feat(chat): inject profile, lessons, and crystal ranking factors

src/agent-harness/answer-context.test.ts

@@ -53,6 +53,38 @@ describe("composeAnswerContext", () => {
     })
   })
 
+  it("puts profile and lessons before knowledge and memory", async () => {
+    const message = await composeAnswerContext({
+      ledger: {
+        ...makeLedger(),
+        retrievalCount: 0,
+        chunks: [],
+        evidence: [],
+      },
+      memoryItems: [],
+      profile: { occupation: "教师" },
+      agentFeedbackLessons: [
+        {
+          itemId: "fb_1",
+          text: "查毛利率 引用错了",
+          reflection: "下次先核对引用",
+        },
+      ],
+      userText: "再查一次",
+    })
+
+    const text = userContentParts(message)
+      .filter((part) => part.type === "text")
+      .map((part) => part.text)
+      .join("\n")
+    expect(text.indexOf("## User Profile")).toBeLessThan(
+      text.indexOf("## Lessons from Past Mistakes"),
+    )
+    expect(text).toContain("occupation: 教师")
+    expect(text).toContain("下次先核对引用")
+    expect(text).toContain("## User's Question")
+  })
+
   it("omits knowledge and memory sections when neither search ran", async () => {
     const message = await composeAnswerContext({
       ledger: {

src/agent-harness/answer-context.ts

@@ -1,9 +1,11 @@
 import type { ModelMessage } from "ai"
 
 import type {
+  AgentFeedbackLesson,
   EvidenceLedgerSnapshot,
   EvidencePart,
   MemorySearchItem,
+  WorkspaceProfile,
 } from "./types"
 
 type UserContentParts = Exclude<
@@ -16,9 +18,26 @@ export async function composeAnswerContext(input: {
   readonly memoryItems: readonly MemorySearchItem[]
   readonly memorySearchAttempted?: boolean
   readonly userText: string
+  readonly profile?: WorkspaceProfile | null
+  readonly agentFeedbackLessons?: readonly AgentFeedbackLesson[]
 }): Promise<ModelMessage> {
   const content: UserContentParts = []
 
+  const profileText = formatProfile(input.profile)
+  if (profileText) {
+    appendText(content, `## User Profile\n${profileText}`)
+  }
+
+  if (input.agentFeedbackLessons && input.agentFeedbackLessons.length > 0) {
+    appendText(
+      content,
+      [
+        "## Lessons from Past Mistakes",
+        ...input.agentFeedbackLessons.map(formatLesson),
+      ].join("\n\n"),
+    )
+  }
+
   if (input.ledger.evidence.length === 0 && input.ledger.retrievalCount > 0) {
     appendText(
       content,
@@ -93,6 +112,28 @@ function appendRawText(content: UserContentParts, text: string): void {
   content.push({ type: "text", text })
 }
 
+function formatProfile(profile: WorkspaceProfile | null | undefined): string | null {
+  if (!profile) return null
+  const lines = (
+    [
+      ["name", profile.name],
+      ["occupation", profile.occupation],
+      ["ageStage", profile.ageStage],
+      ["communicationHabit", profile.communicationHabit],
+      ["workHabit", profile.workHabit],
+    ] as const
+  ).flatMap(([key, value]) =>
+    value && value.length > 0 ? [`${key}: ${value}`] : [],
+  )
+  return lines.length > 0 ? lines.join("\n") : null
+}
+
+function formatLesson(lesson: AgentFeedbackLesson): string {
+  return [lesson.text.trim(), lesson.reflection.trim()]
+    .filter((part) => part.length > 0)
+    .join("\n")
+}
+
 function formatMemoryItem(item: MemorySearchItem): string {
   return [
     `[memory ref="${item.ref}" kind="${item.kind}"]`,

src/agent-harness/runtime.ts

@@ -14,6 +14,7 @@ import { createEvidenceLedger } from "./ledger"
 import { knowhereToolText } from "./knowhere-text"
 import { memoryToolText } from "./memory-text"
 import type {
+  AgentFeedbackLesson,
   AgentTurn,
   AgentTurnInput,
   ContextPolicy,
@@ -32,6 +33,7 @@ import type {
   OutputCitation,
   OutputManifest,
   ResolveConnectedAssets,
+  WorkspaceProfile,
 } from "./types"
 import { memorySearchKinds } from "./types"
 
@@ -49,6 +51,8 @@ export type RunAgentHarnessInput = {
   readonly memoryTools: MemoryToolRuntime
   readonly resolveConnectedAssets?: ResolveConnectedAssets
   readonly maxSteps?: number
+  readonly profile?: WorkspaceProfile | null
+  readonly agentFeedbackLessons?: readonly AgentFeedbackLesson[]
 }
 
 type HarnessToolState = {
@@ -220,6 +224,8 @@ export async function runAgentHarness(
           memoryItems: state.memoryItems ?? [],
           memorySearchAttempted: state.memorySearchAttempted === true,
           userText: input.turn.userText,
+          profile: input.profile,
+          agentFeedbackLessons: input.agentFeedbackLessons,
         })
         await ledger.resolveConnectedAssets(input.resolveConnectedAssets)
       }
@@ -250,6 +256,7 @@ export async function runAgentHarness(
   const ledgerSnapshot = ledger.snapshot()
   return {
     manifest,
+    memoryItems: state.memoryItems ?? [],
     trace: {
       intent: state.intent,
       contextPolicy: state.contextPolicy,

src/agent-harness/types.ts

@@ -147,6 +147,20 @@ export type MemoryToolRuntime = {
   readonly search: (input: MemorySearchRequest) => Promise<MemorySearchResponse>
 }
 
+export type WorkspaceProfile = {
+  readonly name?: string
+  readonly occupation?: string
+  readonly ageStage?: string
+  readonly communicationHabit?: string
+  readonly workHabit?: string
+}
+
+export type AgentFeedbackLesson = {
+  readonly itemId: string
+  readonly text: string
+  readonly reflection: string
+}
+
 export type MemoryCitation = {
   readonly ref: string
   readonly itemId: string
@@ -316,4 +330,5 @@ export type HarnessTrace = {
 export type HarnessRunResult = {
   readonly manifest: OutputManifest
   readonly trace: HarnessTrace
+  readonly memoryItems: readonly MemorySearchItem[]
 }