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feat(v0.3.0): paradigm shift — TimeWeb-only LLM + persistent advisor trail + improvement queue

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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:
mayatnikov
2026-05-27 19:12:48 +03:00
co-authored by Claude Opus 4.7
parent bc381b2a4b
commit 0d97ccccfa
18 changed files with 1188 additions and 197 deletions
Download Patch File Download Diff File Expand all files Collapse all files
scripts/list-improvements.js
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#!/usr/bin/env node
// Operator-facing view of bot-flagged improvement requests.
//
// The LLM (postmortem + reflect + trigger-tuner) writes here when it
// notices a structural gap — a missing skill or a misconfigured policy.
// You read this, decide what's worth implementing, and ship it.
//
// Usage:
// node scripts/list-improvements.js # all open, sorted by priority
// node scripts/list-improvements.js --status all # everything
// node scripts/list-improvements.js --status implemented
// node scripts/list-improvements.js --source reflect
// node scripts/list-improvements.js --category skill
// node scripts/list-improvements.js --done 17 "shipped in 0.3.1"
// node scripts/list-improvements.js --reject 18 "duplicate"
// node scripts/list-improvements.js --stats # aggregate counts
import { config as loadDotenv } from "dotenv";
loadDotenv();
import { initKnowledge, listImprovements, markImprovementStatus, isAvailable, recommendationStats } from "../runtime/knowledge/index.js";
import { stateDir } from "../runtime/config.js";
function parseArgs(argv) {
const out = { status: "open", source: null, category: null, limit: 50, stats: false, action: null };
for (let i = 2; i < argv.length; i++) {
const a = argv[i];
if (a === "--status") out.status = argv[++i];
else if (a === "--source") out.source = argv[++i];
else if (a === "--category") out.category = argv[++i];
else if (a === "--limit") out.limit = Number(argv[++i]) || 50;
else if (a === "--stats") out.stats = true;
else if (a === "--done") { out.action = "implemented"; out.actionId = Number(argv[++i]); out.actionNote = argv[++i] ?? null; }
else if (a === "--reject") { out.action = "rejected"; out.actionId = Number(argv[++i]); out.actionNote = argv[++i] ?? null; }
else if (a === "--inprogress") { out.action = "in_progress"; out.actionId = Number(argv[++i]); out.actionNote = argv[++i] ?? null; }
else if (a === "--help" || a === "-h") { printHelp(); process.exit(0); }
}
if (out.status === "all") out.status = null;
return out;
}
function printHelp() {
console.log(`Usage: node scripts/list-improvements.js [options]
--status <open|in_progress|implemented|rejected|all> default: open
--source <postmortem|reflect|advisor|tuner|manual>
--category <skill|tuning|perception|planning|social|other>
--limit <n> default: 50
--stats show advisor recommendation stats
--done <id> [note] mark a request as implemented
--inprogress <id> [note] mark a request as in progress
--reject <id> [note] mark a request as rejected
`);
}
function priorityLabel(p) {
return ["", "P1 urgent", "P2 high", "P3 normal", "P4 low", "P5 nice-to-have"][p] ?? `P${p}`;
}
function statusLabel(s) {
return ({
open: "OPEN",
in_progress: "WIP",
implemented: "DONE",
rejected: "REJECTED",
duplicate: "DUP",
})[s] ?? s;
}
function formatTs(ts) {
if (!ts) return "?";
const d = new Date(ts);
return d.toISOString().slice(0, 16).replace("T", " ");
}
function renderRow(r) {
const lines = [
`#${r.id} [${statusLabel(r.status).padEnd(8)}] ${priorityLabel(r.priority).padEnd(18)} ×${r.votes}`,
` ${r.title}`,
` source=${r.source} category=${r.category ?? "?"} created=${formatTs(r.ts)}${r.implemented_at ? ` done=${formatTs(r.implemented_at)}` : ""}`,
];
if (r.description) {
lines.push(` ${String(r.description).slice(0, 240)}`);
}
if (r.notes) {
lines.push(` notes: ${String(r.notes).slice(0, 200)}`);
}
return lines.join("\n");
}
async function main() {
const args = parseArgs(process.argv);
await initKnowledge({ stateDir });
if (!isAvailable()) {
console.error(`knowledge DB unavailable at ${stateDir}/knowledge.db`);
console.error(`(install better-sqlite3 and ensure the bot has run at least once)`);
process.exit(1);
}
if (args.action) {
markImprovementStatus(args.actionId, { status: args.action, notes: args.actionNote });
console.log(`#${args.actionId} → ${args.action}${args.actionNote ? ` (${args.actionNote})` : ""}`);
return;
}
if (args.stats) {
const stats = recommendationStats({ sinceHours: 24 });
console.log(`=== Advisor recommendation stats (last 24h) ===`);
if (stats.length === 0) {
console.log("(no recommendations yet)");
} else {
console.log(" trigger_reason total applied ok fail avg_in avg_out avg_latency");
for (const s of stats) {
console.log(` ${(s.trigger_reason || "?").padEnd(22)} ${String(s.total).padStart(5)} ${String(s.applied ?? 0).padStart(7)} ${String(s.succeeded ?? 0).padStart(2)} ${String(s.failed ?? 0).padStart(4)} ${String(Math.round(s.avg_in ?? 0)).padStart(6)} ${String(Math.round(s.avg_out ?? 0)).padStart(7)} ${String(Math.round(s.avg_latency_ms ?? 0)).padStart(11)}`);
}
}
return;
}
const rows = listImprovements({
status: args.status,
source: args.source,
category: args.category,
limit: args.limit,
});
const heading = `=== Improvement requests`
+ (args.status ? ` (status=${args.status})` : ` (all)`)
+ (args.source ? ` source=${args.source}` : "")
+ (args.category ? ` category=${args.category}` : "")
+ ` — ${rows.length} row${rows.length === 1 ? "" : "s"} ===`;
console.log(heading);
if (rows.length === 0) {
console.log("(empty)");
return;
}
for (const r of rows) {
console.log("");
console.log(renderRow(r));
}
}
main().catch((e) => {
console.error("ERROR:", e?.message ?? e);
process.exit(2);
});