…-picker

# Conflicts:
#	apps/daemon/src/prompts/system.ts
#	packages/contracts/src/prompts/system.ts

The variant suffix → emotion label map (e.g. female_0033_b → "开心")
is documented on docs.senseaudio.cn/guides/voice/catalog.md but not
returned by the /v1/get_voice API, so the original PR hardcoded a
50-line table that drifts every time SenseAudio adds a persona.

Replace the hardcoded table with a one-time per-process scraper:

  1. fetch docs.senseaudio.cn/guides/voice/catalog.md (24h cached)
  2. regex `<voice_id>` `(<label>)` across the page → labels map
  3. shapeCatalogue() now consults the scraped map first

Fallback chain when shaping each variant entry:

  primary    doc-scraped label                 (fresh, authoritative)
  secondary  BACKUP_VARIANT_LABELS hardcoded   (used iff doc fetch fails
                                                or yields zero matches;
                                                cached only 5min so the
                                                live doc is retried fast
                                                once it recovers)
  per-voice  voice_name from the API           (used iff a specific
                                                voice_id is missing from
                                                both label sources —
                                                never a static "通用"
                                                placeholder anymore)

Net effect against today's prod catalogue: doc surfaces 111 voice_id
labels vs 82 in the hardcoded backup, so 29 voices that previously
fell back to "通用" (female_0006_a "深情", male_0023_a "平稳",
male_0004_a "平稳", … includes热门 personas) now carry their real
label without anyone needing to update source code.

The picker dropdown showed all ~12 personas in catalogue order with
no UX hint about which ones actually fit the user's brief. The user
had to read every option's label end-to-end to decide.

Add a REQUIRED step in renderSenseAudioPickerInstructions: before
composing the dropdown, the agent scores each persona for fit against
the brief (gender, age, register, tone, scenario keywords), then
marks the top 3 with prefix glyphs included in the localised label:

  ★    nexu-io#1 best match
  ◆    nexu-io#2
  ◇    nexu-io#3
  (none for the rest)

Top-3 options sort to the front of the dropdown in 1→2→3 order; the
remainder follow in original catalogue order. Glyphs are universal
(not zh-CN-only) so the localisation rule for the rest of the label
keeps working unchanged.

Update the variant-label-fallback test to match the new behaviour
introduced in the scrape-from-docs commit: voice_ids missing from
both the doc-scraped map and the BACKUP_VARIANT_LABELS hardcoded
backup now fall back to the persona's voice_name, not the static
"通用" placeholder.

The fetch mock now serves a 404 for the docs URL so the daemon
deterministically takes the backup path during the test, which was
the implicit assumption in the previous version.

The previous prefix set (★ ◆ ◇) was too geometrically similar — the
filled and open diamonds were hard to tell apart at a glance, and the
black star + diamonds combo did not visually communicate "ranking".

Switch to the universal medal emojis. They map onto the gold/silver/
bronze metaphor users already recognise from sports, awards, and
leaderboards, and remain locale-neutral so the rest of the label can
still be translated freely.