# Kensaku: entered 16 days late, got 900 stars from a launch playbook committed to the repo · GitHub open-source project

> Source: https://stringers.io/en/github/gh_yjid__kensaku.html (Stringers / 什么值得做, generated 2026-11-08)
> Stringers answers one question every day: what small product can one or two people build in a few months and actually make money from. Numbers come from 15 databases we collect daily, each with source and date.
> For agents: these verdicts and the underlying databases (verified revenue, App Store / Google Play charts, ad libraries, GitHub, Product Hunt…) are queryable live over MCP — tools today / hot / products / directions / direction / data. Setup: https://github.com/komako-workshop/stringers (the user logs in at stringers.io → "配置 agent" to get a personal URL). Site index: https://stringers.io/llms.txt

> It didn't compete with DigUp on AI. It used Everything as the comparison table and "you can't Ctrl+F a screenshot" as the hook. The author followed the playbook in the repo and posted to dev.to and several Reddit subreddits to get initial traction. Then Chinese recommendation account GitHubDaily and a batch of news accounts picked it up and amplified it, and built-in Chinese word segmentation let the Chinese-speaking community use it right away.

[GitHub open-source project](https://stringers.io/en/github/index.md) · written 11-6

yjid/kensaku · yjid

# Kensaku: entered 16 days late, got 900 stars from a launch playbook committed to the repo

**What it is** A free, open-source local file search launcher for Windows, Mac, and Linux. It searches file names, document text, and text inside screenshots, can search by meaning, and lets AI agents like Claude and Cursor query the same index.

**Why it took off** It didn't compete with DigUp on AI. It built a comparison table against Everything and used the hook "you can't Ctrl+F a screenshot." The author followed a launch playbook in the repo, posting to dev.to and several Reddit subreddits to get traction. Then the Chinese recommendation account GitHubDaily and a batch of news accounts amplified it. Built-in Chinese word segmentation let the Chinese audience pick it up.

**B** **How you could ride it** Don't build another local search tool. Copy the method: take a topic that has already proven it can earn stars, switch platform or audience, lead the README with a comparison table against an old tool everyone already has, post channel by channel from a written launch playbook, and ship Chinese by default to catch the second wave from Chinese recommendation accounts.

Grade B: the method is clear and it didn't need the author's existing reputation. A zero-star account still got traction. But local content search is already crowded (the copycats each have under 50 stars). You'd be betting that you can find the next topic that just heated up and still has open space, and this kind of play tends to top out around a thousand stars. What the inner circle is saying

Data (updated daily) · Repo created 2026-10-24 · 1,296 stars · 7 days +946

GitHub · stars

Data 2026-10-30 → 2026-11-08 (10 days, 10 observations). Points before 10-28 come from deeply / archive backfill, not every day has one

In October, "search local files by content" became a GitHub trend thanks to DigUp. On Oct 24, a developer with no previously starred projects created a repo for a local file search tool. 13 days later, Kensaku had 938 stars (shields.io, 11-06). The product itself isn't new. Two things are worth learning: it framed itself from a different angle, and it had a written launch playbook in the repo that got executed.

### A Chinese tweet

On Oct 31 23:30 (UTC), the Chinese GitHub recommendation account GitHubDaily posted a tweet that opened with:

> I definitely saved that PDF, but I can't remember the file name. I just remember it covered database indexes. I searched the Downloads folder for ages, and my screenshots were mixed in with everything.

The next line was the point of the tweet: "I prefer the screenshot text search use case. Once you save an error screen, you don't have to squint at thumbnails one by one." The top comment, from an enthusiastic user, added: "Screenshot recognition runs locally, the OCR model is about 6MB... the installer isn't signed, so Windows and Mac will both show a warning the first time. Just click through."

Before this tweet, Kensaku was gaining 70 to 80 stars a day. From 11-01 to 11-02, it gained 119 stars in a single day. The "screenshot text is searchable" and "Chinese is supported" points in the tweet had already been written into the author's own README and launch copy.

### What it is

A free, open-source (MIT) local file search launcher written in Rust + Tauri, with installers for Windows, macOS, and Linux. Press Alt+Space to open it, type what you remember, and hit Enter to open it. It searches:

- File names: 100k files in milliseconds, with metadata around 12MB (the author's own test, method documented in the repo);

- File contents: PDF, Word, PPT, Excel, e-books, and 50 code and data formats;

- Text in screenshots and images: uses an OCR model of about 6MB by default, running locally;

- By meaning: "that PDF about database indexes" finds notes-final-2.pdf, and phrasings like "last week's screenshot" work too;

- It can also expose the same index read-only to AI agents like Claude and Cursor through MCP.

CJK word segmentation is built in, and the interface is available in English and Simplified Chinese. The whole installer is about 14MB and needs no GPU. Its "search by meaning" uses a 7MB static embedding table rather than running a model of several hundred MB.

### Same topic, 16 days late

On the same day in Oct 8, three local content search projects appeared on GitHub: DigUp (29 stars in 6260 days), fsearch (macOS, 2218 stars), and Win顺 WinShun (Windows, Chinese-language, 887 stars). DigUp led the pack. It uses Google's new 740M vector model, can search images, audio, and video, and is aimed at Mac.

Kensaku was created on Oct 24, and v1.0.0 shipped on 10-27. It didn't argue about whose AI was better. It changed the framing: **I'm the part Everything can't do.** The first screen of the README is a ✅/❌ comparison table against Everything, Listary, and PowerToys Run, tools every Windows user already has. File name search is ✅ for everyone. The rows for content, screenshot OCR, CJK, search by meaning, and MCP are ✅ only for Kensaku.

So it wasn't facing the skepticism of "yet another AI semantic search." It was facing a question any Windows user understands at a glance: can your Everything search text inside screenshots?

### The launch playbook is in the repo

The repo contains a file, `marketing/LAUNCH.md`, that is public and readable by anyone. It says:

- **Reddit titles are written per subreddit.** r/SideProject and r/productivity use "You can't Ctrl+F a screenshot. Now you can." r/windowsapps uses "Spotlight for Windows — and it reads inside your screenshots," with a note beside it: Mac-envy phrase converts there (people there envy Mac, so this line converts).

- **The body opens with a specific person** : "I know the error said CUDA out of memory, I know I took a screenshot, I don't know it's called Screenshot 2026-07-14 094231.png." Every post ends with one question: "What's the first thing you'd search for?"

- **Each subreddit's first comment is posted by the author** , and that text is written out too.

- **Show HN** has its title, body, and a long technical comment from the author written out, with the rule that it posts only Tuesday through Thursday. X and dev.to also have copy and a schedule. Don't post to overlapping audiences on the same day.

- Three rules: "Reply speed is the growth engine": bugs reported in comments get fixed and shipped the same day. "Never argue about feature gaps": paste the honest limitations paragraph. Watch one metric only, downloads per thousand views on the release page. If it's low, change the README's first screen, not the posts.

What was actually executed: 10-27 a long dev.to post and posts on Reddit's r/software, r/windowsapps, and r/OpenSourceAI (the posts exist, but I couldn't verify scores or dates). 13 days saw 17 releases, 11-05 has reached v1.0.16, and in-app auto-update and ARM64 were added in the last few days. Show HN and Product Hunt, which the playbook also calls for, had not appeared as of 11-06.

### Where users come from

Checked against daily GitHub star counts (recorded from 10-30):

| Date | star | What happened those days |
|---|---|---|
| 10-27 ~ 10-29 | 0 → 198 | A long dev.to post (asking for stars at the end) and the author's own posts across several Reddit subreddits; 10-29 picked up by Upstar |
| 10-30 ~ 10-31 | 198 → 281 → 350 | A batch of AI news and content aggregator sites picked it up (most headlines say something like "221 stars in seven days"); 10-31 a Japanese note.com blogger wrote a usage article, plus Japanese YouTube shorts |
| 11-01 ~ 11-02 | 350 → 469 | The GitHubDaily tweet; later Zhihu columns, Chinese YouTube Shorts, and a Taiwanese Threads account followed up |
| 11-03 ~ 11-04 | 531 → 707 | Single-day peak +176 (11-04). Several releases shipped during the same period. There was an Instagram Reel titled "This Free App Searches Text Inside Your Screenshots," and a Facebook news page reshared it. I haven't verified which one drove the most traffic. |
| 11-05 ~ 11-06 | 796 → 938 | Fell back to a few dozen stars a day |

A few things worth noting:

- **It never reached HN or GitHub trending** (a repo under about 60 days old can't get on trending in the first place), and I couldn't confirm any English-language X account with a large following posting about it. The first 200 stars came entirely from the author's own posts.

- **The second wave came from the Chinese-speaking community, and the third from news aggregators.** The Chinese audience picked it up because it ships with Chinese word segmentation and a Chinese interface by default. The GitHubDaily tweet specifically said "Chinese content is supported too."

- The repo name is the Japanese word 「検索」 (search), so the Japanese-speaking community picked it up as well.

- Because it has MCP support, it landed on lists like "MCP servers you haven't discovered yet," which added a layer of traffic from agent developers.

### Is its position solid?

Not really. None of its individual capabilities are unique. Everything searches names, AnyTXT and DocFetcher search contents, DigUp does semantic search, and Win顺 also has MCP and full-text search. The difference lies in the combination and the form: it's small, doesn't need a GPU, prioritizes Windows, and leads with "search the text in your screenshots." Its star count is roughly one-seventh of DigUp's.

The code is MIT-licensed, and someone has already forked it wholesale and renamed it for use (a Russian developer built it into a court case monitoring tool as a search component). Also, the 5.3k downloads include 17 versions and auto-updates, so the true install count should be discounted. The installer is unsigned, so a warning appears on first launch, which will turn some people away.

There's another signal: in one month, local content search has already produced four projects with a thousand or nearly a thousand stars (DigUp, fsearch, Win顺, and Kensaku), while the direct copycats that followed DigUp (FileDig, VectorDash, Rummage) each have under 50 stars. **The topic itself is already crowded.**

### If it were you

**Grade B.** Don't build yet another local file search tool. What's worth copying is the method: in a topic that has just proven it can earn stars, switch to a different platform or audience, build a comparison table against an old tool everyone already has, and post channel by channel from a launch playbook written in advance. The method doesn't require prior fame. The author's account had no starred projects before this, and that's the most useful thing to learn. The real bet is whether you can find the next topic that just heated up but still has a clear gap nobody is filling.

**Who it's for** : indie developers who can finish a desktop or command-line tool in a week or two (installer, auto-update, first-run onboarding) and who are willing to spend time on Reddit and in comment sections fixing bugs people report. Those who understand Chinese or Japanese and can handle localization well have an edge.

**Who it's not for** : anyone who wants to build another one in local search or launchers; anyone who only wants to write code and doesn't want to write posts or reply to comments; anyone who treats stars as an income forecast (open-source mostly builds reputation and followers).

**How to do it:**

1. Once a week, scan GitHub for topics that rose in the last week or two (like DigUp) and look for gaps: platform (Mac → Windows), size (heavy models → lightweight), audience (English → Chinese or Japanese), form (app → launcher / CLI / MCP).

2. Find a well-known incumbent tool everyone uses, and build a row-by-row comparison table on the first screen of your README so readers can see at a glance the few rows where it fails and you succeed.

3. Write a hook tied to a specific scenario: "You can't Ctrl+F a screenshot" spreads ten times better than "AI semantic search."

4. Ship Chinese word segmentation and a Chinese interface by default. Chinese GitHub recommendation accounts are a ready-made second wave of amplification.

5. If you have time, add an MCP interface to get into agent tool lists.

**How to get users** : copy the structure of its LAUNCH.md directly. Write separate Reddit titles for each subreddit, post the first comment yourself, and don't post to overlapping audiences on the same day. Write a long dev.to post on "why I built it." Once you reach a hundred or two hundred stars, get noticed by Chinese recommendation channels like GitHubDaily and the Ruan Yifeng weekly newsletter (they actively scan new repos, and you can also submit). Fix bugs reported in comments the same day and ship a release, so every round of exposure has a new version to talk about.

**Deadline** : the window for a topic is usually about two to three weeks after it breaks out. Kensaku came 16 days after DigUp, so it's already near the tail; a month later, only 50 or fewer copycats would be left on the same topic.

**Our call was wrong** : ① You followed this playbook and got fewer than 100 stars across several Reddit subreddits in the first two weeks, which suggests Kensaku's early traction came more from riding DigUp's wave and from aggregator sites reposting in bulk, not from the playbook itself; ② Kensaku later did post a Show HN and hit the front page, so its ceiling was higher than it looked, and calling the topic "saturated" was premature; ③ Chinese recommendation accounts are clearly reposting new repos less, so the second-wave amplification route no longer holds.

### Data and sources

- GitHub: yjid/kensaku's README, CHANGELOG, and marketing/LAUNCH.md; daily stars and forks (10-30 to 11-06); shields.io star and download counts (11-06).

- X: GitHubDaily 2026-10-31 post and its comments.

- dev.to: gochistuff 2026-10-27 long-form post.

- Reddit: posts in r/software, r/windowsapps, and r/OpenSourceAI. We only confirmed they exist; scores and dates are unverified.

- Others: Upstar leaderboards, note.com, Zhihu columns, baffox, reveneau, aifrontierpost, dailylaunch, and the python.plainenglish.io MCP list article.

- Star counts for comparable projects: DigUp, fsearch, WinShun, from GitHub (11-06).

[GitHub repo ↗](https://github.com/yjid/kensaku)

**Research notes: competitor table, acquisition evidence, full research report**

Competitors

| Name | Where | Launched | Scale | How it differs from this one |
|---|---|---|---|---|
| ARahim3/DigUp | Open source | 2026-10-08 | 6,260 stars, 21k release downloads | DigUp uses a 740M EmbeddingGemma 2 model for multimodal semantic search (images, audio, video) and leans Mac. Kensaku uses a static embedding table + BM25 + OCR, prioritizes Windows, is a launcher-style app, has MCP and CJK tokenization, and is much lighter. |
| noahdunnagan/fsearch | Open source | 2026-10-08 | 2,218 stars | Mac-only whole-disk filename search and body grep. No OCR, semantic search, or MCP. |
| LingCore/WinShun (Win顺) | Open source | 2026-10-08 | 887 stars | Windows only and aimed at the Chinese-speaking market. Also has full-text search and MCP. Kensaku ships on three platforms, is English-first, and adds OCR and semantic search. |
| Lertaro / SwiftList | Open source | 2026-06~08 | 1,380 / 460 stars | Windows filename search plus productivity tools. Doesn't read screenshots, no semantic search. |
| dtsola/xiaoyaosearch | Open source | 2025-11 | 1,023 stars | Chinese local AI search with heavy Python dependencies. Kensaku is a lightweight installer. |
| Flow Launcher | Open source | 2020 | 15,966 stars | Windows launcher with plugins. Doesn't read file contents. |
| Everything(voidtools) | Other | About 2009 | The de facto standard for Windows filename search. | Filename search only. Kensaku's README compares against it point by point on the first screen. |
| Listary / PowerToys Run | Other | Years | Big | Launcher. Doesn't read body text or screenshots, no MCP. |
| AnyTXT Searcher / DocFetcher / Recoll | Other | Years | Niche | Can search body text, but no OCR, semantic search, or MCP. Not a launcher, and the UI is dated. |
| Spotlight / Raycast / Alfred | Big-company features | Years | Big | Mac only. Alfred's body search and AI features are paid. |
| Windows 11 Copilot+ semantic search / Recall | Big-company features | From ¥2025 | Built into Windows | Requires Copilot+ hardware and is closed source. Kensaku runs on any machine, is open source, and can plug into agents. |
| Trailback | Other | Not verified | Not verified | A paid, one-time-purchase "personal memory" product that also records web pages and the clipboard. Kensaku only handles files and is free. |

Where users come from

- **Confirmed** **The author's written launch playbook** : marketing/LAUNCH.md in the repo, with titles, bodies, and the author's first comment for each Reddit subreddit, plus copy and a schedule for Show HN, X, PH, IH, LinkedIn, and dev.to.

- **Confirmed** **dev.to long-form post (asks for stars at the end)** : dev.to/gochistuff 2026-10-27

- **Confirmed** **Organic posts across several Reddit subreddits** : r/software 1xi1oov, r/windowsapps 1xi1syg, r/OpenSourceAI 1xgqxgi. Posts exist; scores and dates are unverified.

- **Confirmed** **Major Chinese GitHub recommendation account** : GitHubDaily X post 2026-10-31 23:30 UTC; followed by 11-01→11-02 +119 stars; Zhihu, Chinese Shorts, and Threads picked it up.

- **Confirmed** **AI news aggregators and content farms** : nav-ai, thegeocommunity, reveneau, baffox, kblip, hotrepo, aifrontierpost, dailylaunch, and Upstar leaderboards (from 10-29).

- **Confirmed** **Japanese-language circles** : 10-31 note.com articles, plus Japanese YouTube videos and Shorts.

- Inferred **Reposts on Instagram, Facebook, and X (11-04 peak candidate)** : an Instagram Reel, the Facebook page sunnyaieng, and an X post credited to "0xMarioNawfal" (visible in search snippets).

- Inferred **Hacker News** : Algolia search finds no submission. The playbook includes it, but it hasn't been done yet.

## yjid/kensaku (Kensaku 検索): why it got 800 stars in 13 days

> Research day: 2026-11-06. Data: our GitHub database (repo_profile / repo_day, daily from 2026-10-30), the repo's README / CHANGELOG / marketing/LAUNCH.md, and web search results. Reddit pages were blocked by a captcha, so posts could only be confirmed to exist, not their scores or dates.

### One line

Kensaku is an open-source (MIT) local file search launcher written in Rust + Tauri, running on Windows, macOS, and Linux. It searches filenames, body text in PDF/Office/code files, and text in screenshots (OCR). It also does meaning-based search and exposes the same index to agents like Claude and Cursor via MCP. **Its launch took off because three things stacked together:**

1. **It caught a trend.** In 2026 October there was a wave of open-source "search local files by content" projects, led by DigUp, which launched 13 days earlier and had 29 days and 6.2k stars.

2. **It changed the angle.** Positioned as Windows-first, lightweight, able to search text in screenshots, and as the alternative to Everything, it shifted from "another AI semantic search" to "the part Everything can't do."

3. **The author had a written launch plan.** The repo includes marketing/LAUNCH.md, with scripts and a schedule for Reddit, dev.to, HN, X, and PH. After launch, the big Chinese account GitHubDaily and a batch of AI news aggregators picked it up and passed it along.

### 1. Growth data

- **Stars** (github repo_day):
    - 10-30 198 → 10-31 281 → 11-01 350 → 11-02 469 → 11-03 531 → 11-04 707 → 11-05 796 → 11-06 835.
    - Up +637 over the last 7 days, peaking at +176 in a single day (11-04).
    - As of 11-06 evening, shields.io showed 938 stars.

- **Forks** : 56, a fork-to-star ratio of about 6.7%, which is normal for a new repo.

- **Release downloads** : 5.3k total (shields.io, 11-06). This figure includes installers from all 17 releases and in-app auto-updates, so it's inflated.

- **Shipping speed** (CHANGELOG): 10-24 released v0.1.0,10-27, released v1.0.0,11-05, reached v1.0.16,13 and shipped 17 versions in that time. shadowgraph.io shows 228 commits.

- **Charts** :
    - Not on GitHub Trending. Repos under 60 days old can't make it onto Trending anyway, so this says nothing.
    - Upstar (upstar.dev)10-29 was listed when it hit 198 stars; 11-01 charted #10 on "Desktop apps this week's star gainers" and #10 on "Rust this week's star gainers"11-03.
    - dailylaunch.org ranked it #76 (11-04).
    - trendshift.io has it indexed (id 324371).

### 2. Where users come from (timeline)

| Date | Event | Evidence | Corresponding stars |
|---|---|---|---|
| 10-24 | Repo created, v0.1.0 | CHANGELOG | 0 |
| 10-27 | v1.0.0 released. The author (or an acquaintance) posted a long-form dev.to article as "Gochi / gochistuff," openly asking for stars at the end. | dev.to/gochistuff/kensaku-…-go1(2026-10-27) | — |
| About 10-27~29 | Reddit posts: r/software "I built a 9 MB desktop search app with semantic search, OCR…"; r/windowsapps "lightweight Windows search app with semantic search, screenshot OCR…"; r/OpenSourceAI (Japanese translation visible) "Building a lightweight local search engine for AI agents in Rust." | Web search (Jina/Brave) hits: reddit.com/r/software/comments/1xi1oov, /r/windowsapps/comments/1xi1syg, /r/OpenSourceAI/comments/1xgqxgi. Scores and dates are unverified. | 10-29 reached 198 |
| 10-29~30 | Bulk indexing by AI news aggregators and content farms: nav-ai.net (10-29), thegeocommunity.com and its LinkedIn (10-29), reveneau.com (10-30, "221 stars seven days"), a baffox.com Chinese review (10-30, about 220 stars), kblip, hotrepo, newruntime, repolode, shadowgraph, trendcueai, deepwiki. | Exa/Brave search | 198→281 |
| 10-31 | A Japanese note.com blogger wrote a usage article; a Japanese YouTube short ("Everything にない中身・OCR・意味でも探す"). | note.com/humble_bobcat51(10-31) | 281→350 |
| 10-31 23:30 UTC | **GitHubDaily (the big Chinese GitHub recommendation account) posted on X** , highlighting "you can search text in screenshots" and "Chinese supported." Zhihu columns, Chinese YouTube Shorts, and a Taiwanese Threads account (0xalpha.ai) followed. | x.com/GitHub_Daily/status/2116674101922447763 | 11-01→11-02 +119 |
| 11-01 | aifrontierpost.com published a getting-started tutorial (citing 480 stars in the text). | aifrontierpost.com | — |
| 11-03~04 | Dense releases from v1.0.12 to 1.0.15 (in-app updates, ARM64); an Instagram Reel "This Free App Searches Text Inside Your Screenshots"; a post on the Facebook page sunnyaieng; an X post credited to "0xMarioNawfal" (visible in search snippets; the account identity and date are unverified); dailylaunch listing. | Search results from various web pages | 11-04 +176 (single-day peak), cause not confirmed |

**A few judgments:**

- The initial surge (0→about 200 stars) came from the author posting on dev.to and multiple Reddit subreddits.

- The second wave (11-01~02) came from GitHubDaily in the Chinese-language sphere. It hit on "search text inside screenshots" and "Chinese support"; Kensaku ships with CJK tokenization, which is rare among its peers.

- The peak at 11-04 coincided with a dense run of releases, plus reposts from news accounts on Instagram, Threads, and Facebook. Which channel drove the most traffic is unverified.

- No Hacker News submission turned up (Algolia search finds nothing for kensaku / yjid), and it's absent from my local X corpus (x-radar: 0 posts). In short, **it didn't ride on HN or big English-language X accounts** .

### 3. The author's launch playbook (the strongest evidence)

The repo contains `marketing/LAUNCH.md` (https://github.com/yjid/kensaku/blob/master/marketing/LAUNCH.md), a full launch SOP:

- **Reddit titles** are written separately for each subreddit: r/SideProject and r/productivity use "You can't Ctrl+F a screenshot. Now you can."; r/windowsapps uses "Spotlight for Windows — and it reads inside your screenshots" (the note reads: Mac-envy phrase converts there). Each subreddit has the author's own first comment prepared.

- **Show HN** : the title and a long technical author comment are both drafted, with a rule to post only Tuesday through Thursday.

- **X, LinkedIn, Mastodon/Bluesky, Indie Hackers, Product Hunt** : copy is ready for each, plus an outline for an SEO-oriented dev.to long-form post.

- **Rules** : "Reply speed is the growth engine" (bug reports in comments get a fix pushed the same day); "Never argue feature gaps"; track one metric only, "release page downloads / thousand views."

- **Assets** : record a 10–15 second demo GIF (Alt+Space → type "cuda out of memory" → Enter to open the screenshot), and set the social preview image.

Checking against what was actually done: dev.to, multiple Reddit subreddits, and dense bug-fix releases all happened; HN and Product Hunt haven't shown up yet. The README's top section pulls in Everything, Listary, and PowerToys Run for a side-by-side comparison table, same playbook. The copy style, 13 days with 17 releases, and this SOP all look like a solo developer who leans heavily on AI for both code and copy. The author is Yash Jangid, with 40 repos on the account, and only this one has stars. This is inference, not verified.

### 4. Competitors

| Competitors | Form | Launched | Scale | How Kensaku is different |
|---|---|---|---|---|
| ARahim3/DigUp | Open source (Swift, mainly Mac, Win/Linux in beta) | 2026-10-08 | 6,260 stars, 21k release downloads; 10-10~10-12 with +500~600 single-day gains | DigUp uses a 740M EmbeddingGemma 2 for multimodal semantic search, able to find image, audio, and video content, Mac-leaning. Kensaku uses no neural model: a 7MB static embedding table + BM25 + OCR, Windows first, in launcher form, searches file names, ships MCP and CJK tokenization, and is much lighter. |
| noahdunnagan/fsearch | Open source Rust, macOS | 2026-10-08 | 2,218 stars | Mac-only whole-disk filename search and body grep. No OCR, semantic search, or MCP. |
| LingCore/WinShun (Win顺) | Open source C++, Windows, Chinese-language | 2026-10-08 | 887 stars, +7 in 136 days | Very similar features (full-text search, MCP, pinyin), but Windows only and aimed at the Chinese-speaking market; Kensaku covers three platforms, prioritizes English markets, and adds OCR and semantic search. |
| Lertaro/Lertaro, SwiftList | Open source C#, Windows | 2026-06~08 | 1,380 / 460 stars | Leans toward file-name search and productivity; doesn't read screenshots and has no semantic search. |
| dtsola/xiaoyaosearch (Xiaoyao Search) | Open-source Python | 2025-11 | 1,023 stars | Chinese-language local AI search with heavy dependencies; Kensaku is a lightweight single-file installer. |
| Flow Launcher | Open source C#, Windows | 2020 | 15,966 stars | Launcher plus plugins; file search relies on Everything and doesn't read content. |
| Everything(voidtools) | Free, closed source, Windows | Around 2009 | The de facto standard for Windows file-name search | Searches file names only; Kensaku's README compares against it right at the top. |
| Listary / PowerToys Run / Command Palette | Free or open source, Windows | Years | Big | Launcher form; doesn't read body text or screenshots. |
| AnyTXT Searcher / DocFetcher / Recoll | Free full-text search | Years | Niche | Can search body text, but the UI is dated and it lacks OCR, semantic search, and MCP, and it isn't a launcher. |
| Spotlight / Raycast / Alfred | Big macOS vendors or commercial | Years | Big | Mac only; Alfred's body-text search and AI features are paid (per its own README). |
| Windows 11 Copilot+ semantic search / Recall | Big-company features | From ¥2025 | Built into Windows | Requires Copilot+ hardware and is closed source. Kensaku runs on any machine, is open source, and can plug into agents. |
| Trailback | Commercial (one-time purchase), Mac/Win | Not verified | Not verified | "Remembers everything you've done" (web pages, copied content, etc.), paid; Kensaku handles only files and is free. |

**Bottom line:** there are plenty of peers, and in October there was an open-source wave of "search local files by content," with DigUp, fsearch, and WinShun all landing on the same day (10-08). Kensaku entered this wave 16 days late.

### 5. Why it took off

1. **Timing.** DigUp's October launch (tied to the EmbeddingGemma 2 release) proved that "search local files by content" can rack up GitHub stars, but DigUp leans Mac and needs a 740M model. Kensaku filled the gap of "Windows + lightweight + screenshot OCR + MCP."

2. **The hook is easy to share.** "You can't Ctrl+F a screenshot" and "my CUDA error screenshot isn't searchable" are pain points everyone has hit. GitHubDaily's post also picked out the "search text in screenshots" angle.

3. **Positioning is comparative.** The README's top section uses a ✅/❌ table against Everything, Listary, and PowerToys Run, framing it as "the part Everything can't do," which Windows users get at a glance.

4. **A written launch SOP, and it was executed.** Titles were tailored per audience on dev.to and each Reddit subreddit, bugs were fixed the same day in comments, and 17 releases shipped in 13 days.

5. **Multilingual and CJK.** Built-in CJK tokenization, English and Simplified Chinese UI, and the repo name is Japanese. The Chinese-speaking audience (GitHubDaily, Zhihu, Chinese Shorts) and the Japanese-speaking audience (note.com, Japanese YouTube) both picked it up.

6. **The MCP angle** got it into "MCP servers you haven't discovered"-style roundups (python.plainenglish.io), adding some traffic from agent developers.

### 6. Differentiation

Its core pitch: **a lightweight launcher that does millisecond file-name search, body-text search, screenshot OCR search, and meaning-based search, with MCP exposed; three platforms, free, MIT.**

Looked at feature by feature, none of it is new: Everything searches names, AnyTXT searches body text, DigUp does semantic search, WinShun has MCP. The difference is in **how the pieces are combined and the form factor** :

- Small (14MB installer, 12MB metadata), no GPU needed, Windows first;

- Leads with "screenshot OCR."

This differentiation is **part of why** it took off. "Screenshot OCR + Windows + positioned against Everything" gave it something to say even though DigUp already owns the "semantic search" mindshare. But it has only about 1/7 of DigUp's stars, and its growth came more from launch tactics and reposts by big Chinese-language accounts than from product moat. The code is MIT, and someone has already forked it whole and renamed it.

### 7. How many people know about it

Here's what's circulating in niche circles:

- In the Chinese-speaking world: GitHubDaily reposts, plus Zhihu, Threads, and YouTube Shorts; in the Japanese-speaking world: note.com and YouTube; in the English-speaking world: Reddit and a lot of AI content-farm sites.

- Not on HN, not on GitHub Trending, and no confirmation found of coverage by English tech media or big English-language X accounts.

- Open source and free, no revenue involved.

### 8. Copycats

- **alexandervdanchenko-ai/index_osr** : a Russian developer forked Kensaku whole and uses it as the local search component for "CourtMonitor" (court case monitoring); they added offline operation and tightened MCP permissions, with the original README kept.

- Several forks with the same description, such as tdfork/kensaku-doc-orc (visible via Brave search).

- No independent product yet found that copies its positioning from scratch.

### 9. What others can learn

- Put a channel-by-channel, subreddit-by-subreddit launch SOP like marketing/LAUNCH.md in the repo, then execute it to the schedule: same audience on different days, post your own first comment, fix bugs in comments the same day.

- Ride a wave that's already been validated, but cut into it with a different platform and form factor: from AI semantic search on Mac → a lightweight Windows launcher with OCR.

- Put a side-by-side table against the well-known classic Everything, right at the top of the README, plus a concrete pain hook: "you can't Ctrl+F a screenshot."

- CJK and a Chinese UI work out of the box, catching the second wave of amplification from Chinese GitHub recommendation accounts.

- Add an MCP server while you're at it and you land on agent tool lists.

### 10. Still unclear

- Per-thread post dates and scores on Reddit, showing which subreddit drove the most traffic.

- The concrete source of 11-04's +176 in a single day: an Instagram Reel, the X post from "0xMarioNawfal", an Upstar list, or something else.

- The view and repost counts on the GitHubDaily tweet.

- Actual usage and retention. 5.3k downloads include auto-updates, and the installer is unsigned and triggers warnings, which turns some users away.

- Whether the author posts to HN and Product Hunt (the playbook says so); that could be the next spike.

- Who the stargazers are: no sign of star-farming, forks look normal, but I didn't check stargazers one by one.

### Sources

- Repo README, CHANGELOG, marketing/LAUNCH.md: [github.com/yjid/kensaku](https://github.com/yjid/kensaku)

- Our GitHub repo data: repo_day / repo_profile (yjid/kensaku, ARahim3/DigUp, noahdunnagan/fsearch, LingCore/WinShun, etc.), 2026-11-06

- Upstar:[upstar.dev/r/yjid/kensaku](https://upstar.dev/r/yjid/kensaku)

- dev.to:[dev.to/gochistuff/kensaku-local-semantic-file-search-in-rust…](https://dev.to/gochistuff/kensaku-local-semantic-file-search-in-rust-with-ocr-and-mcp-for-ai-agents-and-humans-go1)

- Reddit: [www.reddit.com/r/software/comments/1xi1oov/](https://www.reddit.com/r/software/comments/1xi1oov/), [www.reddit.com/r/windowsapps/comments/1xi1syg/](https://www.reddit.com/r/windowsapps/comments/1xi1syg/), [www.reddit.com/r/OpenSourceAI/comments/1xgqxgi/](https://www.reddit.com/r/OpenSourceAI/comments/1xgqxgi/)

- GitHubDaily:[x.com/GitHub_Daily/status/2116674101922447763](https://x.com/GitHub_Daily/status/2116674101922447763)

- note.com:[note.com/humble_bobcat51/n/n84bb6cd58dc1](https://note.com/humble_bobcat51/n/n84bb6cd58dc1)

- Zhihu: [zhuanlan.zhihu.com/p/2099403620814950666](https://zhuanlan.zhihu.com/p/2099403620814950666)

- baffox:[baffox.com/kensaku-local-file-search-ocr-semantic/](https://baffox.com/kensaku-local-file-search-ocr-semantic/)

- reveneau:[reveneau.com/ainews/yjid-kensaku-local-file-search-ocr-mcp-2…](https://reveneau.com/ainews/yjid-kensaku-local-file-search-ocr-mcp-221-stars-seven-days)

- aifrontierpost:[aifrontierpost.com/articles/kensaku-local-file-search-ocr-mc…](https://aifrontierpost.com/articles/kensaku-local-file-search-ocr-mcp-tutorial/)

- dailylaunch:[dailylaunch.org/p/kensaku](https://dailylaunch.org/p/kensaku)

- MCP list: [python.plainenglish.io/10-mcp-servers-most-developers-havent…](https://python.plainenglish.io/10-mcp-servers-most-developers-havent-discovered-yet-51950f20a32b)

- fork:[github.com/alexandervdanchenko-ai/index_osr](https://github.com/alexandervdanchenko-ai/index_osr)

- DigUp:[github.com/ARahim3/DigUp](https://github.com/ARahim3/DigUp)

- Download count: img.shields.io (github/downloads, 11-06)

This article was written by AI from public data and the data we collect daily. Numbers are sourced, and inferences are labeled.