Compaction produces empty summary for Kimi K3-256K since v1.18.15 — conversation history silently dropped

Summary

Since v1.18.15, compaction produces empty summaries for Kimi K3-256K (kimi-for-coding/k3-256k): the compaction assistant message contains only a reasoning part and no text part (0 text parts, ~40-60 output tokens), then finishes with reason: stop. The conversation history is then replaced by an empty summary, silently dropping all context.

Other models (gpt-5.x, k2p7, deepseek-v4) compact normally on the same session — this is specific to k3-256k (a reasoning model).

Regression Window

• v1.18.13 / v1.18.14: compaction works (structured output summary, ## Objective text part present)
• v1.18.15: compaction starts degrading (summary text becomes non-summary content, or empty)
• v1.18.16: fully broken — output=41~60, 0 text parts

The compaction.ts file is identical between 1.18.15 and 1.18.16, and identical between 1.18.13 and 1.18.14. The change was introduced in v1.18.15 ("Repeated compaction now keeps earlier tool-call history in summaries instead of dropping orphaned results").

Root Cause (from code diff v1.18.14 → v1.18.15)

packages/opencode/src/session/compaction.ts, in SessionCompaction.process:

Before (v1.18.14):

const modelMessages = yield* MessageV2.toModelMessagesEffect(msgs, model, {
  stripMedia: true,
  toolOutputMaxChars: TOOL_OUTPUT_MAX_CHARS,
})
...
messages: [
  ...modelMessages,  // structured history: system/user/assistant roles + tool result blocks
  { role: "user", content: [{ type: "text", text: nextPrompt }] },  // prompt as separate user msg
]

After (v1.18.15+):

const conversation = msgs.map(serialize).filter(Boolean).join("\n\n")  // NEW: flatten to plain text
...
messages: [{
  role: "user",
  content: [{ type: "text", text: [nextPrompt, "The following is the conversation history:", conversation].join("\n\n") }]
}]

A new serialize() helper flattens the whole history into one big plain-text string ([User]: ..., [Assistant]: ..., [Assistant tool call]: ..., [Tool result]: ...) and merges the compaction prompt into a single user message with no role structure.

Why k3-256k breaks

k3-256k is a reasoning model. Given a huge wall of unstructured plain text (11万+ tokens in the failing case), it enters reasoning mode and starts analyzing the content as if it were a coding task instead of summarizing the conversation — the reasoning part in the failing compaction says e.g.:

"The first occurrence (with mapped || preceding) was in classifyPostgresPayment; the second in classifyPaymentReversal (memory)..."

Then it emits reason: stop without ever producing a summary text part. opencode marks the message summary: true, treats compaction as complete, and swaps in an empty summary — all prior context is lost. Stronger-following models (gpt-5.x, k2p7, deepseek) still produce ## Objective summaries despite the format change, which is why this looks model-specific.

Repro

1. Use kimi-for-coding/k3-256k (any variant) in a long session.
2. Trigger compaction (auto at ~131k tokens, or manually: POST /session/{id}/summarize with {"providerID":"kimi-for-coding","modelID":"k3-256k"}).
3. Compaction assistant message has reasoning part only, 0 text parts, output≈40-60.
4. History is replaced with empty summary — context lost.

Verified on v1.18.16 both via auto-compaction and manual /summarize on a 42万-token session.

Suggested Fix

Restore the structured message format for the compaction prompt (use MessageV2.toModelMessagesEffect output as separate role-typed messages, with nextPrompt as a standalone trailing user message), or keep serialize() only as a fallback for models that cannot consume structured tool results. At minimum, detect empty summaries (no text part) and fail compaction instead of silently discarding history.

Environment

• opencode v1.18.16 (also affected: v1.18.15)
• macOS arm64
• provider: kimi-for-coding / k3-256k