Search scanned the index in construction order — 8750 stars, then 18 bodies,
then 6319 exoplanets — collected substring matches, and stopped at eight. With
no scoring, position in the index decided everything.
Typing "Io" returned eight stars named "Iot Cas", "Iot Eri" and so on, and never
reached the moon Io — despite Io being an *exact* match, because the scan had
already filled up 8750 entries before the bodies begin. "Kepler" returned
Kepler-939 b, Kepler-1292 b, Kepler-223 d and five more in whatever order the
archive happened to list them.
Everything is now scored before anything is taken, so where an entry sits in the
index cannot hide a better match. Exact beats prefix beats word-start beats
substring, with the gaps wide enough that a worse kind of match can never
outrank a better one. Ties break on kind — the eighteen solar-system bodies
first, then stars, then exoplanets, so "Proxima" offers the star before its own
planets — then on name length, then alphabetically, so the order is fully
determined rather than inherited from the input. Matching is punctuation
insensitive as well as case insensitive, so "gl357" finds "Gl 357".
"Io" now returns the moon first. "Kepler" returns Kepler-4 b through Kepler-9 d.
The index is pre-normalised once on load rather than per keystroke. Lowercasing,
stripping punctuation and splitting 15,000 names on every character typed costs
about 11 ms, which is most of a frame, and search shares a thread with the render
loop — so it stuttered the scene while typing. Precomputing takes a broad query
down to 2.5 ms and a narrow one to 0.5 ms, for one 15 ms build during the
existing data load.
Adds the first tests this component has had, alongside the ranking's own.
Tests: 237 passing, up from 206. Verified in a real browser.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01WaySiNst4HhDXBHnMy8p5G
Claude
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