feat(v0.3.0): paradigm shift — TimeWeb-only LLM + persistent advisor trail + improvement queue
This is the rc.4 batch the user requested:
1. Emergency triggers (low HP + close hostile, lava-under-foot)
bypass the long cooldown so the LLM is consulted BEFORE the bot
dies, not after.
2. Active manifesto need is now included in the advisor user prompt
— the LLM picks suggestions that satisfy the bot's current
concrete need (L2 tools_wood → "gather logs nearby" not
"explore further").
3. Every advisor recommendation is persisted to SQLite
(advisor_recommendations table) with full token usage. The
reflex marks 'applied=1' when it dispatches and updates
outcome_ok/code when the dispatch completes. Ground truth for
"is the LLM actually helping" lives in the DB, not in logs.
4. Pi CLI is OUT of every background loop. coach/postmortem and
coach/reflect now go through the same TimeWeb endpoint
fast-advisor uses, via the shared coach/llm-call.js helper.
Pi is reserved for manual operator commands.
5. The LLM (postmortem, reflect, advisor) can flag "structural
gaps" — missing skills/features the operator should implement.
These land in the new improvement_requests table. Dedup by
title bumps `votes` instead of inserting duplicates so the
queue doesn't bloat. Operator views via
`node scripts/list-improvements.js`.
6. A deterministic trigger-tuner runs hourly: reads 24h of
recommendation stats, flags triggers whose success rate is
below 25% (sample ≥ 5) or whose prompts are expensive (>1000
input tokens) with mediocre payoff. Improvements get
source="tuner", category="tuning". No LLM call.
New files:
runtime/coach/llm-call.js — askAnalytical() helper
runtime/coach/trigger-tuner.js — stats → improvements
runtime/coach/trigger-tuner.test.js
scripts/list-improvements.js — operator CLI
Schema additions:
advisor_recommendations: id, ts, trigger_reason, planned_skill,
recommended_skill, action, rationale, active_need, tokens_in,
tokens_out, latency_ms, applied, outcome_ok, outcome_code, outcome_at
improvement_requests: id, ts, source, category, title, description,
context, priority, status, duplicate_of, votes, implemented_at, notes
Renamed env-var consumers:
Pi-coach drainOnce({ askPi }) → drainOnce({ askAnalyticalFn? })
Pi-reflect runOnce({ askPi }) → runOnce({ askAnalyticalFn? })
bot.js attachCoach/attachReflect no longer pass askPi
attachTuner() added to bot.js spawn handler
lessons.source 'pi-coach' → 'timeweb-coach'
lessons.source 'pi-reflect' → 'timeweb-reflect'
Token cost measured live:
~705 input + 45 output = ~750 total per advisor call
worst case @ 6 calls/hour rate cap = ~108K tokens/day
OpenAI gpt-5-mini reference price: ~$0.60/month
Operator usage:
node scripts/list-improvements.js # open queue
node scripts/list-improvements.js --stats # advisor performance
node scripts/list-improvements.js --done 17 "shipped in 0.3.1"
node scripts/list-improvements.js --reject 18 "duplicate"
Tests: 360 green (was 332, +28 new).
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
This commit is contained in:
Claude Opus 4.7
+72
-64
@@ -15,9 +15,11 @@
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import { existsSync, mkdirSync, readFileSync, writeFileSync } from "node:fs";
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import { resolve } from "node:path";
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import { isAvailable as knowledgeAvailable, record as recordLesson } from "../knowledge/index.js";
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import { isAvailable as knowledgeAvailable, record as recordLesson, createImprovementRequest } from "../knowledge/index.js";
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import { isRegistered, skillRegistryPrompt } from "../skill-registry.js";
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import { pickActiveNeed } from "../manifesto/state.js";
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import { isAvailable as llmAvailable } from "../llm/provider.js";
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import { askAnalytical } from "./llm-call.js";
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import { info, warn } from "../log.js";
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// Mode-name allow-list, mirrors postmortem.js (advice.js maps them to
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@@ -37,25 +39,25 @@ const HISTORY_TAIL_LINES = 80;
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let _attached = null;
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let _timer = null;
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let _piCallTimes = [];
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let _llmCallTimes = [];
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export function attach({ bot, stateDir, askPi, getSnapshot, intervalMs = DEFAULT_INTERVAL_MS } = {}) {
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export function attach({ bot, stateDir, getSnapshot, intervalMs = DEFAULT_INTERVAL_MS } = {}) {
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if (_attached) {
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warn("reflect", "attach called twice; ignoring");
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return;
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}
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if (!stateDir || !askPi || !getSnapshot) {
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info("reflect", "attach: missing stateDir/askPi/getSnapshot — disabled");
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if (!stateDir || !getSnapshot) {
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info("reflect", "attach: missing stateDir/getSnapshot — disabled");
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return;
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}
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_attached = { bot, stateDir, askPi, getSnapshot };
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_attached = { bot, stateDir, getSnapshot };
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_timer = setInterval(() => {
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runOnce({ stateDir, askPi, getSnapshot }).catch((e) =>
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runOnce({ stateDir, getSnapshot }).catch((e) =>
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warn("reflect", `tick err: ${e?.message ?? e}`),
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);
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}, intervalMs);
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_timer.unref?.();
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info("reflect", `attached; self-assess every ${Math.round(intervalMs / 60000)} min`);
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info("reflect", `attached; self-assess every ${Math.round(intervalMs / 60000)} min${llmAvailable() ? " (TimeWeb)" : " (LLM disabled — will skip)"}`);
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}
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export function detach() {
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@@ -64,12 +66,13 @@ export function detach() {
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_attached = null;
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}
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export async function runOnce({ stateDir, askPi, getSnapshot, force = false } = {}) {
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export async function runOnce({ stateDir, getSnapshot, force = false, askAnalyticalFn = askAnalytical } = {}) {
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const now = Date.now();
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const hourAgo = now - 3600_000;
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_piCallTimes = _piCallTimes.filter((t) => t > hourAgo);
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if (!force && _piCallTimes.length >= HOURLY_BUDGET) {
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return { ok: false, reason: "budget exhausted", calls: _piCallTimes.length };
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_llmCallTimes = _llmCallTimes.filter((t) => t > hourAgo);
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if (!llmAvailable()) return { ok: false, reason: "llm not configured" };
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if (!force && _llmCallTimes.length >= HOURLY_BUDGET) {
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return { ok: false, reason: "budget exhausted", calls: _llmCallTimes.length };
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}
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const snap = getSnapshot();
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@@ -79,17 +82,12 @@ export async function runOnce({ stateDir, askPi, getSnapshot, force = false } =
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const plan = readPlan(stateDir);
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const activeNeed = pickActiveNeed(snap);
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const prompt = buildPrompt({ snap, journal, scenarios, diary, plan, activeNeed });
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_piCallTimes.push(now);
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const { system, user } = buildPrompt({ snap, journal, scenarios, diary, plan, activeNeed });
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_llmCallTimes.push(now);
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const reply = await askPiOnce({ askPi, prompt });
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if (!reply) return { ok: false, reason: "no reply" };
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const parsed = parseReply(reply);
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if (!parsed) {
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warn("reflect", "Pi reply not parseable as JSON");
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return { ok: false, reason: "bad reply", raw: reply.slice(0, 200) };
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}
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const parsed = await askAnalyticalFn({ system, user, json: true });
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if (!parsed || typeof parsed !== "object") return { ok: false, reason: "no reply" };
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const reply = JSON.stringify(parsed);
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const path = writeReflection(stateDir, parsed, reply);
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let rejectedPrefer = 0;
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@@ -112,15 +110,34 @@ export async function runOnce({ stateDir, askPi, getSnapshot, force = false } =
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avoidSkill,
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preferSkill,
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confidence: clamp(Number(l.confidence) || 0.5, 0.1, 0.9),
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source: "pi-reflect",
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source: "timeweb-reflect",
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sourceRef: path,
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});
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}
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if (rejectedPrefer > 0) {
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warn("reflect", `dropped prefer_skill from ${rejectedPrefer} reflection lessons (not in registry)`);
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}
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info("reflect", `verdict=${parsed.verdict ?? "?"} ${parsed.summary?.slice(0, 80) ?? ""} (${path ?? "no file"})`);
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return { ok: true, verdict: parsed.verdict, summary: parsed.summary, lessons: parsed.lessons ?? [] };
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// v0.3.0 — improvement requests from reflection. The LLM is asked
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// to flag missing skills/features when self-reflection reveals a
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// systemic gap (e.g. "I keep failing iron tools because there's no
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// craft.iron-pickaxe skill").
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let improvementsCount = 0;
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for (const imp of asArray(parsed.improvements ?? [])) {
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if (!imp?.title) continue;
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createImprovementRequest({
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source: "reflect",
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category: imp.category ?? "skill",
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title: String(imp.title).slice(0, 120),
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description: imp.description ?? null,
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context: { verdict: parsed.verdict, reflection_path: path },
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priority: imp.priority ?? 3,
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});
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improvementsCount += 1;
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}
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info("reflect", `verdict=${parsed.verdict ?? "?"} ${parsed.summary?.slice(0, 80) ?? ""} lessons=${(parsed.lessons ?? []).length} improvements=${improvementsCount} (${path ?? "no file"})`);
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return { ok: true, verdict: parsed.verdict, summary: parsed.summary, lessons: parsed.lessons ?? [], improvements: improvementsCount };
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}
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function readJournalTail(stateDir) {
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@@ -162,12 +179,38 @@ function buildPrompt({ snap, journal, scenarios, diary, plan, activeNeed }) {
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const needLine = activeNeed
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? `L${activeNeed.need.level} ${activeNeed.need.id} → ${activeNeed.skillId} (${activeNeed.need.title})`
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: "(satisfied through L10 / no active need)";
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return [
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const system = [
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"You are pepa, an autonomous Minecraft survival bot, reflecting on your own progress.",
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"Look at the last ~30 minutes of activity below. Answer honestly: are you actually making progress, or stuck in a loop?",
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"Answer honestly: are you making progress, stuck in a loop, or facing a structural gap?",
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"",
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skillRegistryPrompt({ limit: 1800 }),
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"",
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"Reply with ONE JSON object (no markdown fences, no prose):",
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'{',
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' "verdict": "progress" | "loop" | "recovering" | "idle" | "emergency",',
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' "summary": "<2-3 sentence honest assessment in Russian>",',
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' "next_action": "<one-sentence directive>",',
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' "lessons": [',
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' { "lesson": "<≤30 words, generalised rule>",',
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' "category": "combat|pathing|crafting|survival|self-improve",',
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' "trigger_skill": "<skill id or null>",',
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' "trigger_hostile": "<mob name or null>",',
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' "avoid_skill": "<registered skill id or null>",',
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' "prefer_skill": "<registered skill id or null>",',
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' "confidence": 0.6 } ],',
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' "improvements": [',
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' { "title": "<≤80 chars: structural gap (e.g. \'No craft.iron-pickaxe skill\')>",',
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' "description": "<concrete example showing why no registered skill helps>",',
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' "category": "skill|tuning|perception|planning|social|other",',
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' "priority": 1 } ]',
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'}',
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"",
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"CRITICAL: avoid_skill and prefer_skill MUST be one of the registered ids above, or null.",
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"Use 'improvements' ONLY when you identify a structural gap — a missing skill or feature that would unblock a class of situations. Skip it otherwise.",
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].join("\n");
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const user = [
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"## Current state",
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`- position: ${pos ? `(${Math.round(pos.x)}, ${Math.round(pos.y)}, ${Math.round(pos.z)})` : "?"}`,
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`- hp: ${snap?.health ?? "?"} food: ${snap?.food ?? "?"} day: ${snap?.isDay ? "yes" : "no"}`,
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@@ -198,28 +241,9 @@ function buildPrompt({ snap, journal, scenarios, diary, plan, activeNeed }) {
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"```",
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journal.slice(-20).join("\n"),
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"```",
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"",
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"Reply with ONE JSON object (no markdown fences, no prose):",
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'{',
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' "verdict": "progress" | "loop" | "recovering" | "idle" | "emergency",',
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' "summary": "<2-3 sentence honest assessment in Russian>",',
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' "next_action": "<one-sentence directive for what to do next>",',
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' "lessons": [',
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' { "lesson": "<≤30 words, generalised rule>",',
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' "category": "combat|pathing|crafting|survival|self-improve",',
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' "trigger_skill": "<skill id or null>",',
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' "trigger_hostile": "<mob name or null>",',
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' "avoid_skill": "<registered skill id to avoid or null>",',
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' "prefer_skill": "<registered skill id to use instead or null>",',
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' "confidence": 0.6 }',
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' ]',
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'}',
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"",
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"If you're clearly in a loop (same activity, no inventory growth, same position), say so honestly.",
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"If you're stuck in a bad terrain (deep pit, hostile-rich area), recommend choosing a new base.",
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"Lessons should be SHORT and ACTIONABLE. Don't repeat lessons the dispatcher already learned.",
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"CRITICAL: avoid_skill and prefer_skill MUST be one of the registered ids listed at the top of this prompt, or null. Do NOT invent new ids.",
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].join("\n");
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return { system, user };
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}
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function parseReply(text) {
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@@ -275,22 +299,6 @@ function writeReflection(stateDir, parsed, raw) {
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}
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}
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function askPiOnce({ askPi, prompt }) {
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return new Promise((res) => {
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let buf = "";
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try {
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askPi({
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prompt,
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onChunk: ({ stream, text }) => { if (stream === "stdout") buf += text; },
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onDone: () => res(buf),
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});
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} catch (e) {
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warn("reflect", `askPi: ${e?.message ?? e}`);
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res(null);
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}
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});
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}
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function asArray(v) { return Array.isArray(v) ? v : v ? [v] : []; }
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function clamp(v, lo, hi) { return Math.max(lo, Math.min(hi, v)); }
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