Merge pull request #943 from PR0M3TH3AN/agents/daily/const-refactor-agent-6148832155416611801

[constants] extract memory service numeric literals to canonical modules

.scheduler-memory/latest/daily/memories.md

@@ -1,3 +1,6 @@
+### 1. [2026-02-27] (scheduler, daily, retrieve)
+
+Memory retrieval seed for daily :: Required startup + artifacts + memory + issue capture
 ### 1. [2026-02-28] (scheduler, daily, retrieve)
 
 # Memory Update (2026-02-25)

.scheduler-memory/memory-store.json

@@ -513,6 +513,12 @@
     }
   ],
   [
+    "094aab2a-4a25-4322-a198-1638752acc77",
+    {
+      "schema_version": 1,
+      "id": "094aab2a-4a25-4322-a198-1638752acc77",
+      "agent_id": "const-refactor-agent",
+      "session_id": "session-mm5d7amf",
     "c60afd2d-1325-4096-849a-77e11f2b5e39",
     {
       "schema_version": 1,
@@ -547,6 +553,8 @@
       ],
       "importance": 0.4,
       "embedding_id": null,
+      "created_at": 1772225327752,
+      "last_seen": 1772225327764,
       "created_at": 1772221041979,
       "last_seen": 1772221041993,
       "created_at": 1772218140227,
@@ -560,6 +568,12 @@
     }
   ],
   [
+    "cef905d0-7a66-459c-8937-41310afc934f",
+    {
+      "schema_version": 1,
+      "id": "cef905d0-7a66-459c-8937-41310afc934f",
+      "agent_id": "const-refactor-agent",
+      "session_id": "session-mm5dpefy",
     "9c49ca58-c6e5-4751-a3de-ab48bf7a4da1",
     {
       "schema_version": 1,
@@ -592,6 +606,8 @@
       ],
       "importance": 0.8,
       "embedding_id": null,
+      "created_at": 1772226172512,
+      "last_seen": 1772226172512,
       "created_at": 1772222021666,
       "last_seen": 1772222021666,
       "created_at": 1772218432277,

.scheduler-memory/session-mm5d7amf/retrieve.json

@@ -0,0 +1,18 @@
+{
+  "cadence": "daily",
+  "operation": "retrieve",
+  "runId": "session-mm5d7amf",
+  "servicePath": "src/services/memory/index.js#getRelevantMemories",
+  "inputs": {
+    "agentId": "const-refactor-agent",
+    "promptPath": "torch/src/prompts/daily/const-refactor-agent.md",
+    "promptIntent": "Required startup + artifacts + memory + issue capture",
+    "query": "scheduler | daily | agent | const-refactor-agent | intent | Required startup + artifacts + memory + issue capture",
+    "events": 1
+  },
+  "outputs": {
+    "ingestedCount": 1,
+    "retrievedCount": 1
+  },
+  "status": "ok"
+}

.scheduler-memory/session-mm5d7amf/retrieve.ok

@@ -0,0 +1 @@
+MEMORY_RETRIEVED

.scheduler-memory/session-mm5dpefy/store.json

@@ -0,0 +1,20 @@
+{
+  "cadence": "daily",
+  "operation": "store",
+  "runId": "session-mm5dpefy",
+  "servicePath": "src/services/memory/index.js#ingestEvents",
+  "inputs": {
+    "agentId": "const-refactor-agent",
+    "promptPath": "torch/src/prompts/daily/const-refactor-agent.md",
+    "promptIntent": "Required startup + artifacts + memory + issue capture",
+    "events": 1,
+    "sourceFile": "memory-update.md"
+  },
+  "outputs": {
+    "storedCount": 1,
+    "summaries": [
+      "# Memory Update — bug-reproducer-agent — 2026-02-27\n\n## Key findings\n- The `scheduler-flow.md` script execution failed due to a missing runner (`codex`).\n- The automated `bug-reproducer-agent` prompt execution failed.\n- Fallback manual investigation identified one active issue: …"
+    ]
+  },
+  "status": "ok"
+}

.scheduler-memory/session-mm5dpefy/store.ok

@@ -0,0 +1 @@
+MEMORY_STORED

reports/performance/constants-refactor/candidates.json

@@ -0,0 +1,58 @@
+[
+  {
+    "value": 1000,
+    "semantic": "one second in ms",
+    "occurrences": [
+      {"file": "torch/src/services/memory/index.js", "line": 45, "context": "const MIN_SAVE_INTERVAL_MS = 1000;"},
+      {"file": "torch/src/services/memory/pruner.js", "line": 3, "context": "const DAY_MS = 24 * 60 * 60 * 1000;"},
+      {"file": "torch/src/services/memory/retriever.js", "line": 8, "context": "const DEFAULT_RECENCY_HALF_LIFE_MS = 1000 * 60 * 60 * 24 * 7;"},
+      {"file": "torch/src/services/memory/formatter.js", "line": 3, "context": "const DEFAULT_TOKEN_BUDGET = 1000;"}
+    ]
+  },
+  {
+    "value": 60000,
+    "semantic": "one minute in ms (or 60_000)",
+    "occurrences": [
+      {"file": "torch/src/services/memory/index.js", "line": 548, "context": "windowMs / 60_000"},
+      {"file": "torch/src/services/memory/ingestor.js", "line": 6, "context": "const WINDOW_BUCKET_MS = 60_000;"},
+      {"file": "torch/src/services/memory/cache.js", "line": 153, "context": "setRuntimeEvent(scope, event, ttlMs = 60_000) {"},
+      {"file": "torch/src/services/memory/cache.js", "line": 157, "context": "const safeTtlMs = Number.isFinite(ttlMs) && ttlMs > 0 ? ttlMs : 60_000;"},
+      {"file": "torch/src/services/memory/scheduler.js", "line": 2, "context": "const MINUTE_MS = 60_000;"}
+    ]
+  },
+  {
+    "value": "24 * 60 * 60 * 1000",
+    "semantic": "one day in ms",
+    "occurrences": [
+      {"file": "torch/src/services/memory/pruner.js", "line": 3, "context": "const DAY_MS = 24 * 60 * 60 * 1000;"},
+      {"file": "torch/src/services/memory/index.js", "line": 329, "context": "const retentionMs = options.retentionMs ?? (1000 * 60 * 60 * 24 * 30);"},
+      {"file": "torch/src/services/memory/index.js", "line": 495, "context": "const retentionMs = options.retentionMs ?? (1000 * 60 * 60 * 24 * 30);"}
+    ]
+  },
+  {
+    "value": 280,
+    "semantic": "max summary chars length",
+    "occurrences": [
+      {"file": "torch/src/services/memory/pruner.js", "line": 116, "context": ".slice(0, 280)"},
+      {"file": "torch/src/services/memory/summarizer.js", "line": 116, "context": "const maxSummaryLength = options.maxSummaryLength ?? 280;"},
+      {"file": "torch/src/services/memory/ingestor.js", "line": 92, "context": "function compactContextExcerpt(text, maxChars = 280) {"}
+    ]
+  },
+  {
+    "value": 0.25,
+    "semantic": "default importance score",
+    "occurrences": [
+      {"file": "torch/src/services/memory/summarizer.js", "line": 64, "context": "Math.min(1, Math.max(0, rawImportance)) : 0.25;"},
+      {"file": "torch/src/services/memory/summarizer.js", "line": 72, "context": "return { summary: bounded, importance: 0.25 };"},
+      {"file": "torch/src/services/memory/retriever.js", "line": 3, "context": "w_imp: 0.25,"}
+    ]
+  },
+  {
+    "value": 0.35,
+    "semantic": "low importance / semantic overlap threshold",
+    "occurrences": [
+      {"file": "torch/src/services/memory/summarizer.js", "line": 89, "context": "return overlap / summaryTokens.length >= 0.35;"},
+      {"file": "torch/src/services/memory/pruner.js", "line": 184, "context": "lowImportanceThreshold: options.lowImportanceThreshold ?? 0.35,"}
+    ]
+  }
+]

reports/performance/constants-refactor/raw-numeric-hits.txt

@@ -0,0 +1,37 @@
+torch/src/services/memory/index.js:45:const MIN_SAVE_INTERVAL_MS = 1000;
+torch/src/services/memory/index.js:158:const ESTIMATED_INDEX_BYTES_PER_RECORD = 512;
+torch/src/services/memory/index.js:164:    if (typeof value === 'string' && value.length > 300) {
+torch/src/services/memory/index.js:165:      safe[key] = `${value.slice(0, 300)}…`;
+torch/src/services/memory/index.js:225:  if (samples.length > 10_000) {
+torch/src/services/memory/index.js:226:    samples.splice(0, samples.length - 10_000);
+torch/src/services/memory/index.js:324: * const result = await runPruneCycle({ retentionMs: 30 * 24 * 60 * 60 * 1000 });
+torch/src/services/memory/index.js:329:  const retentionMs = options.retentionMs ?? (1000 * 60 * 60 * 24 * 30);
+torch/src/services/memory/index.js:491: * const preview = await triggerPruneDryRun({ retentionMs: 7 * 24 * 60 * 60 * 1000 });
+torch/src/services/memory/index.js:495:  const retentionMs = options.retentionMs ?? (1000 * 60 * 60 * 24 * 30);
+torch/src/services/memory/index.js:530: * const stats = await memoryStats({ windowMs: 60 * 60 * 1000 });
+torch/src/services/memory/index.js:535:  const windowMs = Number.isFinite(options.windowMs) ? Math.max(1, Number(options.windowMs)) : (60 * 60 * 1000);
+torch/src/services/memory/index.js:548:  const ingestThroughputPerMinute = ingestedInWindow / Math.max(1, (windowMs / 60_000));
+torch/src/services/memory/pruner.js:3:const DAY_MS = 24 * 60 * 60 * 1000;
+torch/src/services/memory/pruner.js:116:  const fallbackSummary = group.map((item) => item.summary || item.content).filter(Boolean).join(' ').slice(0, 280);
+torch/src/services/memory/pruner.js:184:    lowImportanceThreshold: options.lowImportanceThreshold ?? 0.35,
+torch/src/services/memory/pruner.js:185:    deleteImportanceThreshold: options.deleteImportanceThreshold ?? 0.12,
+torch/src/services/memory/summarizer.js:64:    : 0.25;
+torch/src/services/memory/summarizer.js:72:  return { summary: bounded, importance: 0.25 };
+torch/src/services/memory/summarizer.js:89:  return overlap / summaryTokens.length >= 0.35;
+torch/src/services/memory/summarizer.js:116:  const maxSummaryLength = options.maxSummaryLength ?? 280;
+torch/src/services/memory/ingestor.js:6:const WINDOW_BUCKET_MS = 60_000;
+torch/src/services/memory/ingestor.js:37:    : 300;
+torch/src/services/memory/ingestor.js:92:function compactContextExcerpt(text, maxChars = 280) {
+torch/src/services/memory/retriever.js:2:  w_sim: 0.6,
+torch/src/services/memory/retriever.js:3:  w_imp: 0.25,
+torch/src/services/memory/retriever.js:4:  w_rec: 0.15,
+torch/src/services/memory/retriever.js:5:  pinBoost: 0.15,
+torch/src/services/memory/retriever.js:8:const DEFAULT_RECENCY_HALF_LIFE_MS = 1000 * 60 * 60 * 24 * 7;
+torch/src/services/memory/formatter.js:3:const DEFAULT_TOKEN_BUDGET = 1000;
+torch/src/services/memory/cache.js:2:const DEFAULT_MAX_EVENTS_PER_NAMESPACE = 200;
+torch/src/services/memory/cache.js:3:const DEFAULT_MAX_TOTAL_EVENTS = 5000;
+torch/src/services/memory/cache.js:153:    setRuntimeEvent(scope, event, ttlMs = 60_000) {
+torch/src/services/memory/cache.js:157:      const safeTtlMs = Number.isFinite(ttlMs) && ttlMs > 0 ? ttlMs : 60_000;
+torch/src/services/memory/scheduler.js:2:const MINUTE_MS = 60_000;
+torch/src/services/memory/scheduler.js:3:const HOUR_MS = 60 * MINUTE_MS;
+torch/src/services/memory/scheduler.js:4:const DAY_MS = 24 * HOUR_MS;

src/context/CONTEXT_1772225357.md

@@ -0,0 +1,2 @@
+Fri Feb 27 20:49:17 UTC 2026
+Exploring duplicated constants in js/

src/decisions/DECISIONS_1772226155.md

@@ -0,0 +1,7 @@
+## Decisions
+
+- **Domain-specific constants vs Global**: The constants were found specifically within `torch/src/services/memory/`. Therefore, I created `torch/src/services/memory/constants/` rather than a global `src/constants.js`.
+- **Time constants**: Created `time.js` for `SECOND_MS`, `MINUTE_MS`, `HOUR_MS`, `DAY_MS`, `WEEK_MS`, `MONTH_MS`.
+- **Text constants**: Created `text.js` for `MAX_SUMMARY_LENGTH`.
+- **Scoring constants**: Created `scoring.js` for `DEFAULT_IMPORTANCE_SCORE` and `LOW_IMPORTANCE_THRESHOLD`.
+- Replaced literals in `index.js`, `pruner.js`, `retriever.js`, `ingestor.js`, `summarizer.js`, `cache.js`, `scheduler.js`.

src/test_logs/TEST_LOG_1772226155.md

@@ -0,0 +1 @@
+Ran `npm run --prefix torch lint` and verified that there are no linter errors.

src/todo/TODO_1772226155.md

@@ -0,0 +1,10 @@
+## Constants Refactoring TODOs
+
+1. `1000` (second in ms): Replaced with `SECOND_MS`
+2. `60000` (minute in ms): Replaced with `MINUTE_MS`
+3. `24 * 60 * 60 * 1000` (day in ms): Replaced with `DAY_MS`
+4. `280` (max summary length): Replaced with `MAX_SUMMARY_LENGTH`
+5. `0.25` (default importance): Replaced with `DEFAULT_IMPORTANCE_SCORE`
+6. `0.35` (low importance threshold): Replaced with `LOW_IMPORTANCE_THRESHOLD`
+
+Status: All complete. Constants extracted to `torch/src/services/memory/constants/`.

torch/src/services/memory/cache.js

@@ -1,3 +1,5 @@
+import { MINUTE_MS } from './constants/time.js';
+
 const DEFAULT_MAX_NAMESPACES = 128;
 const DEFAULT_MAX_EVENTS_PER_NAMESPACE = 200;
 const DEFAULT_MAX_TOTAL_EVENTS = 5000;
@@ -150,11 +152,11 @@ export function createMemoryCache(options = {}) {
       runtimeNamespaces.clear();
       totalRuntimeEvents = 0;
     },
-    setRuntimeEvent(scope, event, ttlMs = 60_000) {
+    setRuntimeEvent(scope, event, ttlMs = MINUTE_MS) {
       const now = Date.now();
       removeExpired(now);
 
-      const safeTtlMs = Number.isFinite(ttlMs) && ttlMs > 0 ? ttlMs : 60_000;
+      const safeTtlMs = Number.isFinite(ttlMs) && ttlMs > 0 ? ttlMs : MINUTE_MS;
       const expiresAt = now + safeTtlMs;
       const namespaceKey = getNamespaceKey(scope);
       const bucket = runtimeNamespaces.get(namespaceKey) ?? { events: [] };

torch/src/services/memory/constants/scoring.js

@@ -0,0 +1,2 @@
+export const DEFAULT_IMPORTANCE_SCORE = 0.25;
+export const LOW_IMPORTANCE_THRESHOLD = 0.35;

torch/src/services/memory/constants/text.js

@@ -0,0 +1 @@
+export const MAX_SUMMARY_LENGTH = 280;

torch/src/services/memory/constants/time.js

@@ -0,0 +1,6 @@
+export const SECOND_MS = 1000;
+export const MINUTE_MS = 60 * SECOND_MS;
+export const HOUR_MS = 60 * MINUTE_MS;
+export const DAY_MS = 24 * HOUR_MS;
+export const WEEK_MS = 7 * DAY_MS;
+export const MONTH_MS = 30 * DAY_MS;

torch/src/services/memory/index.js

@@ -42,7 +42,9 @@ let currentSavePromise = null;
 let pendingSavePromise = null;
 let pendingSaveResolve = null;
 let lastSaveTime = 0;
-const MIN_SAVE_INTERVAL_MS = 1000;
+import { SECOND_MS, MONTH_MS, MINUTE_MS } from './constants/time.js';
+
+const MIN_SAVE_INTERVAL_MS = SECOND_MS;
 
 async function performSave(store) {
   try {
@@ -326,7 +328,7 @@ export async function getRelevantMemories(params) {
 export async function runPruneCycle(options = {}) {
   const repository = options.repository ?? memoryRepository;
   const telemetry = buildTelemetryEmitter(options);
-  const retentionMs = options.retentionMs ?? (1000 * 60 * 60 * 24 * 30);
+  const retentionMs = options.retentionMs ?? MONTH_MS;
   const pruneMode = options.pruneMode ?? getMemoryPruneMode(options.env);
   const dbCandidates = await listPruneCandidates(repository, {
     retentionMs,
@@ -492,7 +494,7 @@ export async function inspectMemory(id, options = {}) {
  */
 export async function triggerPruneDryRun(options = {}) {
   const repository = options.repository ?? memoryRepository;
-  const retentionMs = options.retentionMs ?? (1000 * 60 * 60 * 24 * 30);
+  const retentionMs = options.retentionMs ?? MONTH_MS;
   const dbCandidates = await listPruneCandidates(repository, {
     retentionMs,
     now: options.now,
@@ -532,7 +534,7 @@ export async function triggerPruneDryRun(options = {}) {
 export async function memoryStats(options = {}) {
   const repository = options.repository ?? memoryRepository;
   const now = options.now ?? Date.now();
-  const windowMs = Number.isFinite(options.windowMs) ? Math.max(1, Number(options.windowMs)) : (60 * 60 * 1000);
+  const windowMs = Number.isFinite(options.windowMs) ? Math.max(1, Number(options.windowMs)) : (60 * MINUTE_MS);
   const memories = await listMemories({}, { repository });
 
   const countsByType = memories.reduce((acc, memory) => {
@@ -545,7 +547,7 @@ export async function memoryStats(options = {}) {
   const archivedRate = archivedCount / Math.max(1, memories.length);
 
   const ingestedInWindow = memoryStatsState.ingested.filter((timestamp) => timestamp >= (now - windowMs)).length;
-  const ingestThroughputPerMinute = ingestedInWindow / Math.max(1, (windowMs / 60_000));
+  const ingestThroughputPerMinute = ingestedInWindow / Math.max(1, (windowMs / MINUTE_MS));
 
   return {
     countsByType,

torch/src/services/memory/ingestor.js

@@ -2,8 +2,10 @@ import { createHash, randomUUID } from 'node:crypto';
 import { createMemoryRecord, normalizeEvent, validateMemoryItem } from './schema.js';
 import { embedText, getDefaultEmbedderAdapter } from './embedder.js';
 import { summarizeEvents } from './summarizer.js';
+import { MINUTE_MS } from './constants/time.js';
+import { MAX_SUMMARY_LENGTH } from './constants/text.js';
 
-const WINDOW_BUCKET_MS = 60_000;
+const WINDOW_BUCKET_MS = MINUTE_MS;
 const MAX_DEDUPE_KEYS = 2000;
 const dedupeWindow = new Map();
 
@@ -89,7 +91,7 @@ async function rememberWindowFingerprint(repository, dedupeKey, payload) {
 }
 
 
-function compactContextExcerpt(text, maxChars = 280) {
+function compactContextExcerpt(text, maxChars = MAX_SUMMARY_LENGTH) {
   if (typeof text !== 'string' || text.length === 0) return '';
   const compact = text.replace(/\s+/g, ' ').trim();
   if (compact.length <= maxChars) return compact;

torch/src/services/memory/pruner.js

@@ -1,6 +1,7 @@
 import { loadMemoryPromptTemplates } from './summarizer.js';
-
-const DAY_MS = 24 * 60 * 60 * 1000;
+import { DAY_MS } from './constants/time.js';
+import { MAX_SUMMARY_LENGTH } from './constants/text.js';
+import { LOW_IMPORTANCE_THRESHOLD } from './constants/scoring.js';
 
 /**
  * @typedef {'keep' | 'archive' | 'delete'} LifecycleAction
@@ -113,7 +114,7 @@ function groupNearDuplicates(memories, options) {
  */
 async function condenseGroup(group, generateSummary, condenseTemplate) {
   const [primary, ...rest] = group;
-  const fallbackSummary = group.map((item) => item.summary || item.content).filter(Boolean).join(' ').slice(0, 280);
+  const fallbackSummary = group.map((item) => item.summary || item.content).filter(Boolean).join(' ').slice(0, MAX_SUMMARY_LENGTH);
   const fallback = {
     summary: fallbackSummary || primary.summary,
     importance: Math.max(...group.map((item) => item.importance)),
@@ -181,7 +182,7 @@ export async function createLifecyclePlan(memories, options) {
   const policy = {
     now,
     retentionMs: options.retentionMs,
-    lowImportanceThreshold: options.lowImportanceThreshold ?? 0.35,
+    lowImportanceThreshold: options.lowImportanceThreshold ?? LOW_IMPORTANCE_THRESHOLD,
     deleteImportanceThreshold: options.deleteImportanceThreshold ?? 0.12,
     recentUsageMs: options.recentUsageMs ?? Math.max(Math.floor(options.retentionMs / 2), DAY_MS),
     duplicateWindowMs: options.duplicateWindowMs ?? (7 * DAY_MS),

torch/src/services/memory/retriever.js

@@ -1,11 +1,14 @@
+import { WEEK_MS } from './constants/time.js';
+import { DEFAULT_IMPORTANCE_SCORE } from './constants/scoring.js';
+
 const DEFAULT_WEIGHTS = {
   w_sim: 0.6,
-  w_imp: 0.25,
+  w_imp: DEFAULT_IMPORTANCE_SCORE,
   w_rec: 0.15,
   pinBoost: 0.15,
 };
 
-const DEFAULT_RECENCY_HALF_LIFE_MS = 1000 * 60 * 60 * 24 * 7;
+const DEFAULT_RECENCY_HALF_LIFE_MS = WEEK_MS;
 
 function cosineSimilarity(left = [], right = []) {
   const size = Math.max(left.length, right.length);

torch/src/services/memory/scheduler.js

@@ -1,8 +1,5 @@
 import { getMemoryPruneMode, isMemoryEnabled, isMemoryIngestEnabled } from './feature-flags.js';
-const MINUTE_MS = 60_000;
-const HOUR_MS = 60 * MINUTE_MS;
-const DAY_MS = 24 * HOUR_MS;
-const WEEK_MS = 7 * DAY_MS;
+import { MINUTE_MS, HOUR_MS, DAY_MS, WEEK_MS } from './constants/time.js';
 
 const JOBS = {
   ingestRecentRuntimeEvents: {

torch/src/services/memory/summarizer.js

@@ -1,6 +1,8 @@
 import { readFileSync } from 'node:fs';
 import path from 'node:path';
 import { fileURLToPath } from 'node:url';
+import { MAX_SUMMARY_LENGTH } from './constants/text.js';
+import { DEFAULT_IMPORTANCE_SCORE, LOW_IMPORTANCE_THRESHOLD } from './constants/scoring.js';
 
 const __filename = fileURLToPath(import.meta.url);
 const __dirname = path.dirname(__filename);
@@ -61,7 +63,7 @@ function parseSummaryPayload(rawResponse) {
   const rawImportance = Number(parsed.importance);
   const importance = Number.isFinite(rawImportance)
     ? Math.min(1, Math.max(0, rawImportance))
-    : 0.25;
+    : DEFAULT_IMPORTANCE_SCORE;
 
   return { summary, importance };
 }
@@ -69,7 +71,7 @@ function parseSummaryPayload(rawResponse) {
 function deterministicFallback(events, maxSummaryLength) {
   const joined = events.map((event) => redactObviousPii(event.content)).join(' ').trim();
   const bounded = joined.length > maxSummaryLength ? `${joined.slice(0, maxSummaryLength - 1)}…` : joined;
-  return { summary: bounded, importance: 0.25 };
+  return { summary: bounded, importance: DEFAULT_IMPORTANCE_SCORE };
 }
 
 function isLikelyFactual(summary, sourceText) {
@@ -86,7 +88,7 @@ function isLikelyFactual(summary, sourceText) {
 
   if (!summaryTokens.length) return true;
   const overlap = summaryTokens.filter((token) => sourceTokens.has(token)).length;
-  return overlap / summaryTokens.length >= 0.35;
+  return overlap / summaryTokens.length >= LOW_IMPORTANCE_THRESHOLD;
 }
 
 function sanitizeResult(parsed, sourceText, maxSummaryLength, fallback) {
@@ -113,7 +115,7 @@ function sanitizeResult(parsed, sourceText, maxSummaryLength, fallback) {
  * @returns {Promise<{ summary: string, importance: number }>}
  */
 export async function summarizeEvents(events, options = {}) {
-  const maxSummaryLength = options.maxSummaryLength ?? 280;
+  const maxSummaryLength = options.maxSummaryLength ?? MAX_SUMMARY_LENGTH;
   const fallback = deterministicFallback(events, maxSummaryLength);
   if (!fallback.summary) return fallback;
 

torch/task-logs/daily/2026-02-27T21-08-43Z__const-refactor-agent__completed.md

@@ -0,0 +1 @@
+completed