chore(minecraft): rename planner to repl naming

services/minecraft/codex-skills/minecraft-debug-mcp/SKILL.md

@@ -36,7 +36,7 @@ Use this skill to run the local bot and interact with its MCP debug interface sa
 - Use `get_last_prompt` to inspect latest LLM input.
 - Use `execute_repl` for deep object inspection or one-off targeted calls on the running brain.
 - Use `inject_chat` to simulate player chat and verify behavior loop.
-- Use `get_llm_trace` to assert planner behavior in automation (for example, detect repeated `await skip()` on specific events).
+- Use `get_llm_trace` to assert REPL behavior in automation (for example, detect repeated `await skip()` on specific events).
 - Use `execute_repl("forget_conversation()")` to clear conversation memory before prompt-engineering tests.
 
 Read `references/mcp-surface.md` for exact tool/resource names and argument schemas.
@@ -46,7 +46,7 @@ Read `references/mcp-surface.md` for exact tool/resource names and argument sche
 - `get_state` returns a large variable snapshot; prefer it over REPL for first-pass health checks.
 - `get_last_prompt` can return very large payloads; call only when prompt-level debugging is needed.
 - `execute_repl` returns a structured result where `returnValue` is stringified; parse mentally as display output, not typed JSON.
-- `get_logs(limit=10)` is enough to verify whether an injected event reached planner/executor.
+- `get_logs(limit=10)` is enough to verify whether an injected event reached REPL/executor.
 - `get_llm_trace(limit, turnId?)` gives structured attempt-level trace data (messages, content, reasoning, usage, duration).
 - `get_last_prompt` and `get_llm_trace` are compacted for MCP: system prompt/system-role messages are omitted to reduce token cost.
 - Prefer compact value reads in REPL:
@@ -69,7 +69,7 @@ Read `references/mcp-surface.md` for exact tool/resource names and argument sche
    - Call `get_logs(limit=10)` and check for:
      - bot acknowledgement chat
      - action tool feedback (for example `collectBlocks`)
-     - planner result summary
+     - REPL result summary
    - Call `get_llm_trace(limit=5)` when you need exact model output/reasoning for assertions.
 5. Re-check inventory using the same REPL snippet and compare against baseline.
 

services/minecraft/codex-skills/minecraft-debug-mcp/references/mcp-surface.md

@@ -80,7 +80,7 @@ The bot starts this server during normal runtime from:
 - Log verification pattern that worked reliably:
   1. `inject_chat(...)`
   2. `get_logs(limit: 10)`
-  3. Confirm sequence: `turn_input` -> `llm_attempt` -> `feedback` -> `planner_result`
+  3. Confirm sequence: `turn_input` -> `llm_attempt` -> `feedback` -> `repl_result`
 
 ## Repeatable Smoke Test Recipe
 
@@ -95,7 +95,7 @@ Use this exact sequence for fast live validation:
    - `inject_chat({ username: \"codex-live-test\", message: \"please gather 3 dirt blocks\" })`
 3. Execution proof
    - `get_logs({ limit: 10 })`
-   - Expect acknowledgement chat + `collectBlocks` success feedback + planner summary.
+   - Expect acknowledgement chat + `collectBlocks` success feedback + REPL summary.
    - `get_llm_trace({ limit: 5 })`
    - Assert expected LLM behavior (for example response code, or repeated `await skip()`).
    - Assert trace payload does not include `role: "system"` entries.
@@ -106,7 +106,7 @@ Use this exact sequence for fast live validation:
 
 To validate read->action behavior:
 1. Inject a query-style chat (for example inventory question).
-2. Confirm first planner result is no-action with concrete return value (via `get_logs`/`get_llm_trace`).
+2. Confirm first REPL result is no-action with concrete return value (via `get_logs`/`get_llm_trace`).
 3. Confirm follow-up turn uses that returned value to perform chat/action.
 
 ## Runtime Caveat

services/minecraft/src/cognitive/conscious/brain.ts

@@ -41,7 +41,7 @@ interface QueuedEvent {
   reject: (err: Error) => void
 }
 
-interface PlannerOutcomeSummary {
+interface ReplOutcomeSummary {
   actionCount: number
   okCount: number
   errorCount: number
@@ -165,7 +165,7 @@ function getEventPriority(event: BotEvent): number {
 
 export class Brain {
   private debugService: DebugService
-  private readonly planner = new JavaScriptPlanner()
+  private readonly repl = new JavaScriptPlanner()
   private paused = false
 
   // State
@@ -176,7 +176,7 @@ export class Brain {
   private giveUpUntil = 0
   private giveUpReason: string | undefined
   private lastContextView: string | undefined
-  private lastPlannerOutcome: PlannerOutcomeSummary | undefined
+  private lastReplOutcome: ReplOutcomeSummary | undefined
   private conversationHistory: Message[] = []
   private lastLlmInputSnapshot: LlmInputSnapshot | null = null
   private runtimeMineflayer: MineflayerWithAgents | null = null
@@ -280,7 +280,7 @@ export class Brain {
       source: { type: 'system', id: 'debug-repl' },
       timestamp: Date.now(),
     }
-    const variables = this.planner.describeGlobals(
+    const variables = this.repl.describeGlobals(
       this.deps.taskExecutor.getAvailableActions(),
       this.createRuntimeGlobals(replEvent, snapshot as unknown as Record<string, unknown>),
     )
@@ -400,13 +400,13 @@ export class Brain {
     const snapshot = this.deps.reflexManager.getContextSnapshot()
     const actionDefs = new Map(this.deps.taskExecutor.getAvailableActions().map(action => [action.name, action]))
     const normalizedReplCode = this.normalizeReplCode(code)
-    const codeToEvaluate = this.planner.canEvaluateAsExpression(normalizedReplCode)
+    const codeToEvaluate = this.repl.canEvaluateAsExpression(normalizedReplCode)
       ? `return (\n${normalizedReplCode}\n)`
       : normalizedReplCode
 
     this.isReplEvaluating = true
     try {
-      const runResult = await this.planner.evaluate(
+      const runResult = await this.repl.evaluate(
         codeToEvaluate,
         this.deps.taskExecutor.getAvailableActions(),
         this.createRuntimeGlobals({
@@ -910,11 +910,11 @@ export class Brain {
       this.deps.logger.withError(lastError).warn('Brain: No response after all retries')
       this.appendLlmLog({
         turnId,
-        kind: 'planner_error',
+        kind: 'repl_error',
         eventType: event.type,
         sourceType: event.source.type,
         sourceId: event.source.id,
-        tags: ['planner', 'error', 'empty_response'],
+        tags: ['repl', 'error', 'empty_response'],
         text: 'No LLM response after retries',
       })
       return
@@ -934,11 +934,12 @@ export class Brain {
       const actionDefs = new Map(this.deps.taskExecutor.getAvailableActions().map(action => [action.name, action]))
       let turnCancellationToken: CancellationToken | undefined
 
-      const codeToEvaluate = this.planner.canEvaluateAsExpression(result)
-        ? `return (\n${result}\n)`
-        : this.rewriteTrailingExpressionToReturn(result)
+      const normalizedLlmCode = this.normalizeReplCode(result)
+      const codeToEvaluate = this.repl.canEvaluateAsExpression(normalizedLlmCode)
+        ? `return (\n${normalizedLlmCode}\n)`
+        : normalizedLlmCode
 
-      const runResult = await this.planner.evaluate(
+      const runResult = await this.repl.evaluate(
         codeToEvaluate,
         this.deps.taskExecutor.getAvailableActions(),
         this.createRuntimeGlobals(event, snapshot as unknown as Record<string, unknown>, bot),
@@ -962,7 +963,7 @@ export class Brain {
         },
       )
 
-      this.lastPlannerOutcome = {
+      this.lastReplOutcome = {
         actionCount: runResult.actions.length,
         okCount: runResult.actions.filter(item => item.ok).length,
         errorCount: runResult.actions.filter(item => !item.ok).length,
@@ -972,12 +973,12 @@ export class Brain {
       }
       this.appendLlmLog({
         turnId,
-        kind: 'planner_result',
+        kind: 'repl_result',
         eventType: event.type,
         sourceType: event.source.type,
         sourceId: event.source.id,
         tags: [
-          'planner',
+          'repl',
           runResult.actions.length === 0 ? 'no_actions' : 'actions',
           runResult.actions.some(item => !item.ok) ? 'error' : 'ok',
         ],
@@ -1038,11 +1039,11 @@ export class Brain {
       this.deps.logger.withError(err).error('Brain: Failed to execute decision')
       this.appendLlmLog({
         turnId,
-        kind: 'planner_error',
+        kind: 'repl_error',
         eventType: event.type,
         sourceType: event.source.type,
         sourceId: event.source.id,
-        tags: ['planner', 'error'],
+        tags: ['repl', 'error'],
         text: truncateForPrompt(toErrorMessage(err), 360),
         metadata: {
           code: result,
@@ -1105,13 +1106,13 @@ export class Brain {
       parts.push(`[STATE] giveUp active (${remainingSec}s left). reason=${this.giveUpReason ?? 'unknown'}`)
     }
 
-    if (this.lastPlannerOutcome) {
-      const ageMs = Date.now() - this.lastPlannerOutcome.updatedAt
-      const returnValue = truncateForPrompt(this.lastPlannerOutcome.returnValue ?? 'undefined')
-      const logs = this.lastPlannerOutcome.logs.length > 0
-        ? this.lastPlannerOutcome.logs.map((line, index) => `#${index + 1} ${truncateForPrompt(line, 120)}`).join(' | ')
+    if (this.lastReplOutcome) {
+      const ageMs = Date.now() - this.lastReplOutcome.updatedAt
+      const returnValue = truncateForPrompt(this.lastReplOutcome.returnValue ?? 'undefined')
+      const logs = this.lastReplOutcome.logs.length > 0
+        ? this.lastReplOutcome.logs.map((line, index) => `#${index + 1} ${truncateForPrompt(line, 120)}`).join(' | ')
         : '(none)'
-      parts.push(`[SCRIPT] Last eval ${ageMs}ms ago: return=${returnValue}; actions=${this.lastPlannerOutcome.actionCount} (ok=${this.lastPlannerOutcome.okCount}, err=${this.lastPlannerOutcome.errorCount}); logs=${logs}`)
+      parts.push(`[SCRIPT] Last eval ${ageMs}ms ago: return=${returnValue}; actions=${this.lastReplOutcome.actionCount} (ok=${this.lastReplOutcome.okCount}, err=${this.lastReplOutcome.errorCount}); logs=${logs}`)
     }
 
     parts.push('[RUNTIME] Globals are refreshed every turn: snapshot, self, environment, social, threat, attention, autonomy, event, now, query, bot, mineflayer, currentInput, llmLog, mem, lastRun, prevRun, lastAction. Player gaze is available in environment.nearbyPlayersGaze when needed.')

services/minecraft/src/cognitive/conscious/llm-log.test.ts

@@ -8,12 +8,12 @@ function seedEntries(count: number): LlmLogEntry[] {
   return Array.from({ length: count }, (_, index) => ({
     id: index + 1,
     turnId: Math.floor(index / 2) + 1,
-    kind: index % 3 === 0 ? 'planner_error' : 'turn_input',
+    kind: index % 3 === 0 ? 'repl_error' : 'turn_input',
     timestamp: 1000 + index,
     eventType: 'perception',
     sourceType: 'minecraft',
     sourceId: index % 2 === 0 ? 'Alex' : 'Steve',
-    tags: index % 3 === 0 ? ['error', 'planner'] : ['input'],
+    tags: index % 3 === 0 ? ['error', 'repl'] : ['input'],
     text: index % 3 === 0 ? 'Invalid tool parameters' : 'Chat event',
     metadata: { i: index },
   }))

services/minecraft/src/cognitive/conscious/llm-log.ts

@@ -1,8 +1,8 @@
 export type LlmLogEntryKind
   = 'turn_input'
     | 'llm_attempt'
-    | 'planner_result'
-    | 'planner_error'
+    | 'repl_result'
+    | 'repl_error'
     | 'scheduler'
     | 'feedback'