModelMessagesEffect = Effect.fnUntraced(function* (
                 input: part.state.input,
                 output,
                 ...(part.metadata?.providerExecuted ? { providerExecuted: true } : {}),
-                ...(differentModel ? {} : { callProviderMetadata: providerMeta(part.metadata) }),
+                ...(differentProvider ? {} : { callProviderMetadata: providerMeta(part.metadata) }),
               })
             } else {
               assistantMessage.parts.push({
@@ -769,7 +774,7 @@ export const toModelMessagesEffect = Effect.fnUntraced(function* (
                 input: part.state.input,
                 errorText: part.state.error,
                 ...(part.metadata?.providerExecuted ? { providerExecuted: true } : {}),
-                ...(differentModel ? {} : { callProviderMetadata: providerMeta(part.metadata) }),
+                ...(differentProvider ? {} : { callProviderMetadata: providerMeta(part.metadata) }),
               })
             }
           }
@@ -783,14 +788,14 @@ export const toModelMessagesEffect = Effect.fnUntraced(function* (
               input: part.state.input,
               errorText: "[Tool execution was interrupted]",
               ...(part.metadata?.providerExecuted ? { providerExecuted: true } : {}),
-              ...(differentModel ? {} : { callProviderMetadata: providerMeta(part.metadata) }),
+              ...(differentProvider ? {} : { callProviderMetadata: providerMeta(part.metadata) }),
             })
         }
         if (part.type === "reasoning") {
           assistantMessage.parts.push({
             type: "reasoning",
             text: part.text,
-            ...(differentModel ? {} : { providerMetadata: part.metadata }),
+            ...(differentProvider ? {} : { providerMetadata: part.metadata }),
           })
         }
       }

packages/opencode/src/session/overflow.ts

@@ -3,17 +3,18 @@ import type { Provider } from "@/provider"
 import { ProviderTransform } from "@/provider"
 import type { MessageV2 } from "./message-v2"
 
-const COMPACTION_BUFFER = 20_000
-
 export function usable(input: { cfg: Config.Info; model: Provider.Model }) {
   const context = input.model.limit.context
   if (context === 0) return 0
 
-  const reserved =
-    input.cfg.compaction?.reserved ?? Math.min(COMPACTION_BUFFER, ProviderTransform.maxOutputTokens(input.model))
+  // Reserve headroom so compaction triggers before the next turn overflows.
+  // maxOutputTokens() is capped at 32K (OUTPUT_TOKEN_MAX) regardless of the
+  // model's raw output limit, so this is never excessively aggressive.
+  // Users can override via config.compaction.reserved if needed (#12924).
+  const reserved = input.cfg.compaction?.reserved ?? ProviderTransform.maxOutputTokens(input.model)
   return input.model.limit.input
     ? Math.max(0, input.model.limit.input - reserved)
-    : Math.max(0, context - ProviderTransform.maxOutputTokens(input.model))
+    : Math.max(0, context - reserved)
 }
 
 export function isOverflow(input: { cfg: Config.Info; tokens: MessageV2.Assistant["tokens"]; model: Provider.Model }) {

packages/opencode/test/session/compaction.test.ts

@@ -418,20 +418,20 @@ describe("session.compaction.isOverflow", () => {
     ),
   )
 
-  // ─── Bug reproduction tests ───────────────────────────────────────────
-  // These tests demonstrate that when limit.input is set, isOverflow()
-  // does not subtract any headroom for the next model response. This means
-  // compaction only triggers AFTER we've already consumed the full input
-  // budget, leaving zero room for the next API call's output tokens.
+  // ─── Headroom reservation tests ──────────────────────────────────────
+  // These tests verify that when limit.input is set, isOverflow()
+  // correctly reserves headroom (maxOutputTokens, capped at 32K) so
+  // compaction triggers before the next API call overflows.
   //
-  // Compare: without limit.input, usable = context - output (reserves space).
-  // With limit.input, usable = limit.input (reserves nothing).
+  // Previously (bug), the limit.input path only subtracted a 20K buffer
+  // while the non-input path subtracted the full maxOutputTokens — an
+  // asymmetry that let sessions grow ~12K tokens too large before compacting.
   //
   // Related issues: #10634, #8089, #11086, #12621
   // Open PRs: #6875, #12924
 
   it.live(
-    "BUG: no headroom when limit.input is set — compaction should trigger near boundary but does not",
+    "no headroom when limit.input is set — compaction should trigger near boundary",
     provideTmpdirInstance(() =>
       Effect.gen(function* () {
         const compact = yield* SessionCompaction.Service
@@ -457,7 +457,7 @@ describe("session.compaction.isOverflow", () => {
   )
 
   it.live(
-    "BUG: without limit.input, same token count correctly triggers compaction",
+    "without limit.input, same token count correctly triggers compaction",
     provideTmpdirInstance(() =>
       Effect.gen(function* () {
         const compact = yield* SessionCompaction.Service
@@ -477,15 +477,15 @@ describe("session.compaction.isOverflow", () => {
   )
 
   it.live(
-    "BUG: asymmetry — limit.input model allows 30K more usage before compaction than equivalent model without it",
+    "asymmetry — limit.input model does not allow more usage than equivalent model without it",
     provideTmpdirInstance(() =>
       Effect.gen(function* () {
         const compact = yield* SessionCompaction.Service
         // Two models with identical context/output limits, differing only in limit.input
         const withInputLimit = createModel({ context: 200_000, input: 200_000, output: 32_000 })
         const withoutInputLimit = createModel({ context: 200_000, output: 32_000 })
 
-        // 170K total tokens — well above context-output (168K) but below input limit (200K)
+        // 181K total tokens — above usable (context - maxOutput = 168K)
         const tokens = { input: 166_000, output: 10_000, reasoning: 0, cache: { read: 5_000, write: 0 } }
 
         const withLimit = yield* compact.isOverflow({ tokens, model: withInputLimit })