feat(v0.3.0): auto-trigger fast-advisor + token usage tracking

Closes the awareness → LLM → action loop that the rc.1/2/3 sequence
left as a followup. When the bot is wedged, looping, or just suffered
a preempt-then-retry, the reflex fires advise() in the background;
when the recommendation lands it overrides the next dispatch.

Async by design: advise() takes 5-15s on TimeWeb's hosted endpoint —
too slow for a synchronous reflex tick. tickAdvisor() is fire-and-
forget, the result lands on ctx.advisorRecommendation, and the *next*
tick reads and consumes it. Recommendations age out after 60s.

Components:

- runtime/coach/advisor-trigger.js — policy + async fire path
  - tickAdvisor(ctx, {plannedSkillId}) checks three triggers:
    1. wedged > 60s (no significant move)
    2. last 4+ dispatches are the same skill AND it's planned again
    3. preempt within last 30s + same skill being retried
  - 90s trigger cooldown, single-in-flight guard
  - consumeFreshRecommendation(ctx) reads/clears the cache
- runtime/reflex.js — curriculumReflex calls tickAdvisor() every tick
  and consumes a fresh recommendation BEFORE dispatching. ctx flag
  disableAdvisor=true for tests.
- runtime/bot.js — dispatchAction maintains a rolling 8-slot
  reflexCtx.recentSkillIds for the loop-detection trigger.

Token usage:

- runtime/llm/provider.js — normaliseUsage() reads OpenAI/TimeWeb-
  style {prompt_tokens, completion_tokens, total_tokens} from the
  response. Returned on every complete() result and logged at info
  level as "in=Nt/out=Mt".
- runtime/coach/fast-advisor.js — getUsageSnapshot() aggregates
  total tokens across all calls in the session.

Measured on live TimeWeb endpoint (gpt-5.4-mini agent):
  per call: ~705 input + 45 output = ~750 tokens
  rate limit: 6 calls/hour
  worst case at full budget: ~108K tokens/day
  estimated cost (OpenAI gpt-5-mini reference price): ~$0.60/month

Well within any reasonable budget — model can run hot 24/7.

Smoke verified: scripts/check-timeweb.js probe 4 produces
  trigger fired: true (wedged_90s)
  recommendation: recovery.tunnel-out
  rationale: "Stuck wedged for 90s; exploration is failing."
  latency: 5302ms

Tests: 345 green (was 332, +13 advisor-trigger).

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

runtime/reflex.test.js

@@ -49,6 +49,8 @@ function makeCtx({
 	disableManifesto = true, // curriculum branch tests don't construct
 	                          // full snapshots; manifesto is exercised by
 	                          // runtime/manifesto/state.test.js separately.
+	disableAdvisor = true,   // advisor-trigger fires real async LLM calls,
+	                          // tested directly in advisor-trigger.test.js.
 } = {}) {
 	const dispatches = [];
 	const ctx = {
@@ -62,6 +64,7 @@ function makeCtx({
 		skillBackoff,
 		metrics,
 		disableManifesto,
+		disableAdvisor,
 		dispatch(fn, label, opts = {}) {
 			dispatches.push({ fn, label, opts });
 		},