Four ways in. One engine.
Typical latency in milliseconds. Scoped = a query pinned to a folder; whole machine = every drive at once.
Four tools. Every search.
iFileNames2,000 nsFind files and folders by filename across every drive.
iFileText~5 msSearch text inside files. Functions, TODOs, imports, errors.
iFileSearchParallelNot sure where the match is? Both at once.
iFileKnowledgeOne pathEverything known about one file or folder: its machine-wide connections, plus the notes on it.
budget.xlsxFind a spreadsheet by nameext:pdf annual reportPDFs with both words in the name/src ext:ts mod:7dTypeScript in /src, changed this weektype:video sort:sizeAll videos, largest firstTODO: fixEvery TODO across your codebaseEvery operator composes.
Search
keywordsAll words must match
budget 2025"quotes"Hold spaces in a folder name
/"ATS Pack/Wallpapers"||Either term (OR)
readme || license!folderSkip everything inside a folder
config !testFilter
/folderScope to directory
/src authext:By extension
ext:ts,tsxtype:By category
type:videosize:By file size
size:>10mbmod:Modified within
mod:7dcreated:Created within
created:30dshow:Add back hidden and system files
show:allSort
sort:relevanceBest match (default)
sort:modifiedRecently changed
sort:sizeLargest first
sort:nameA → Z
sort:createdNewest created
File types
type:codetype:documenttype:videotype:audiotype:imagetype:spreadsheettype:presentationtype:applicationtype:repotype:otherTime and size sorts run newest and largest first: append -asc to flip one. sort:size-asc = smallest first. Name already runs A → Z, so it flips the other way: sort:name-desc = Z → A.
Every query kind, measured: medians, not cherry-picks.
Real end-to-end latency with full ranking on a live, freshly cold-built index: the honest distribution, worst cases and all. Beside each, what the same job costs the scanner your AI uses today.
| Query kind | median | p95 | worst | ripgrep, same job |
|---|---|---|---|---|
| File name, selective | 0.4 ms | 2.0 ms | 2.8 ms | no filename mode, the OS walk: 88 sec |
| File name, common, full-set ranked | 5.4 ms | 9.1 ms | 10.3 ms | no filename mode |
| Folder name | 1.8 ms | 3.4 ms | 3.9 ms | no folder search |
| Content, common words | 9.0 ms | 12 ms | 33 ms | re-reads every file, every query |
| Content, rare symbols | 7.0 ms | 60 ms | 91 ms | 17 min 13 sec (whole machine, cold) |
| Content, exact phrases | 16 ms | 167 ms | 167 ms | re-scans every file: the more text, the slower |
| Document text, PDF · DOCX · XLSX | 3.0 ms | 7.0 ms | 13 ms | can't: scanners don't read PDF/Office text |
| Scoped to a folder | 0.2 ms | 0.4 ms | 0.4 ms | ~90 ms (one warm folder, their best case) |
Real searches on one real PC, a Ryzen 9 on Windows 11, same machine and same queries for both. And ripgrep isn’t a strawman: it’s the search engine inside VS Code and the one AI agents like Claude Code run. Full methodology in the ripgrep comparison.
One engine. Four ways in.
The desktop app, the CLI, the MCP server and the direct pipe: one install, one always-fresh index. Free on every machine you own.
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