压缩与补丁文本：压的时候也要命中缓存

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  "messages": [
    {
      "role": "user",
      "content": [
        {
          "type": "text",
          "text": "Read packages/compaction/compaction-basic/src/summarizer.ts and packages/compaction/compaction-basic/src/region.ts. Explain in five bullets how a compaction request is assembled and how its result lands back in the session."
        },
        {
          "type": "text",
          "text": "<system-reminder>\nThe following workspace instructions may be relevant to your work. Use them as guidance when applicable. More specific instructions take precedence over broader ones. They do not override system, developer, or direct user instructions.\n\nInstructions from: AGENTS.md\n\n# Workspace notes\n\n- TypeScript monorepo: every package lives under `packages/<group>/<name>/src`.\n- This checkout is read-only. Do not try to edit or write files.\n- When you explain code, cite `path:line` for every claim.\n\n</system-reminder>"
        },
        {
          "type": "text",
          "text": "Current runtime context. This snapshot supersedes earlier runtime-context snapshots.\n\nCurrent working directory: \"/tmp/dsh-lab/compaction/ws\"."
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      "content": [
        {
          "type": "thinking",
          "thinking": "",
          "signature": "62a048f7-5ea2-4111-b43f-825d3e5721d5"
        },
        {
          "type": "text",
          "text": "I'll read both files."
        },
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          "type": "tool_use",
          "id": "call_00_ET_gb6NwxQvXf27RCVj6OTi5910",
          "name": "read",
          "input": {
            "file_path": "packages/compaction/compaction-basic/src/summarizer.ts"
          }
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          "type": "tool_use",
          "id": "call_01_ET_i32zCYNMeST2K4IoK0UW5515",
          "name": "read",
          "input": {
            "file_path": "packages/compaction/compaction-basic/src/region.ts"
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      "content": [
        {
          "type": "tool_result",
          "tool_use_id": "call_00_ET_gb6NwxQvXf27RCVj6OTi5910",
          "content": [
            {
              "type": "text",
              "text": "<path>/tmp/dsh-lab/compaction/ws/packages/compaction/compaction-basic/src/summarizer.ts</path>\n<type>file</type>\n<content>\n1: /**\n2:  * Default one-shot summarization and durable checkpoint framing.\n3:  *\n4:  * @module @deepseek-ai/dsh-compaction-basic/summarizer\n5:  */\n6: \n7: import type { Context } from '@deepseek-ai/cordis'\n8: import { contentHasImage, BlockAssembler, LlmError } from '@deepseek-ai/dsh-llm'\n9: import { deepFreeze } from '@deepseek-ai/dsh-util-values'\n10: import type {\n11:   ContentBlock, FinishReason, GenerateOptions, Message, RequestMessage, TokenUsage, ToolSchema,\n12: } from '@deepseek-ai/dsh-llm'\n13: import type { Agent } from '@deepseek-ai/dsh-agent'\n14: \n15: interface SummaryConfig {\n16:   readonly summarizationProvider: string\n17:   readonly summarizationModel: string\n18:   readonly maxTokens: number\n19: }\n20: \n21: /** Tags wrapping the structured summary inside the landed checkpoint node. */\n22: const SUMMARY_OPEN_TAG = '<compacted-summary>'\n23: const SUMMARY_CLOSE_TAG = '</compacted-summary>'\n24: \n25: /**\n26:  * The summarization directive, delivered as the FINAL user message after the\n27:  * replayed conversation rather than as a distinct summarizer system prompt.\n28:  * Keeping the conversation's own system prompt, tools, and message prefix in\n29:  * front of it makes the auxiliary call a genuine prefix of the last routed\n30:  * request, so the provider's KV cache is reused instead of invalidated.\n31:  */\n32: const COMPACTION_INSTRUCTION = [\n33:   'You are now acting as a compaction engine for this AI coding assistant. Condense the conversation ABOVE into a structured checkpoint that lets another model resume the work with no loss of essential context.',\n34:   '',\n35:   'Output EXACTLY the Markdown structure below: keep every section, in order. Use terse bullets, not prose paragraphs. Write \"(none)\" for an empty section — never drop a section.',\n36:   '',\n37:   '## Primary Request and Intent',\n38:   \"- [the user's original and evolving goals; quote verbatim where the exact wording matters]\",\n39:   '',\n40:   '## Key Technical Concepts',\n41:   '- [technologies, frameworks, patterns, and conventions in play]',\n42:   '',\n43:   '## Files and Code',\n44:   '- [exact path: why it matters, key changes or snippets]',\n45:   '',\n46:   '## Errors and Fixes',\n47:   '- [error: how it was resolved, plus any related user feedback]',\n48:   '',\n49:   '## Pending Jobs',\n50:   '- [explicitly requested work not yet completed]',\n51:   '',\n52:   '## Current Work',\n53:   '- [precisely what was in progress at this checkpoint]',\n54:   '',\n55:   '## Next Step',\n56:   '- [the single next action, directly in line with the most recent request, or \"(none)\"]',\n57:   '',\n58:   '## Critical Context',\n59:   '- [decisions and their rationale, constraints, user preferences, open questions, data needed to continue]',\n60:   '',\n61:   'Rules:',\n62:   '- Write concise English engineering prose. Preserve exact file paths, commands, error strings, identifiers, numeric values, function signatures, and syntax fragments.',\n63:   '- Capture user feedback and explicit instructions faithfully, especially corrections.',\n64:   '- Do NOT mention this summarization request or that the context was compacted.',\n65:   '- Output only the checkpoint text: do not call any tool or take any other action.',\n66:   `- If the conversation already contains a ${SUMMARY_OPEN_TAG} block, it is a PRIOR checkpoint. Do not copy it forward verbatim: preserve still-true facts, drop stale ones, and merge newer information into a single consolidated summary under the same structure.`,\n67: ].join('\\n')\n68: \n69: /** Framing that makes the replacement user message established context. */\n70: const CHECKPOINT_PREAMBLE =\n71:   'This is an automatically generated checkpoint condensing an earlier span of the conversation to free up context. Treat the captured context as established background and build on it without restating it. Continue the task directly from the messages that follow, without acknowledging this checkpoint.'\n72: \n73: /**\n74:  * The replayed conversation sur\n\n[... tool result middle pruned ...]\n\nor | undefined {\n198:   switch (finish.kind) {\n199:     case 'error':\n200:     case 'aborted': {\n201:       return new LlmError(finish.failure.message, finish.failure.code, finish.failure)\n202:     }\n203:     case 'max-tokens': {\n204:       const error = new Error('summarization truncated at the token cap (incomplete checkpoint)') as Error & { code?: string }\n205:       error.code = 'MAX_TOKENS'\n206:       return error\n207:     }\n208:     default:\n209:       return undefined\n210:   }\n211: }\n212: \n213: /** Reject visual output and keep only text before synthesizing a user message. */\n214: function summaryText(\n215:   blocks: readonly ContentBlock[],\n216: ): Array<Extract<ContentBlock, { type: 'text' }>> {\n217:   if (contentHasImage(blocks)) {\n218:     throw new LlmError('compaction summary cannot contain image output', 'UNSUPPORTED_CONTENT')\n219:   }\n220:   return blocks.filter((block): block is Extract<ContentBlock, { type: 'text' }> => block.type === 'text')\n221: }\n\n(End of file - total 221 lines)\n</content>"
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          "content": [
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              "type": "text",
              "text": "<path>/tmp/dsh-lab/compaction/ws/packages/compaction/compaction-basic/src/region.ts</path>\n<type>file</type>\n<content>\n1: /**\n2:  * Surface retention selection and the shared log-recorded compaction\n3:  * transaction for automatic open-turn and manual idle-session compaction.\n4:  *\n5:  * @module @deepseek-ai/dsh-compaction-basic/region\n6:  */\n7: \n8: import { randomUUID } from 'node:crypto'\n9: import { isDeepStrictEqual } from 'node:util'\n10: import {\n11:   CompactionId,\n12:   ManualCompactionError,\n13:   compactCheckpointSource,\n14:   toolPairingBalancedAfter,\n15:   toolPairingBalancedBefore,\n16: } from '@deepseek-ai/dsh-compaction'\n17: import type { CompactionResult } from '@deepseek-ai/dsh-compaction'\n18: import type { CommandId } from '@deepseek-ai/dsh-commands/brand'\n19: import { createUserMessage, errorChain } from '@deepseek-ai/dsh-llm'\n20: import type { Message, UserMessage } from '@deepseek-ai/dsh-llm'\n21: import type { TokenMeasurement, TokenMeter } from '@deepseek-ai/dsh-token-meter'\n22: import { SessionSeq, type Session, type SessionEvent } from '@deepseek-ai/dsh-session'\n23: import type { Agent } from '@deepseek-ai/dsh-agent'\n24: import { frameSummary } from './summarizer.ts'\n25: import type { SummarizationInput, SummaryResult } from './summarizer.ts'\n26: interface RegionDependencies {\n27:   readonly meter: TokenMeter\n28:   summarize(input: SummarizationInput, agent: Agent, signal?: AbortSignal): Promise<SummaryResult>\n29:   recover(error: unknown, agent: Agent, sourceEventSeqs: readonly SessionSeq[], signal?: AbortSignal): boolean\n30: }\n31: \n32: /** One validated inclusive span of current surface positions. */\n33: interface SurfaceSelection {\n34:   readonly start: SessionSeq\n35:   readonly end: SessionSeq\n36:   readonly startIdx: number\n37:   readonly endIdx: number\n38:   readonly shadowedSeqs: readonly SessionSeq[]\n39: }\n40: \n41: /** A selection with its priced snapshot and the replay input built from it. */\n42: interface PreparedCompaction extends SurfaceSelection {\n43:   readonly measurement: TokenMeasurement\n44:   readonly selectedNodes: TokenMeasurement['nodes']\n45:   readonly shadowedTokenCount: number\n46:   /** Route-priced total of the selected span; the shrink comparison's unit. */\n47:   readonly shadowedRouteTokenCount: number\n48:   readonly input: SummarizationInput\n49: }\n50: \n51: type SummarizedCompaction = PreparedCompaction & SummaryResult & {\n52:   readonly checkpointMessage: UserMessage\n53: }\n54: \n55: interface CompactionTransactionOptions {\n56:   /** `current-turn` derives a numbered owner; `null` writes a standalone bracket. */\n57:   readonly owner: 'current-turn' | null\n58:   /** Surface relationship that must survive asynchronous summarization. */\n59:   readonly stability: 'whole-surface' | 'selected-span'\n60:   /** Optional durability checkpoint after a successfully closed bracket. */\n61:   readonly flush?: () => Promise<void>\n62:   /** Manual command that initiated this transaction, when present. */\n63:   readonly sourceCommandId?: CommandId\n64: }\n65: \n66: interface CompactionEntryState {\n67:   readonly openTurn: number | null\n68:   readonly unmatchedCompactionStart: SessionEvent<'compaction/start'> | undefined\n69:   readonly latestEndSeedSeq: SessionSeq | undefined\n70: }\n71: \n72: /**\n73:  * Rejects a summary whose replacement boundaries are no longer the ones it was\n74:  * built from, distinguished from summarizer and shrink failures so a manual\n75:  * caller can report the two causes differently.\n76:  */\n77: class SurfaceChangedError extends Error {}\n78: \n79: /** Whether the summary may still replace the span it was built from. */\n80: type StabilityCheck = (\n81:   dependencies: RegionDependencies,\n82:   session: Session,\n83:   prepared: PreparedCompaction,\n84: ) => void\n85: \n86: /** Failure captured after `compaction/start` has committed. */\n87: interface TransactionFailure {\n88:   readonly error: unknown\n89:   readonly stage: 'summary' | 'commit'\n90: }\n91: \n92: /**\n93:  * The `system/message` holding surface node 0, or `undefined` when another\n94:  * message-producing event starts th\n\n[... tool result middle pruned ...]\n\nnst event = session.eventAt(SessionSeq(seq))!\n576:     if (latestEndSeedSeq === undefined && event.type === 'session/end-seed') {\n577:       latestEndSeedSeq = event.seq\n578:     }\n579:     if (!compactionEntryStateKnown) {\n580:       if (event.type === 'compaction/start') {\n581:         unmatchedCompactionStart = event\n582:         compactionEntryStateKnown = true\n583:       } else if (event.type === 'compaction/end') {\n584:         compactionEntryStateKnown = true\n585:       }\n586:     }\n587:     if (!openTurnStateKnown) {\n588:       if (event.type === 'turn/start') {\n589:         openTurn = event.data.turn\n590:         openTurnStateKnown = true\n591:       } else if (event.type === 'turn/end') {\n592:         openTurnStateKnown = true\n593:       }\n594:     }\n595:     if (openTurnStateKnown\n596:       && compactionEntryStateKnown\n597:       && latestEndSeedSeq !== undefined) break\n598:   }\n599:   return { openTurn, unmatchedCompactionStart, latestEndSeedSeq }\n600: }\n\n(End of file - total 600 lines)\n</content>"
            }
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          "is_error": false
        }
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      "role": "assistant",
      "content": [
        {
          "type": "thinking",
          "thinking": "Let me write five bullets explaining assembly and landing back, with citations.\n\nKey claims:\n\n1. Range selection: selectCompactableRange picks span retaining tail (region.ts:117-155), system head excluded (region.ts:131), balance check (region.ts:143-147).\n2. Validation + prepare: validateSurfaceRegion checks start/end exist, ordered, tool pairing balanced (region.ts:337-358); prepareCompaction prices nodes via meter (region.ts:361-384) and builds summarization input (region.ts:382).\n3. Input assembly: buildSummarizationInput puts system head message + region messages (region.ts:544-563); summarizer adds instruction as final user message (summarizer.ts:145-151), options with toolHistory, tools, purpose 'compaction', sessionId, maxTokens, signal (summarizer.ts:152-162); key resolution priority (summarizer.ts:127-142).\n4. Result: streamed chunks assembled via BlockAssembler (summarizer.ts:163), finish errors fail closed, max-tokens error (summarizer.ts:197-211), text-only projection rejecting images (summarizer.ts:214-220), empty summary error (summarizer.ts:169-171), usage returned (summarizer.ts:172-180).\n5. Landing: frameSummary wraps with preamble + tags (summarizer.ts:188-194); summarizeCompaction creates user message with compactCheckpointSource (region.ts:410-413), shrink check vs route token count (region.ts:417-422); commitCompactionBody appends compaction/summary event then user/message with surfaceOp replace (region.ts:491-509); compaction/end (region.ts:237-239) and result completion (region.ts:525-530).\n\nCould also mention transaction bracket / locking as part of assembly (compaction/start as lock region.ts:204-210).\n\nFive bullets — combine. Let me write concisely but with citations.",
          "signature": "4e70847f-72e2-498c-a3f7-0e7e2734c438"
        },
        {
          "type": "text",
          "text": "Both files read. Here's how a compaction request is built and how its outcome returns to the session.\n\n- **Span selection & validation (the \"what to compact\" decision).** `selectCompactableRange` walks the priced surface backwards accumulating tokens until the `retainTokens` tail budget is met, then walks forward to the first tool-pairing-balanced boundary, never letting a `system/message` at node 0 into the range (`packages/compaction/compaction-basic/src/region.ts:117-155`, head exclusion at `region.ts:131`). `validateSurfaceRegion` then confirms both seqs exist on the surface, are ordered, and are balanced on both sides so no tool-call/result pair or open step is split (`region.ts:337-358`).\n\n- **Transaction opening and the compaction lock.** The owner is derived from the open turn, or `null` for manual idle compaction, and a `compaction/start` event with a fresh `CompactionId` is appended *before* any `await` — the durable marker itself is the lock, re-checked by `assertCompactionInactive` (`region.ts:184-210`, `region.ts:308-320`). `prepareCompaction` then prices the selected nodes with the meter, checks the surface hasn't drifted, and captures both the heuristic and route-priced totals (`region.ts:361-384`).\n\n- **Request assembly (replay-then-instruction).** `buildSummarizationInput` reconstructs the last routed request's cacheable prefix: the `system/message` head's derived message (if any), the header's tool schemas, then the shadowed region's events projected to messages in surface order (`region.ts:544-563`). The summarizer appends `COMPACTION_INSTRUCTION` as the **final user message** rather than using a separate summarizer system prompt, precisely so the call is a byte-prefix of the real request and hits the provider's KV cache (`summarizer.ts:25-67`, `summarizer.ts:145-151`); target provider/model resolves as config → last routed header → agent options (`summarizer.ts:127-142`) and the call goes out via `ctx.llm.stream()` with `toolHistory`, `purpose: 'compaction'`, the session id, `maxTokens`, and any abort signal (`summarizer.ts:152-163`).\n\n- **Result collection and fail-closed shaping.** Chunks feed a `BlockAssembler`; terminal `error`/`aborted` finish reasons become an `LlmError`, and `max-tokens` becomes a hard `MAX_TOKENS` error rather than a silently truncated checkpoint (`summarizer.ts:163-165`, `summarizer.ts:197-211`). The output is projected to text-only, rejecting any image block, and an empty summary throws (`summarizer.ts:167-171`, `summarizer.ts:214-220`). `SummaryResult` carries the safe `summary`, the raw output plus `llmStreamCall: true` marker, and provider usage (`summarizer.ts:87-107`, `summarizer.ts:172-180`).\n\n- **Landing back in the session.** `frameSummary` wraps the text in the preamble plus `<compacted-summary>` tags (`summarizer.ts:188-194`), `summarizeCompaction` turns that into a `UserMessage` tagged by `compactCheckpointSource` and refuses it if the framed estimate isn't strictly smaller than the span's route-priced total (`region.ts:410-422`), re-running summarization once if `recover` accepts the failure (`region.ts:396-409`). `commitCompactionBody` then appends `compaction/summary` (range, seqs, token count, provider/model, usage, raw output) followed by a `user/message` carrying `surfaceOp: { op: 'replace', startSeq, endSeq }` and `sourceEventSeqs`, which is what swaps the span for the checkpoint on the surface (`region.ts:491-509`); the bracket closes with `compaction/end` and `completeCompaction` attaches `endSeq` to the returned `CompactionResult` (`region.ts:237-239`, `region.ts:525-530`). A failed close leaves the unmatched start detectable for the next caller (`region.ts:240-251`)."
        }
      ]
    },
    {
      "role": "user",
      "content": [
        {
          "type": "text",
          "text": "Now read packages/compaction/compaction-basic/src/config.ts. With a 1,000,000-token context window, a 256,000-token output reservation and default settings, what are thresholdTokens and retainTokens? Show the arithmetic."
        }
      ]
    },
    {
      "role": "assistant",
      "content": [
        {
          "type": "thinking",
          "thinking": "Let me read config.ts.",
          "signature": "2c12eb3f-af24-41a6-a36a-0ac2dc557db9"
        },
        {
          "type": "tool_use",
          "id": "call_00_W6wEHJZv5Fkx9ROyRgL23464",
          "name": "read",
          "input": {
            "file_path": "packages/compaction/compaction-basic/src/config.ts"
          }
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            {
              "type": "text",
              "text": "<path>/tmp/dsh-lab/compaction/ws/packages/compaction/compaction-basic/src/config.ts</path>\n<type>file</type>\n<content>\n1: /**\n2:  * Load-time validation and routed-model policy resolution for compaction-basic.\n3:  *\n4:  * @module @deepseek-ai/dsh-compaction-basic/config\n5:  */\n6: \n7: import type { LlmCallConfig } from '@deepseek-ai/dsh-llm'\n8: import { deepFreeze } from '@deepseek-ai/dsh-util-values'\n9: import type {\n10:   BasicCompactionConfig,\n11:   CompactionPolicyConfig,\n12:   ModelCompactPolicyConfig,\n13:   ResolvedCompactSpec,\n14:   ResolvedConfig,\n15:   ResolvedRetention,\n16:   ResolvedTargetPolicy,\n17: } from './types.ts'\n18: \n19: /** Default request-pressure fraction for every routed model. */\n20: const DEFAULT_THRESHOLD_RATIO = 0.8\n21: \n22: /** Default verbatim-tail fraction for every routed model. */\n23: const DEFAULT_RETAIN_RATIO = 0.16\n24: \n25: /** Fields shared by top-level defaults and exact-target overrides. */\n26: const POLICY_CONFIG_KEYS = [\n27:   'thresholdRatio',\n28:   'headroomTokens',\n29:   'retainRatio',\n30:   'retainTokens',\n31:   'summarizationProvider',\n32:   'summarizationModel',\n33:   'maxTokens',\n34:   'compactionRetries',\n35:   'maxOverflowRetries',\n36: ] as const\n37: \n38: /** Complete public top-level configuration key set. */\n39: const BASIC_COMPACT_CONFIG_KEYS: ReadonlySet<string> = new Set([\n40:   ...POLICY_CONFIG_KEYS,\n41:   'modelPolicies',\n42:   'auto',\n43: ])\n44: \n45: /** Complete exact-target override key set. */\n46: const MODEL_POLICY_KEYS: ReadonlySet<string> = new Set([\n47:   'provider',\n48:   'model',\n49:   ...POLICY_CONFIG_KEYS,\n50: ])\n51: \n52: /** Target-specific pressure configuration failure eligible for warning suppression. */\n53: export class TargetPressureConfigError extends Error {\n54:   /**\n55:    * @param targetKey - exact provider/model route used as the warning key.\n56:    * @param message - actionable configuration failure detail.\n57:    */\n58:   constructor(readonly targetKey: string, message: string) {\n59:     super(message)\n60:   }\n61: }\n62: \n63: /**\n64:  * Resolve and validate service defaults plus exact-target partial overrides.\n65:  * @param config - untrusted plugin configuration after Loader normalization.\n66:  * @returns detached immutable defaults and validated exact-target overrides.\n67:  */\n68: export function resolveConfig(config: BasicCompactionConfig = {}): ResolvedConfig {\n69:   validateKeys(config, BASIC_COMPACT_CONFIG_KEYS, 'BasicCompactionConfig')\n70:   validatePolicy(config, 'BasicCompactionConfig')\n71:   if (config.auto !== undefined && typeof config.auto !== 'boolean') {\n72:     throw new Error('BasicCompactionConfig: auto must be a boolean')\n73:   }\n74: \n75:   const headroomTokens = config.headroomTokens ?? 65_536\n76:   const maxTokens = config.maxTokens ?? headroomTokens\n77:   assertPositiveInteger('BasicCompactionConfig.maxTokens (explicit or from headroomTokens)', maxTokens)\n78:   const thresholdRatio = config.thresholdRatio ?? DEFAULT_THRESHOLD_RATIO\n79:   const retention = resolveRetention(config, { retainRatio: DEFAULT_RETAIN_RATIO })\n80:   validateRatioRetention(thresholdRatio, retention, 'BasicCompactionConfig')\n81:   const modelPolicies = resolveModelPolicies(config.modelPolicies)\n82:   for (const [index, policy] of modelPolicies.entries()) {\n83:     if (policy.maxTokens === undefined && config.maxTokens === undefined\n84:       && policy.headroomTokens !== undefined) {\n85:       policy.maxTokens = policy.headroomTokens\n86:     }\n87:     assertPositiveInteger(\n88:       `BasicCompactionConfig: modelPolicies[${index}].maxTokens (explicit or from headroomTokens)`,\n89:       policy.maxTokens ?? maxTokens,\n90:     )\n91:     validateRatioRetention(\n92:       policy.thresholdRatio ?? thresholdRatio,\n93:       resolveRetention(policy, retention),\n94:       `BasicCompactionConfig: modelPolicies[${index}]`,\n95:     )\n96:   }\n97: \n98:   return deepFreeze({\n99:     thresholdRatio,\n100:     headroomTokens,\n101:     ...retention,\n102:     summarizationProvider: config.summarizationProvider ?? '',\n103:     summarizationModel: config.summarizationMod\n\n[... tool result middle pruned ...]\n\n  if (typeof value !== 'string' || value.length === 0) {\n342:     throw new Error(`${name} must be a non-empty string`)\n343:   }\n344: }\n345: \n346: function assertPositiveInteger(name: string, value: unknown): asserts value is number {\n347:   if (typeof value !== 'number' || !Number.isInteger(value) || value <= 0) {\n348:     throw new Error(`${name} (${String(value)}) must be a positive integer`)\n349:   }\n350: }\n351: \n352: function assertNonNegativeInteger(name: string, value: unknown): asserts value is number {\n353:   if (typeof value !== 'number' || !Number.isInteger(value) || value < 0) {\n354:     throw new Error(`${name} (${String(value)}) must be a non-negative integer`)\n355:   }\n356: }\n357: \n358: function assertRatio(name: string, value: unknown): asserts value is number {\n359:   if (typeof value !== 'number' || !Number.isFinite(value) || value <= 0 || value > 1) {\n360:     throw new Error(`${name} (${String(value)}) must be a number in (0, 1]`)\n361:   }\n362: }\n\n(End of file - total 362 lines)\n</content>"
            }
          ],
          "is_error": false
        }
      ]
    },
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      "role": "assistant",
      "content": [
        {
          "type": "thinking",
          "thinking": "The middle was pruned — I need the resolveRetention and the policy resolution function that computes thresholdTokens/retainTokens from contextWindow and output reservation. Let me read lines ~100-300.",
          "signature": "77dda3c2-c945-43e3-a167-9d81fb44be11"
        },
        {
          "type": "text",
          "text": "The middle of the file was pruned — I need the resolution arithmetic."
        },
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          "id": "call_00_O2Ug6dojgFL2bsEF6RgB1794",
          "name": "read",
          "input": {
            "file_path": "packages/compaction/compaction-basic/src/config.ts",
            "offset": 100,
            "limit": 200
          }
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              "type": "text",
              "text": "<path>/tmp/dsh-lab/compaction/ws/packages/compaction/compaction-basic/src/config.ts</path>\n<type>file</type>\n<content>\n100:     headroomTokens,\n101:     ...retention,\n102:     summarizationProvider: config.summarizationProvider ?? '',\n103:     summarizationModel: config.summarizationModel ?? '',\n104:     maxTokens,\n105:     compactionRetries: config.compactionRetries ?? 1,\n106:     maxOverflowRetries: config.maxOverflowRetries ?? 1,\n107:     modelPolicies,\n108:     auto: config.auto ?? true,\n109:   })\n110: }\n111: \n112: /**\n113:  * Merge the exact provider/model override over the validated default policy.\n114:  * @param config - validated service defaults and override table.\n115:  * @param target - exact durable provider/model route to match.\n116:  * @returns detached immutable policy before model-capacity scaling.\n117:  */\n118: export function resolveTargetPolicy(\n119:   config: ResolvedConfig,\n120:   target: Pick<LlmCallConfig, 'provider' | 'model'>,\n121: ): ResolvedTargetPolicy {\n122:   const override = config.modelPolicies.find(policy => (\n123:     policy.provider === target.provider && policy.model === target.model\n124:   ))\n125:   const inheritedRetention: ResolvedRetention = config.retainTokens === undefined\n126:     ? { retainRatio: config.retainRatio }\n127:     : { retainTokens: config.retainTokens }\n128:   return deepFreeze({\n129:     target: { provider: target.provider, model: target.model },\n130:     thresholdRatio: override?.thresholdRatio ?? config.thresholdRatio,\n131:     headroomTokens: override?.headroomTokens ?? config.headroomTokens,\n132:     ...resolveRetention(override ?? {}, inheritedRetention),\n133:     summarizationProvider: override?.summarizationProvider ?? config.summarizationProvider,\n134:     summarizationModel: override?.summarizationModel ?? config.summarizationModel,\n135:     maxTokens: override?.maxTokens ?? config.maxTokens,\n136:     compactionRetries: override?.compactionRetries ?? config.compactionRetries,\n137:     maxOverflowRetries: override?.maxOverflowRetries ?? config.maxOverflowRetries,\n138:   })\n139: }\n140: \n141: /**\n142:  * Scale one routed policy into concrete token budgets for its model capacity.\n143:  *\n144:  * Pressure is capped by both the window fraction and the capacity remaining\n145:  * after the routed output reservation plus compaction headroom. Retention scales\n146:  * the message budget before headroom is deducted.\n147:  *\n148:  * @param policy - merged policy for the exact routed target.\n149:  * @param contextWindow - positive adapter-owned capacity for that target.\n150:  * @param reservedCompletionTokens - output tokens one routed request reserves.\n151:  * @returns detached immutable pressure and retention budgets.\n152:  */\n153: export function resolveCompactSpec(\n154:   policy: ResolvedTargetPolicy,\n155:   contextWindow: number,\n156:   reservedCompletionTokens: number,\n157: ): ResolvedCompactSpec {\n158:   const targetKey = `${policy.target.provider}/${policy.target.model}`\n159:   if (!Number.isInteger(contextWindow) || contextWindow <= 0) {\n160:     throw new TargetPressureConfigError(\n161:       targetKey,\n162:       `BasicCompactionConfig: contextWindow (${contextWindow}) must be a positive integer`,\n163:     )\n164:   }\n165:   if (!Number.isInteger(reservedCompletionTokens) || reservedCompletionTokens < 0) {\n166:     throw new TargetPressureConfigError(\n167:       targetKey,\n168:       `BasicCompactionConfig: reservedCompletionTokens (${reservedCompletionTokens}) `\n169:       + 'must be a non-negative integer',\n170:     )\n171:   }\n172:   const messageBudgetTokens = contextWindow - reservedCompletionTokens\n173:   if (messageBudgetTokens <= 0) {\n174:     throw new TargetPressureConfigError(\n175:       targetKey,\n176:       `compaction-basic: ${targetKey} reserves ${reservedCompletionTokens} completion tokens `\n177:       + `of its ${contextWindow}-token context window, leaving no message budget; configure `\n178:       + \"the adapter model's contextWindow above the effective request maxTokens\",\n179:     )\n180:   }\n181:   const pressureBudgetTokens = messageBudgetTo\n\n[... tool result middle pruned ...]\n\ns\n286:   const compactionRetries = config.compactionRetries\n287:   const maxOverflowRetries = config.maxOverflowRetries\n288:   if (thresholdRatio !== undefined) assertRatio(`${name}.thresholdRatio`, thresholdRatio)\n289:   if (headroomTokens !== undefined) assertNonNegativeInteger(`${name}.headroomTokens`, headroomTokens)\n290:   if (retainRatio !== undefined) assertRatio(`${name}.retainRatio`, retainRatio)\n291:   if (retainTokens !== undefined) assertNonNegativeInteger(`${name}.retainTokens`, retainTokens)\n292:   if (retainRatio !== undefined && retainTokens !== undefined) {\n293:     throw new Error(`${name}: retainRatio and retainTokens are mutually exclusive`)\n294:   }\n295:   if (maxTokens !== undefined) assertPositiveInteger(`${name}.maxTokens`, maxTokens)\n296:   if (compactionRetries !== undefined) {\n297:     assertNonNegativeInteger(`${name}.compactionRetries`, compactionRetries)\n298:   }\n299:   if (maxOverflowRetries !== undefined) {\n\n(Showing lines 100-299 of 362. Use offset=300 to continue.)\n</content>"
            }
          ],
          "is_error": false
        }
      ]
    },
    {
      "role": "assistant",
      "content": [
        {
          "type": "thinking",
          "thinking": "Defaults: thresholdRatio 0.8 (config.ts:20), retainRatio 0.16 (config.ts:23), headroomTokens default 65_536 (config.ts:75). maxTokens defaults to headroomTokens — but the question gives reservedCompletionTokens = 256,000, which is the routed output reservation, an input to resolveCompactSpec, separate from `maxTokens`. Actually reservedCompletionTokens comes from adapter. So use 256,000.\n\nCompute:\n- messageBudgetTokens = 1,000,000 - 256,000 = 744,000 (config.ts:172)\n- pressureBudgetTokens = 744,000 - 65,536 = 678,464 (config.ts:181)\n- thresholdTokens = floor(min(1,000,000 * 0.8, 678,464)) = floor(min(800,000, 678,464)) = 678,464 (config.ts:191-194)\n- retainTokens (default ratio, since retainTokens undefined) = floor(744,000 * 0.16) = floor(119,040) = 119,040 (config.ts:195-197)\n\nCheck retainTokens < thresholdTokens: 119,040 < 678,464 ✓ (config.ts:198).\n\nNote the headroom cap binds, not the 0.8 ratio — interesting point: pressure budget 678,464 is below 800,000.\n\nAlso note retainRatio is scaled against messageBudgetTokens, not contextWindow — 744,000*0.16 = 119,040 rather than 160,000.\n\nAlso note validateRatioRetention: 0.16 < 0.8 passes at load (config.ts:235).\n\nAlso mention maxTokens default = headroomTokens = 65,536 (config.ts:76) — but that's the summarization request cap, not the reservation. The reservedCompletionTokens is supplied separately (config.ts:150, 156).\n\nNumbers: 119,040 exactly (744000*0.16 = 119,040).",
          "signature": "b7fe14ea-359f-43cd-ad43-f0a6d813e080"
        },
        {
          "type": "text",
          "text": "Defaults confirmed: `thresholdRatio` 0.8 (`config.ts:20`), `retainRatio` 0.16 (`config.ts:23`), `headroomTokens` 65,536 (`config.ts:75`). Since the default is a ratio, not a fixed `retainTokens`, the ratio path applies (`config.ts:195-197`); `reservedCompletionTokens` is an input supplied by the adapter, distinct from `maxTokens` (`config.ts:150-156`).\n\n**Arithmetic** (`resolveCompactSpec`, `config.ts:172-197`):\n\n```\nmessageBudgetTokens   = contextWindow − reservedCompletionTokens\n                      = 1,000,000 − 256,000\n                      = 744,000                          (config.ts:172)\n\npressureBudgetTokens  = messageBudgetTokens − headroomTokens\n                      = 744,000 − 65,536\n                      = 678,464                          (config.ts:181)\n\nthresholdTokens       = floor( min( contextWindow × thresholdRatio,\n                                    pressureBudgetTokens ) )\n                      = floor( min( 1,000,000 × 0.8, 678,464 ) )\n                      = floor( min( 800,000, 678,464 ) )\n                      = 678,464                          (config.ts:191-194)\n\nretainTokens          = floor( messageBudgetTokens × retainRatio )   [ratio default]\n                      = floor( 744,000 × 0.16 )\n                      = floor( 119,040.0 )\n                      = 119,040                          (config.ts:195-197)\n```\n\n- **`thresholdTokens` = 678,464** — note the headroom cap binds, not the nominal 80% figure: 800,000 > 678,464, so the budget after the 256,000 output reservation and 65,536 headroom is the real ceiling. A larger reservation or headroom would silently dominate the ratio here.\n- **`retainTokens` = 119,040** — scaled against `messageBudgetTokens` (744,000), *not* the raw 1,000,000 window (which would have given 160,000), because retention is clamped to the message budget before headroom is deducted (`config.ts:145-146`, `config.ts:196`).\n\nThe result is valid: `retainTokens` (119,040) < `thresholdTokens` (678,464), so the guard at `config.ts:198-204` passes, and the load-time ratio check `0.16 < 0.8` passes at `config.ts:235-240`. Both budgets are returned under `deepFreeze` alongside `contextWindow` and the ratios (`config.ts:205-216`).\n\nOne caveat on literals: there is no rounding loss here, but `Math.floor` on both means a non-integer context window or an odd window/ratio pairing could shave up to 1 token off each figure rather than rounding to nearest."
        }
      ]
    },
    {
      "role": "user",
      "content": [
        {
          "type": "text",
          "text": "Read packages/compaction/compaction-tool-result-pruner/src/index.ts and packages/compaction/compaction-tool-result-pruner/src/config.ts. When does the pruner run relative to summarization, and what exactly does a pruned tool result look like?"
        }
      ]
    },
    {
      "role": "assistant",
      "content": [
        {
          "type": "thinking",
          "thinking": "",
          "signature": "58dfa939-83b6-4d54-8ea9-72d0a800c591"
        },
        {
          "type": "tool_use",
          "id": "call_00_ET_uZNbnKaMIkbydPq995NR5044",
          "name": "read",
          "input": {
            "file_path": "packages/compaction/compaction-tool-result-pruner/src/index.ts"
          }
        },
        {
          "type": "tool_use",
          "id": "call_01_ET_p0xGozRbRHw4CsHaI38A3444",
          "name": "read",
          "input": {
            "file_path": "packages/compaction/compaction-tool-result-pruner/src/config.ts"
          }
        }
      ]
    },
    {
      "role": "user",
      "content": [
        {
          "type": "tool_result",
          "tool_use_id": "call_00_ET_uZNbnKaMIkbydPq995NR5044",
          "content": [
            {
              "type": "text",
              "text": "<path>/tmp/dsh-lab/compaction/ws/packages/compaction/compaction-tool-result-pruner/src/index.ts</path>\n<type>file</type>\n<content>\n1: /**\n2:  * Replay-safe, model-free tool-result pruning service.\n3:  *\n4:  * @module @deepseek-ai/dsh-compaction-tool-result-pruner\n5:  */\n6: \n7: import { Context, Service } from '@deepseek-ai/cordis'\n8: import z from '@deepseek-ai/schemastery'\n9: import { freezeMessage } from '@deepseek-ai/dsh-llm'\n10: import type { ContentBlock } from '@deepseek-ai/dsh-llm'\n11: import type { Session, SessionEvent, SessionSeq, ToolResultMessage } from '@deepseek-ai/dsh-session'\n12: // Type-only: the `compaction/*` SessionEventMap merges (the shadow-price event).\n13: import type {} from '@deepseek-ai/dsh-compaction'\n14: // Type-only: the `ctx.tokenMeter` Context merge for the declared injection.\n15: import type {} from '@deepseek-ai/dsh-token-meter'\n16: import { codePointLength, DEFAULTS, PRUNE_MARKER, resolveConfig } from './config.ts'\n17: import type {\n18:   PrunedEntry,\n19:   PruneResult,\n20:   ResolvedConfig,\n21:   ToolResultPruneConfig,\n22: } from './types.ts'\n23: \n24: export { codePointLength, DEFAULTS, PRUNE_MARKER, resolveConfig } from './config.ts'\n25: export type {\n26:   PrunedEntry,\n27:   PruneResult,\n28:   ResolvedConfig,\n29:   ToolResultPruneConfig,\n30: } from './types.ts'\n31: \n32: declare module '@deepseek-ai/cordis' {\n33:   interface Context {\n34:     toolResultPruner: ToolResultPruner\n35:   }\n36: }\n37: \n38: interface SnapshotCandidate {\n39:   readonly seq: SessionSeq\n40:   readonly event: SessionEvent<'tool/result'>\n41: }\n42: \n43: /** Deterministic head/middle/tail pruning for current tool-result surface nodes. */\n44: export class ToolResultPruner extends Service {\n45:   // The token meter prices each shadowed node for its logged shadow-price\n46:   // event, so pruning genuinely requires the pricing capability.\n47:   static inject = ['tokenMeter']\n48: \n49:   static Config: z<ToolResultPruneConfig> = z.object({\n50:     thresholdChars: z.number().step(1).min(1).default(DEFAULTS.thresholdChars),\n51:     headChars: z.number().step(1).min(0).default(DEFAULTS.headChars),\n52:     tailChars: z.number().step(1).min(0).default(DEFAULTS.tailChars),\n53:   })\n54: \n55:   /** Resolved and immutable character budgets. */\n56:   readonly config: ResolvedConfig\n57: \n58:   constructor(ctx: Context, config: ToolResultPruneConfig = {}) {\n59:     super(ctx, 'toolResultPruner')\n60:     this.config = resolveConfig(config)\n61:   }\n62: \n63:   /**\n64:    * Measure text content in Unicode code points; non-text blocks cost zero.\n65:    * @param blocks - tool-result content to measure.\n66:    * @returns total Unicode code points across text blocks.\n67:    */\n68:   measureContent(blocks: readonly ContentBlock[]): number {\n69:     let chars = 0\n70:     for (const block of blocks) {\n71:       if (block.type === 'text') chars += codePointLength(block.text)\n72:     }\n73:     return chars\n74:   }\n75: \n76:   /**\n77:    * Replace an over-budget text middle while retaining rich-block order.\n78:    * Text slicing is by Unicode code point, not UTF-16 code unit, so a retained\n79:    * boundary cannot split a surrogate pair. Grapheme clusters may still split.\n80:    * @param blocks - original tool-result content.\n81:    * @returns pruned content, or `null` when the text is within budget.\n82:    */\n83:   pruneContent(blocks: readonly ContentBlock[]): ContentBlock[] | null {\n84:     const totalChars = this.measureContent(blocks)\n85:     if (totalChars <= this.config.thresholdChars) return null\n86: \n87:     const removedStart = this.config.headChars\n88:     const removedEnd = totalChars - this.config.tailChars\n89:     const pruned: ContentBlock[] = []\n90:     let consumed = 0\n91:     let markerInserted = false\n92: \n93:     for (const block of blocks) {\n94:       if (block.type !== 'text') {\n95:         pruned.push(block)\n96:         continue\n97:       }\n98: \n99:       const points = Array.from(block.text)\n100:       const blockStart = consumed\n101:       const blockEnd = blockStart + points.length\n102:       const headEnd = Math.min(point\n\n[... tool result middle pruned ...]\n\nnt, so pure consumers subtract the\n159:       // shadowed node's heuristic price without retaining per-node state.\n160:       session.append('compaction/prune', {\n161:         shadowedRange: { start: seq, end: seq },\n162:         shadowedSeqs: [seq],\n163:         shadowedTokenCount: this.ctx.tokenMeter.estimateMessage(original),\n164:       })\n165:       const replacement = session.append('tool/result', {\n166:         ...event.data,\n167:         message,\n168:       }, {\n169:         surfaceOp: { op: 'replace', startSeq: seq, endSeq: seq },\n170:         sourceEventSeqs: [seq],\n171:       })\n172:       pruned.push({\n173:         originalSeq: seq,\n174:         replacementSeq: replacement.seq,\n175:         callId: event.data.message.source.callId,\n176:         charsBefore,\n177:         charsAfter,\n178:       })\n179:       charsRemoved += charsBefore - charsAfter\n180:     }\n181:     return { pruned, charsRemoved }\n182:   }\n183: }\n184: \n185: export default ToolResultPruner\n\n(End of file - total 185 lines)\n</content>"
            }
          ],
          "is_error": false
        },
        {
          "type": "tool_result",
          "tool_use_id": "call_01_ET_p0xGozRbRHw4CsHaI38A3444",
          "content": [
            {
              "type": "text",
              "text": "<path>/tmp/dsh-lab/compaction/ws/packages/compaction/compaction-tool-result-pruner/src/config.ts</path>\n<type>file</type>\n<content>\n1: /** Configuration resolution for deterministic tool-result pruning. */\n2: \n3: import { deepFreeze } from '@deepseek-ai/dsh-util-values'\n4: import type { ResolvedConfig, ToolResultPruneConfig } from './types.ts'\n5: \n6: /** Fixed marker substituted for every removed middle span. */\n7: export const PRUNE_MARKER = '\\n\\n[... tool result middle pruned ...]\\n\\n'\n8: \n9: /** Low-friction defaults for coding-agent tool output. */\n10: export const DEFAULTS: ResolvedConfig = deepFreeze({\n11:   thresholdChars: 8192,\n12:   headChars: 4096,\n13:   tailChars: 1024,\n14: })\n15: \n16: const CONFIG_KEYS: ReadonlySet<string> = new Set([\n17:   'thresholdChars',\n18:   'headChars',\n19:   'tailChars',\n20: ])\n21: \n22: /**\n23:  * Count Unicode code points without splitting surrogate pairs.\n24:  * @param text - text to measure.\n25:  * @returns the Unicode code-point count.\n26:  */\n27: export function codePointLength(text: string): number {\n28:   return Array.from(text).length\n29: }\n30: \n31: /**\n32:  * Resolve and validate pruning budgets.\n33:  * @param config - raw plugin configuration.\n34:  * @returns a detached deeply immutable configuration.\n35:  */\n36: export function resolveConfig(config: ToolResultPruneConfig = {}): ResolvedConfig {\n37:   for (const key of Object.keys(config)) {\n38:     if (!CONFIG_KEYS.has(key)) {\n39:       throw new Error(\n40:         `ToolResultPruneConfig: unknown key \"${key}\" `\n41:         + '(allowed: thresholdChars, headChars, tailChars)',\n42:       )\n43:     }\n44:   }\n45: \n46:   const resolved: ResolvedConfig = {\n47:     thresholdChars: config.thresholdChars ?? DEFAULTS.thresholdChars,\n48:     headChars: config.headChars ?? DEFAULTS.headChars,\n49:     tailChars: config.tailChars ?? DEFAULTS.tailChars,\n50:   }\n51:   assertPositiveInteger('thresholdChars', resolved.thresholdChars)\n52:   assertNonNegativeInteger('headChars', resolved.headChars)\n53:   assertNonNegativeInteger('tailChars', resolved.tailChars)\n54: \n55:   const emittedChars = resolved.headChars\n56:     + codePointLength(PRUNE_MARKER)\n57:     + resolved.tailChars\n58:   if (emittedChars > resolved.thresholdChars) {\n59:     throw new Error(\n60:       `ToolResultPruneConfig: headChars + marker + tailChars (${emittedChars}) `\n61:       + `must be at most thresholdChars (${resolved.thresholdChars})`,\n62:     )\n63:   }\n64:   return deepFreeze(structuredClone(resolved))\n65: }\n66: \n67: function assertPositiveInteger(name: string, value: number): void {\n68:   if (!Number.isInteger(value) || value <= 0) {\n69:     throw new Error(`ToolResultPruneConfig: ${name} (${value}) must be a positive integer`)\n70:   }\n71: }\n72: \n73: function assertNonNegativeInteger(name: string, value: number): void {\n74:   if (!Number.isInteger(value) || value < 0) {\n75:     throw new Error(`ToolResultPruneConfig: ${name} (${value}) must be a non-negative integer`)\n76:   }\n77: }\n\n(End of file - total 77 lines)\n</content>"
            }
          ],
          "is_error": false
        },
        {
          "type": "text",
          "text": "You are now acting as a compaction engine for this AI coding assistant. Condense the conversation ABOVE into a structured checkpoint that lets another model resume the work with no loss of essential context.\n\nOutput EXACTLY the Markdown structure below: keep every section, in order. Use terse bullets, not prose paragraphs. Write \"(none)\" for an empty section — never drop a section.\n\n## Primary Request and Intent\n- [the user's original and evolving goals; quote verbatim where the exact wording matters]\n\n## Key Technical Concepts\n- [technologies, frameworks, patterns, and conventions in play]\n\n## Files and Code\n- [exact path: why it matters, key changes or snippets]\n\n## Errors and Fixes\n- [error: how it was resolved, plus any related user feedback]\n\n## Pending Jobs\n- [explicitly requested work not yet completed]\n\n## Current Work\n- [precisely what was in progress at this checkpoint]\n\n## Next Step\n- [the single next action, directly in line with the most recent request, or \"(none)\"]\n\n## Critical Context\n- [decisions and their rationale, constraints, user preferences, open questions, data needed to continue]\n\nRules:\n- Write concise English engineering prose. Preserve exact file paths, commands, error strings, identifiers, numeric values, function signatures, and syntax fragments.\n- Capture user feedback and explicit instructions faithfully, especially corrections.\n- Do NOT mention this summarization request or that the context was compacted.\n- Output only the checkpoint text: do not call any tool or take any other action.\n- If the conversation already contains a <compacted-summary> block, it is a PRIOR checkpoint. Do not copy it forward verbatim: preserve still-true facts, drop stale ones, and merge newer information into a single consolidated summary under the same structure."
        }
      ]
    }
  ],
  "max_tokens": 65536,
  "thinking": {
    "type": "enabled"
  },
  "output_config": {
    "effort": "high"
  },
  "system": "You are an AI agent powered by DeepSeek Harness.\n\nYou are a coding agent powered by the deepseek-flash model.\n\nUse the read tool — not shell commands like cat — to inspect text files. Use offset and limit to continue reading large files.",
  "tools": [
    {
      "name": "read",
      "description": "Read a UTF-8 text file and return line-numbered content.",
      "input_schema": {
        "type": "object",
        "properties": {
          "file_path": {
            "type": "string",
            "description": "Path to read, resolved by the filesystem backend."
          },
          "offset": {
            "type": "number",
            "description": "1-based first line to return. Defaults to 1."
          },
          "limit": {
            "type": "number",
            "description": "Maximum number of lines to return. Defaults to 2000."
          }
        },
        "required": [
          "file_path"
        ]
      }
    }
  ]
}

{
  "model": "deepseek-flash",
  "max_tokens": 65536,
  "thinking": {
    "type": "enabled"
  },
  "output_config": {
    "effort": "high"
  },
  "system": "You are a context summarization assistant. Your task is to read a conversation between a user and an AI assistant, then produce a structured summary following the exact format specified.\n\nDo NOT continue the conversation. Do NOT respond to any questions in the conversation. ONLY output the structured summary.",
  "messages": [
    {
      "role": "user",
      "content": [
        {
          "type": "text",
          "text": "<conversation>\n[User]: Read packages/compaction/compaction-basic/src/summarizer.ts and packages/compaction/compaction-basic/src/region.ts. Explain in five bullets how a compaction request is assembled and how its result lands back in the session.\n\n[User]: <system-reminder>\nThe following workspace instructions may be relevant to your work. Use them as guidance when applicable. More specific instructions take precedence over broader ones. They do not override system, developer, or direct user instructions.\n\nInstructions from: AGENTS.md\n\n# Workspace notes\n\n- TypeScript monorepo: every package lives under `packages/<group>/<name>/src`.\n- This checkout is read-only. Do not try to edit or write files.\n- When you explain code, cite `path:line` for every claim.\n\n</system-reminder>\n\n[User]: Current runtime context. This snapshot supersedes earlier runtime-context snapshots.\n\nCurrent working directory: \"/tmp/dsh-lab/compaction/ws\".\n\n[Assistant]: I'll read both files.\n\n[Assistant tool calls]: read(file_path=\"packages/compaction/compaction-basic/src/summarizer.ts\"); read(file_path=\"packages/compaction/compaction-basic/src/region.ts\")\n\n[Tool result]: <path>/tmp/dsh-lab/compaction/ws/packages/compaction/compaction-basic/src/summarizer.ts</path>\n<type>file</type>\n<content>\n1: /**\n2:  * Default one-shot summarization and durable checkpoint framing.\n3:  *\n4:  * @module @deepseek-ai/dsh-compaction-basic/summarizer\n5:  */\n6: \n7: import type { Context } from '@deepseek-ai/cordis'\n8: import { contentHasImage, BlockAssembler, LlmError } from '@deepseek-ai/dsh-llm'\n9: import { deepFreeze } from '@deepseek-ai/dsh-util-values'\n10: import type {\n11:   ContentBlock, FinishReason, GenerateOptions, Message, RequestMessage, TokenUsage, ToolSchema,\n12: } from '@deepseek-ai/dsh-llm'\n13: import type { Agent } from '@deepseek-ai/dsh-agent'\n14: \n15: interface SummaryConfig {\n16:   readonly summarizationProvider: string\n17:   readonly summarizationModel: string\n18:   readonly maxTokens: number\n19: }\n20: \n21: /** Tags wrapping the structured summary inside the landed checkpoint node. */\n22: const SUMMARY_OPEN_TAG = '<compacted-summary>'\n23: const SUMMARY_CLOSE_TAG = '</compacted-summary>'\n24: \n25: /**\n26:  * The summarization directive, delivered as the FINAL user message after the\n27:  * replayed conversation rather than as a distinct summarizer system prompt.\n28:  * Keeping the conversation's own system prompt, tools, and message prefix in\n29:  * front of it makes the auxiliary call a genuine prefix of the last routed\n30:  * request, so the provider's KV cache is reused instead of invalidated.\n31:  */\n32: const COMPACTION_INSTRUCTION = [\n33:   'You are now acting as a compaction engine for this AI coding assistant. Condense the conversation ABOVE into a structured checkpoint that lets another model resume the work with no loss of essential context.',\n34:   '',\n35:   'Output EXACTLY the Markdown structure below: keep every section, in order. Use terse bullets, not prose paragraphs. Write \"(none)\" for an empty section — never drop a section.',\n36:   '',\n37:   '## Primary Request and Intent',\n38:   \"- [the user's original and evolving g\n\n[... 3159 more characters truncated]\n\n[Tool result]: <path>/tmp/dsh-lab/compaction/ws/packages/compaction/compaction-basic/src/region.ts</path>\n<type>file</type>\n<content>\n1: /**\n2:  * Surface retention selection and the shared log-recorded compaction\n3:  * transaction for automatic open-turn and manual idle-session compaction.\n4:  *\n5:  * @module @deepseek-ai/dsh-compaction-basic/region\n6:  */\n7: \n8: import { randomUUID } from 'node:crypto'\n9: import { isDeepStrictEqual } from 'node:util'\n10: import {\n11:   CompactionId,\n12:   ManualCompactionError,\n13:   compactCheckpointSource,\n14:   toolPairingBalancedAfter,\n15:   toolPairingBalancedBefore,\n16: } from '@deepseek-ai/dsh-compaction'\n17: import type { CompactionResult } from '@deepseek-ai/dsh-compaction'\n18: import type { CommandId } from '@deepseek-ai/dsh-commands/brand'\n19: import { createUserMessage, errorChain } from '@deepseek-ai/dsh-llm'\n20: import type { Message, UserMessage } from '@deepseek-ai/dsh-llm'\n21: import type { TokenMeasurement, TokenMeter } from '@deepseek-ai/dsh-token-meter'\n22: import { SessionSeq, type Session, type SessionEvent } from '@deepseek-ai/dsh-session'\n23: import type { Agent } from '@deepseek-ai/dsh-agent'\n24: import { frameSummary } from './summarizer.ts'\n25: import type { SummarizationInput, SummaryResult } from './summarizer.ts'\n26: interface RegionDependencies {\n27:   readonly meter: TokenMeter\n28:   summarize(input: SummarizationInput, agent: Agent, signal?: AbortSignal): Promise<SummaryResult>\n29:   recover(error: unknown, agent: Agent, sourceEventSeqs: readonly SessionSeq[], signal?: AbortSignal): boolean\n30: }\n31: \n32: /** One validated inclusive span of current surface positions. */\n33: interface SurfaceSelection {\n34:   readonly start: SessionSeq\n35:   readonly end: SessionSeq\n36:   readonly startIdx: number\n37:   readonly endIdx: number\n38:   readonly shadowedSeqs: readonly SessionSeq[]\n39: }\n40: \n41: /** A selection with its priced snapshot and the replay input built from it. */\n42: interface PreparedCompaction extends Sur\n\n[... 3159 more characters truncated]\n\n[Assistant]: Both files read. Here's how a compaction request is built and how its outcome returns to the session.\n\n- **Span selection & validation (the \"what to compact\" decision).** `selectCompactableRange` walks the priced surface backwards accumulating tokens until the `retainTokens` tail budget is met, then walks forward to the first tool-pairing-balanced boundary, never letting a `system/message` at node 0 into the range (`packages/compaction/compaction-basic/src/region.ts:117-155`, head exclusion at `region.ts:131`). `validateSurfaceRegion` then confirms both seqs exist on the surface, are ordered, and are balanced on both sides so no tool-call/result pair or open step is split (`region.ts:337-358`).\n\n- **Transaction opening and the compaction lock.** The owner is derived from the open turn, or `null` for manual idle compaction, and a `compaction/start` event with a fresh `CompactionId` is appended *before* any `await` — the durable marker itself is the lock, re-checked by `assertCompactionInactive` (`region.ts:184-210`, `region.ts:308-320`). `prepareCompaction` then prices the selected nodes with the meter, checks the surface hasn't drifted, and captures both the heuristic and route-priced totals (`region.ts:361-384`).\n\n- **Request assembly (replay-then-instruction).** `buildSummarizationInput` reconstructs the last routed request's cacheable prefix: the `system/message` head's derived message (if any), the header's tool schemas, then the shadowed region's events projected to messages in surface order (`region.ts:544-563`). The summarizer appends `COMPACTION_INSTRUCTION` as the **final user message** rather than using a separate summarizer system prompt, precisely so the call is a byte-prefix of the real request and hits the provider's KV cache (`summarizer.ts:25-67`, `summarizer.ts:145-151`); target provider/model resolves as config → last routed header → agent options (`summarizer.ts:127-142`) and the call goes out via `ctx.llm.stream()` with `toolHistory`, `purpose: 'compaction'`, the session id, `maxTokens`, and any abort signal (`summarizer.ts:152-163`).\n\n- **Result collection and fail-closed shaping.** Chunks feed a `BlockAssembler`; terminal `error`/`aborted` finish reasons become an `LlmError`, and `max-tokens` becomes a hard `MAX_TOKENS` error rather than a silently truncated checkpoint (`summarizer.ts:163-165`, `summarizer.ts:197-211`). The output is projected to text-only, rejecting any image block, and an empty summary throws (`summarizer.ts:167-171`, `summarizer.ts:214-220`). `SummaryResult` carries the safe `summary`, the raw output plus `llmStreamCall: true` marker, and provider usage (`summarizer.ts:87-107`, `summarizer.ts:172-180`).\n\n- **Landing back in the session.** `frameSummary` wraps the text in the preamble plus `<compacted-summary>` tags (`summarizer.ts:188-194`), `summarizeCompaction` turns that into a `UserMessage` tagged by `compactCheckpointSource` and refuses it if the framed estimate isn't strictly smaller than the span's route-priced total (`region.ts:410-422`), re-running summarization once if `recover` accepts the failure (`region.ts:396-409`). `commitCompactionBody` then appends `compaction/summary` (range, seqs, token count, provider/model, usage, raw output) followed by a `user/message` carrying `surfaceOp: { op: 'replace', startSeq, endSeq }` and `sourceEventSeqs`, which is what swaps the span for the checkpoint on the surface (`region.ts:491-509`); the bracket closes with `compaction/end` and `completeCompaction` attaches `endSeq` to the returned `CompactionResult` (`region.ts:237-239`, `region.ts:525-530`). A failed close leaves the unmatched start detectable for the next caller (`region.ts:240-251`).\n\n[User]: Now read packages/compaction/compaction-basic/src/config.ts. With a 1,000,000-token context window, a 256,000-token output reservation and default settings, what are thresholdTokens and retainTokens? Show the arithmetic.\n\n[Assistant tool calls]: read(file_path=\"packages/compaction/compaction-basic/src/config.ts\")\n\n[Tool result]: <path>/tmp/dsh-lab/compaction/ws/packages/compaction/compaction-basic/src/config.ts</path>\n<type>file</type>\n<content>\n1: /**\n2:  * Load-time validation and routed-model policy resolution for compaction-basic.\n3:  *\n4:  * @module @deepseek-ai/dsh-compaction-basic/config\n5:  */\n6: \n7: import type { LlmCallConfig } from '@deepseek-ai/dsh-llm'\n8: import { deepFreeze } from '@deepseek-ai/dsh-util-values'\n9: import type {\n10:   BasicCompactionConfig,\n11:   CompactionPolicyConfig,\n12:   ModelCompactPolicyConfig,\n13:   ResolvedCompactSpec,\n14:   ResolvedConfig,\n15:   ResolvedRetention,\n16:   ResolvedTargetPolicy,\n17: } from './types.ts'\n18: \n19: /** Default request-pressure fraction for every routed model. */\n20: const DEFAULT_THRESHOLD_RATIO = 0.8\n21: \n22: /** Default verbatim-tail fraction for every routed model. */\n23: const DEFAULT_RETAIN_RATIO = 0.16\n24: \n25: /** Fields shared by top-level defaults and exact-target overrides. */\n26: const POLICY_CONFIG_KEYS = [\n27:   'thresholdRatio',\n28:   'headroomTokens',\n29:   'retainRatio',\n30:   'retainTokens',\n31:   'summarizationProvider',\n32:   'summarizationModel',\n33:   'maxTokens',\n34:   'compactionRetries',\n35:   'maxOverflowRetries',\n36: ] as const\n37: \n38: /** Complete public top-level configuration key set. */\n39: const BASIC_COMPACT_CONFIG_KEYS: ReadonlySet<string> = new Set([\n40:   ...POLICY_CONFIG_KEYS,\n41:   'modelPolicies',\n42:   'auto',\n43: ])\n44: \n45: /** Complete exact-target override key set. */\n46: const MODEL_POLICY_KEYS: ReadonlySet<string> = new Set([\n47:   'provider',\n48:   'model',\n49:   ...POLICY_CONFIG_KEYS,\n50: ])\n51: \n52: /** Target-specific pressure configuration failure eligible for warning suppression. */\n53: export class TargetPressureConfigError extends Error {\n54:   /**\n55:    * @param targetKey - exact provider/model route used as the warning key.\n56:    * @param message - actionable configuration failure detail.\n57:    */\n58:   constructor(readonly targetKey: string, message: string) {\n59:   \n\n[... 3159 more characters truncated]\n\n[Assistant]: The middle of the file was pruned — I need the resolution arithmetic.\n\n[Assistant tool calls]: read(file_path=\"packages/compaction/compaction-basic/src/config.ts\", offset=100, limit=200)\n\n[Tool result]: <path>/tmp/dsh-lab/compaction/ws/packages/compaction/compaction-basic/src/config.ts</path>\n<type>file</type>\n<content>\n100:     headroomTokens,\n101:     ...retention,\n102:     summarizationProvider: config.summarizationProvider ?? '',\n103:     summarizationModel: config.summarizationModel ?? '',\n104:     maxTokens,\n105:     compactionRetries: config.compactionRetries ?? 1,\n106:     maxOverflowRetries: config.maxOverflowRetries ?? 1,\n107:     modelPolicies,\n108:     auto: config.auto ?? true,\n109:   })\n110: }\n111: \n112: /**\n113:  * Merge the exact provider/model override over the validated default policy.\n114:  * @param config - validated service defaults and override table.\n115:  * @param target - exact durable provider/model route to match.\n116:  * @returns detached immutable policy before model-capacity scaling.\n117:  */\n118: export function resolveTargetPolicy(\n119:   config: ResolvedConfig,\n120:   target: Pick<LlmCallConfig, 'provider' | 'model'>,\n121: ): ResolvedTargetPolicy {\n122:   const override = config.modelPolicies.find(policy => (\n123:     policy.provider === target.provider && policy.model === target.model\n124:   ))\n125:   const inheritedRetention: ResolvedRetention = config.retainTokens === undefined\n126:     ? { retainRatio: config.retainRatio }\n127:     : { retainTokens: config.retainTokens }\n128:   return deepFreeze({\n129:     target: { provider: target.provider, model: target.model },\n130:     thresholdRatio: override?.thresholdRatio ?? config.thresholdRatio,\n131:     headroomTokens: override?.headroomTokens ?? config.headroomTokens,\n132:     ...resolveRetention(override ?? {}, inheritedRetention),\n133:     summarizationProvider: override?.summarizationProvider ?? config.summarizationProvider,\n134:     summarizationModel: override?.summarizationModel ?? config.summarizationModel,\n135:     maxTokens: override?.maxTokens ?? config.maxTokens,\n136:     compactionRetries: override?.compactionRetries ?? config.compactionRetries,\n137:     maxOverflowRetri\n\n[... 3159 more characters truncated]\n\n[Assistant]: Defaults confirmed: `thresholdRatio` 0.8 (`config.ts:20`), `retainRatio` 0.16 (`config.ts:23`), `headroomTokens` 65,536 (`config.ts:75`). Since the default is a ratio, not a fixed `retainTokens`, the ratio path applies (`config.ts:195-197`); `reservedCompletionTokens` is an input supplied by the adapter, distinct from `maxTokens` (`config.ts:150-156`).\n\n**Arithmetic** (`resolveCompactSpec`, `config.ts:172-197`):\n\n```\nmessageBudgetTokens   = contextWindow − reservedCompletionTokens\n                      = 1,000,000 − 256,000\n                      = 744,000                          (config.ts:172)\n\npressureBudgetTokens  = messageBudgetTokens − headroomTokens\n                      = 744,000 − 65,536\n                      = 678,464                          (config.ts:181)\n\nthresholdTokens       = floor( min( contextWindow × thresholdRatio,\n                                    pressureBudgetTokens ) )\n                      = floor( min( 1,000,000 × 0.8, 678,464 ) )\n                      = floor( min( 800,000, 678,464 ) )\n                      = 678,464                          (config.ts:191-194)\n\nretainTokens          = floor( messageBudgetTokens × retainRatio )   [ratio default]\n                      = floor( 744,000 × 0.16 )\n                      = floor( 119,040.0 )\n                      = 119,040                          (config.ts:195-197)\n```\n\n- **`thresholdTokens` = 678,464** — note the headroom cap binds, not the nominal 80% figure: 800,000 > 678,464, so the budget after the 256,000 output reservation and 65,536 headroom is the real ceiling. A larger reservation or headroom would silently dominate the ratio here.\n- **`retainTokens` = 119,040** — scaled against `messageBudgetTokens` (744,000), *not* the raw 1,000,000 window (which would have given 160,000), because retention is clamped to the message budget before headroom is deducted (`config.ts:145-146`, `config.ts:196`).\n\nThe result is valid: `retainTokens` (119,040) < `thresholdTokens` (678,464), so the guard at `config.ts:198-204` passes, and the load-time ratio check `0.16 < 0.8` passes at `config.ts:235-240`. Both budgets are returned under `deepFreeze` alongside `contextWindow` and the ratios (`config.ts:205-216`).\n\nOne caveat on literals: there is no rounding loss here, but `Math.floor` on both means a non-integer context window or an odd window/ratio pairing could shave up to 1 token off each figure rather than rounding to nearest.\n\n[User]: Read packages/compaction/compaction-tool-result-pruner/src/index.ts and packages/compaction/compaction-tool-result-pruner/src/config.ts. When does the pruner run relative to summarization, and what exactly does a pruned tool result look like?\n\n[Assistant tool calls]: read(file_path=\"packages/compaction/compaction-tool-result-pruner/src/index.ts\"); read(file_path=\"packages/compaction/compaction-tool-result-pruner/src/config.ts\")\n\n[Tool result]: <path>/tmp/dsh-lab/compaction/ws/packages/compaction/compaction-tool-result-pruner/src/index.ts</path>\n<type>file</type>\n<content>\n1: /**\n2:  * Replay-safe, model-free tool-result pruning service.\n3:  *\n4:  * @module @deepseek-ai/dsh-compaction-tool-result-pruner\n5:  */\n6: \n7: import { Context, Service } from '@deepseek-ai/cordis'\n8: import z from '@deepseek-ai/schemastery'\n9: import { freezeMessage } from '@deepseek-ai/dsh-llm'\n10: import type { ContentBlock } from '@deepseek-ai/dsh-llm'\n11: import type { Session, SessionEvent, SessionSeq, ToolResultMessage } from '@deepseek-ai/dsh-session'\n12: // Type-only: the `compaction/*` SessionEventMap merges (the shadow-price event).\n13: import type {} from '@deepseek-ai/dsh-compaction'\n14: // Type-only: the `ctx.tokenMeter` Context merge for the declared injection.\n15: import type {} from '@deepseek-ai/dsh-token-meter'\n16: import { codePointLength, DEFAULTS, PRUNE_MARKER, resolveConfig } from './config.ts'\n17: import type {\n18:   PrunedEntry,\n19:   PruneResult,\n20:   ResolvedConfig,\n21:   ToolResultPruneConfig,\n22: } from './types.ts'\n23: \n24: export { codePointLength, DEFAULTS, PRUNE_MARKER, resolveConfig } from './config.ts'\n25: export type {\n26:   PrunedEntry,\n27:   PruneResult,\n28:   ResolvedConfig,\n29:   ToolResultPruneConfig,\n30: } from './types.ts'\n31: \n32: declare module '@deepseek-ai/cordis' {\n33:   interface Context {\n34:     toolResultPruner: ToolResultPruner\n35:   }\n36: }\n37: \n38: interface SnapshotCandidate {\n39:   readonly seq: SessionSeq\n40:   readonly event: SessionEvent<'tool/result'>\n41: }\n42: \n43: /** Deterministic head/middle/tail pruning for current tool-result surface nodes. */\n44: export class ToolResultPruner extends Service {\n45:   // The token meter prices each shadowed node for its logged shadow-price\n46:   // event, so pruning genuinely requires the pricing capability.\n47:   static inject = ['tokenMeter']\n48: \n49:   static Config: z<ToolResultPruneConfig> = z.object({\n50:     thresholdChars: z.n\n\n[... 3159 more characters truncated]\n\n[Tool result]: <path>/tmp/dsh-lab/compaction/ws/packages/compaction/compaction-tool-result-pruner/src/config.ts</path>\n<type>file</type>\n<content>\n1: /** Configuration resolution for deterministic tool-result pruning. */\n2: \n3: import { deepFreeze } from '@deepseek-ai/dsh-util-values'\n4: import type { ResolvedConfig, ToolResultPruneConfig } from './types.ts'\n5: \n6: /** Fixed marker substituted for every removed middle span. */\n7: export const PRUNE_MARKER = '\\n\\n[... tool result middle pruned ...]\\n\\n'\n8: \n9: /** Low-friction defaults for coding-agent tool output. */\n10: export const DEFAULTS: ResolvedConfig = deepFreeze({\n11:   thresholdChars: 8192,\n12:   headChars: 4096,\n13:   tailChars: 1024,\n14: })\n15: \n16: const CONFIG_KEYS: ReadonlySet<string> = new Set([\n17:   'thresholdChars',\n18:   'headChars',\n19:   'tailChars',\n20: ])\n21: \n22: /**\n23:  * Count Unicode code points without splitting surrogate pairs.\n24:  * @param text - text to measure.\n25:  * @returns the Unicode code-point count.\n26:  */\n27: export function codePointLength(text: string): number {\n28:   return Array.from(text).length\n29: }\n30: \n31: /**\n32:  * Resolve and validate pruning budgets.\n33:  * @param config - raw plugin configuration.\n34:  * @returns a detached deeply immutable configuration.\n35:  */\n36: export function resolveConfig(config: ToolResultPruneConfig = {}): ResolvedConfig {\n37:   for (const key of Object.keys(config)) {\n38:     if (!CONFIG_KEYS.has(key)) {\n39:       throw new Error(\n40:         `ToolResultPruneConfig: unknown key \"${key}\" `\n41:         + '(allowed: thresholdChars, headChars, tailChars)',\n42:       )\n43:     }\n44:   }\n45: \n46:   const resolved: ResolvedConfig = {\n47:     thresholdChars: config.thresholdChars ?? DEFAULTS.thresholdChars,\n48:     headChars: config.headChars ?? DEFAULTS.headChars,\n49:     tailChars: config.tailChars ?? DEFAULTS.tailChars,\n50:   }\n51:   assertPositiveInteger('thresholdChars', resolved.thresholdChars)\n52:   assertNonNegativeInteger('headChars', resolved.h\n\n[... 1032 more characters truncated]\n</conversation>\n\nThe messages above are a conversation to summarize. Create a structured context checkpoint summary that another LLM will use to continue the work.\n\nUse this EXACT format:\n\n## Goal\n[What is the user trying to accomplish? Can be multiple items if the session covers different tasks.]\n\n## Constraints & Preferences\n- [Any constraints, preferences, or requirements mentioned by user]\n- [Or \"(none)\" if none were mentioned]\n\n## Progress\n### Done\n- [x] [Completed tasks/changes]\n\n### In Progress\n- [ ] [Current work]\n\n### Blocked\n- [Issues preventing progress, if any]\n\n## Key Decisions\n- **[Decision]**: [Brief rationale]\n\n## Next Steps\n1. [Ordered list of what should happen next]\n\n## Critical Context\n- [Any data, examples, or references needed to continue]\n- [Or \"(none)\" if not applicable]\n\nKeep each section concise. Preserve exact file paths, function names, and error messages."
        }
      ]
    }
  ]
}