u/lingya22

I built a Chrome extension to avoid wasting time replying to dead Reddit threads — 62 installs in 25 days, looking for feedback

Hey everyone,

I’ve been doing a lot of manual Reddit outreach for small projects, and one problem kept annoying me:

A thread can look active from the outside, but once you open it, the OP is gone, the conversation has drifted, or it’s basically too late to get a meaningful reply seen.

So I built a small Chrome extension called Reddit Growth Copilot.

The idea is simple: before spending 10–20 minutes writing a thoughtful reply, it helps you judge whether a Reddit thread is actually worth engaging with.

It looks at things like:

  • thread freshness
  • comment activity
  • whether the OP is still participating
  • reply window timing
  • fake-active risk
  • whether the thread still looks alive or already dead

It then gives an opportunity score and a quick recommendation, so you can decide whether to reply now, skip it, or treat it as research instead of outreach.

I launched it quietly about 25 days ago, and it has reached 62 installs so far. Not huge, but enough to tell me that other people might have the same pain.

I’m trying to figure out what to improve next.

A few things I’m considering:

  • better OP activity detection
  • clearer “reply now / skip / research only” labels
  • saved thread tracking
  • suggested reply angles based on thread context
  • support for more growth/customer-discovery workflows

Would love feedback from anyone who uses Reddit for customer discovery, early user acquisition, indie hacking, SaaS validation, or community marketing.

Do you manually check whether a thread is still worth replying to?

And what signals do you personally look at before deciding to comment?

reddit.com
u/lingya22 — 21 hours ago

I got tired of replying to Reddit threads that looked active but were already dead, so I built a small tool

I’ve been using Reddit a lot for customer discovery and early-stage growth.

One thing that kept happening:

I’d find a thread that looked promising, spend time writing a thoughtful reply, and then realize the conversation was basically already dead.

The OP stopped replying.
The comments had drifted.
The thread had activity, but no real opening left.
Or it was just “fake active” — lots of noise, no actual discussion.

So I built a Chrome extension to help me quickly judge whether a Reddit thread is still worth replying to.

It scores a thread based on freshness, comment activity, OP participation, reply timing, and fake-active risk.

https://preview.redd.it/h1t3br9uu01h1.png?width=1473&format=png&auto=webp&s=e5470bfc9642df302ff3dbab59a654425a131dae

Chrome Web Store link:
https://chromewebstore.google.com/detail/reddit-growth-copilot/fnlbicpmajhmdcnhcbdmomdkakllgfaf

The goal isn’t to automate comments or spam people. It’s more like a sanity check before spending time on a reply.

I launched it quietly and it’s now at 62 installs after about 25 days.

I’m still early and trying to decide what matters most to improve.

For people who use Reddit for growth, research, SaaS validation, or finding early users:

How do you decide whether a thread is still worth replying to?

Do you look at recency, OP activity, comment count, upvotes, or something else?

reddit.com
u/lingya22 — 21 hours ago

I got tired of replying to Reddit threads that looked active but were already dead, so I built a small tool

I’ve been using Reddit a lot for customer discovery and early-stage growth.

One thing that kept happening:

I’d find a thread that looked promising, spend time writing a thoughtful reply, and then realize the conversation was basically already dead.

The OP stopped replying.
The comments had drifted.
The thread had activity, but no real opening left.
Or it was just “fake active” — lots of noise, no actual discussion.

So I built a Chrome extension to help me quickly judge whether a Reddit thread is still worth replying to.

https://preview.redd.it/y1nl8mkfu01h1.png?width=1473&format=png&auto=webp&s=f956c5a6b90cd85d2230527116235771dffa4984

It scores a thread based on freshness, comment activity, OP participation, reply timing, and fake-active risk.

Chrome Web Store link:
https://chromewebstore.google.com/detail/reddit-growth-copilot/fnlbicpmajhmdcnhcbdmomdkakllgfaf

The goal isn’t to automate comments or spam people. It’s more like a sanity check before spending time on a reply.

I launched it quietly and it’s now at 62 installs after about 25 days.

I’m still early and trying to decide what matters most to improve.

For people who use Reddit for growth, research, SaaS validation, or finding early users:

How do you decide whether a thread is still worth replying to?

Do you look at recency, OP activity, comment count, upvotes, or something else?

reddit.com
u/lingya22 — 21 hours ago

I got tired of replying to Reddit threads that looked active but were already dead, so I built a small tool

I’ve been using Reddit a lot for customer discovery and early-stage growth.

One thing that kept happening:

I’d find a thread that looked promising, spend time writing a thoughtful reply, and then realize the conversation was basically already dead.

The OP stopped replying.
The comments had drifted.
The thread had activity, but no real opening left.
Or it was just “fake active” — lots of noise, no actual discussion.

So I built a Chrome extension to help me quickly judge whether a Reddit thread is still worth replying to.

https://preview.redd.it/y1nl8mkfu01h1.png?width=1473&format=png&auto=webp&s=f956c5a6b90cd85d2230527116235771dffa4984

It scores a thread based on freshness, comment activity, OP participation, reply timing, and fake-active risk.

Chrome Web Store link:
https://chromewebstore.google.com/detail/reddit-growth-copilot/fnlbicpmajhmdcnhcbdmomdkakllgfaf

The goal isn’t to automate comments or spam people. It’s more like a sanity check before spending time on a reply.

I launched it quietly and it’s now at 62 installs after about 25 days.

I’m still early and trying to decide what matters most to improve.

For people who use Reddit for growth, research, SaaS validation, or finding early users:

How do you decide whether a thread is still worth replying to?

Do you look at recency, OP activity, comment count, upvotes, or something else?

reddit.com
u/lingya22 — 21 hours ago

I built a Chrome extension to avoid wasting time replying to dead Reddit threads — 62 installs in 25 days, looking for feedback

I’ve been using Reddit a lot for customer discovery and early-stage growth.

One thing that kept happening:

I’d find a thread that looked promising, spend time writing a thoughtful reply, and then realize the conversation was basically already dead.

The OP stopped replying.
The comments had drifted.
The thread had activity, but no real opening left.
Or it was just “fake active” — lots of noise, no actual discussion.

So I built a Chrome extension to help me quickly judge whether a Reddit thread is still worth replying to.

It scores a thread based on freshness, comment activity, OP participation, reply timing, and fake-active risk.

https://preview.redd.it/tu3vdwo8u01h1.png?width=1473&format=png&auto=webp&s=19edfac9496e4e0c3c702af3f2e270a6c9c5fa38

Chrome Web Store link:
https://chromewebstore.google.com/detail/reddit-growth-copilot/fnlbicpmajhmdcnhcbdmomdkakllgfaf

The goal isn’t to automate comments or spam people. It’s more like a sanity check before spending time on a reply.

I launched it quietly and it’s now at 62 installs after about 25 days.

I’m still early and trying to decide what matters most to improve.

For people who use Reddit for growth, research, SaaS validation, or finding early users:

How do you decide whether a thread is still worth replying to?

Do you look at recency, OP activity, comment count, upvotes, or something else?

reddit.com
u/lingya22 — 21 hours ago

Do you actually use X/Twitter bookmarks, or do they just become a graveyard?

I’m curious how other people manage this.

I save a lot of useful posts on X/Twitter:

  • good hooks
  • launch posts
  • growth examples
  • reply formats
  • content ideas
  • posts I want to study later

But after a while, bookmarks become almost useless for me.

I can save something, but later I usually can’t remember why I saved it, what angle I wanted to study, or how to find it again.

Screenshots are even worse because they lose context.

I ended up building a small Chrome extension for myself called HookVault. The idea is basically a local-first swipe file for public X/Twitter posts: save a post, add tags/notes, search later, and export it if needed.

No account, no backend, no cloud sync. Saved posts stay on your device.

I’m not sure if this is just my own messy workflow or if other people have the same problem.

How do you organize useful X/Twitter posts after saving them?

reddit.com
u/lingya22 — 3 days ago
▲ 13 r/Startup_Ideas+8 crossposts

I kept running into the same annoying workflow:

I’d see a useful post on X —

a strong hook,

a launch post,

a product demo,

a meme format,

an ad angle,

or just a good content structure

and then I’d save it somewhere random.

Sometimes I liked it.

Sometimes I bookmarked it.

Sometimes I took a screenshot.

Sometimes I pasted it into notes.

The problem was that none of those turned into an actual reusable library.

So I built a small Chrome extension called HookVault.

It lets you save public X/Twitter posts into a local swipe file with:

- source link

- post text

- author info when available

- media type

- tags

- personal notes

- used / unused status

- search and filters

- CSV / JSON export

It’s local-first and uses chrome.storage.local.

No account, no backend, no cloud sync, no data collection.

Also, it is not a video downloader. It saves the post context for research/inspiration, not the video file.

I mainly built it for creators/builders who study what works on X and want a cleaner way to organize examples.

Would love feedback on the workflow:

Do you currently keep a swipe file?

And if yes, where do you keep it — Notion, bookmarks, screenshots, something else?

Link:

https://chromewebstore.google.com/detail/hookvault-save-xtwitter-p/dpamdgndkneedmfplgnnbdogiakajcpo

u/lingya22 — 1 day ago
▲ 11 r/startups_promotion+10 crossposts

I’ve been building Chrome extensions for a while, but recently ran into a problem with my own setup:

I had ~27 extensions installed…
and couldn’t confidently answer:

→ which ones I actually still use
→ which ones overlap
→ which ones might be risky

Chrome lets you manage extensions, but it doesn’t really help you decide what to keep

and once you install enough, things get messy fast

So I built a small side project:

Extension Manager & Cleaner
https://chromewebstore.google.com/detail/extension-manager-cleaner/kkkbalogfpcbhmgobjohlcamikmaedia

What it does

  • scans all installed extensions (locally only)
  • highlights ones that need attention
  • detects overlaps (e.g. multiple wallets / ad blockers)
  • shows enabled vs disabled breakdown
  • suggests actions like:
    • keep
    • disable first
    • review permissions

Why I built it this way

I initially wanted to detect “unused extensions”

but quickly realized:

that’s actually really hard to measure reliably

So instead, I focused on signals like:

  • permissions scope
  • duplication
  • whether it’s enabled
  • whether you’ve reviewed it recently

What surprised me

I had:

  • 4 crypto wallet extensions enabled at once
  • overlapping extensions doing similar things
  • a few I didn’t even remember installing

Also learned that extensions can request pretty deep access to your browsing data depending on permissions

so this felt more like a browser hygiene / safety problem than just cleanup

Tech

  • Chrome Extension (Manifest V3)
  • chrome.management API
  • fully local (no backend, no tracking)

Still figuring out

  • how aggressive suggestions should be
  • how to define “high attention” better
  • whether to add periodic review reminders

Would love feedback from other builders:

  • how do you manage your extensions today?
  • would you trust a tool like this to suggest removals?
  • anything obvious I’m missing?
u/lingya22 — 1 day ago

I’ve been building Chrome extensions for a while, but recently ran into a problem with my own browser:

I had ~27 extensions installed…
and couldn’t confidently answer:

→ which ones I actually still use
→ which ones overlap
→ which ones might be risky

Chrome gives you a list, but not much context

so I ended up building a small side project:

Extension Manager & Cleaner

What it does

  • scans all installed extensions (locally)
  • highlights ones that need attention
  • detects possible overlaps (e.g. multiple wallets / ad blockers)
  • shows enabled vs disabled breakdown
  • suggests actions like:
    • keep
    • disable first
    • review permissions

Design decisions

One thing I realized quickly:

“unused” is actually hard to measure

there’s no clean way to know if an extension is actively used

so instead of guessing, I focused on:

  • permission scope
  • duplication
  • whether the user has reviewed it
  • enabled state

Example from my own setup

I had:

  • multiple crypto wallets enabled at once
  • overlapping extensions in the same category
  • a few extensions I didn’t even remember installing

which made this feel more like a hygiene / safety problem than just “cleanup”

Tech

  • Chrome Extension (Manifest V3)
  • chrome.management API
  • fully local (no backend, no tracking)

Still figuring out

  • how to better define “attention” vs “safe”
  • how aggressive suggestions should be
  • whether to add periodic review reminders

Would love feedback from other builders:

  • how do you personally manage extensions?
  • would you trust a tool like this to suggest removals?
  • anything obvious I’m missing?

happy to share the extension if anyone wants to try it:https://chromewebstore.google.com/detail/extension-manager-cleaner/kkkbalogfpcbhmgobjohlcamikmaedia

reddit.com
u/lingya22 — 12 days ago

I’ve been building Chrome extensions for a while, but recently ran into a problem with my own browser:

I had ~27 extensions installed…
and couldn’t confidently answer:

→ which ones I actually still use
→ which ones overlap
→ which ones might be risky

Chrome gives you a list, but not much context

so I ended up building a small side project:

Extension Manager & Cleaner

What it does

  • scans all installed extensions (locally)
  • highlights ones that need attention
  • detects possible overlaps (e.g. multiple wallets / ad blockers)
  • shows enabled vs disabled breakdown
  • suggests actions like:
    • keep
    • disable first
    • review permissions

Design decisions

One thing I realized quickly:

“unused” is actually hard to measure

there’s no clean way to know if an extension is actively used

so instead of guessing, I focused on:

  • permission scope
  • duplication
  • whether the user has reviewed it
  • enabled state

Example from my own setup

I had:

  • multiple crypto wallets enabled at once
  • overlapping extensions in the same category
  • a few extensions I didn’t even remember installing

which made this feel more like a hygiene / safety problem than just “cleanup”

Tech

  • Chrome Extension (Manifest V3)
  • chrome.management API
  • fully local (no backend, no tracking)

Still figuring out

  • how to better define “attention” vs “safe”
  • how aggressive suggestions should be
  • whether to add periodic review reminders

Would love feedback from other builders:

  • how do you personally manage extensions?
  • would you trust a tool like this to suggest removals?
  • anything obvious I’m missing?

happy to share the extension if anyone wants to try it:https://chromewebstore.google.com/detail/extension-manager-cleaner/kkkbalogfpcbhmgobjohlcamikmaedia

reddit.com
u/lingya22 — 12 days ago

I opened my Chrome extensions the other day and saw this:

27 installed
26 enabled

…and honestly, I had no idea what half of them were doing anymore

What made it worse:

• multiple crypto wallets installed at the same time
• 2–3 ad blockers running together
• some extensions with very broad permissions
• a few I probably haven’t touched in months

but Chrome doesn’t really help you answer:

→ which ones are redundant
→ which ones are risky
→ which ones you can safely remove

So I built a small tool for myself:

Extension Manager & Cleaner

It doesn’t try to track you or anything
just analyzes your installed extensions locally and shows:

• which ones need attention
• possible overlaps (like multiple wallets / blockers)
• enabled vs disabled breakdown
• simple suggestions like “disable first” instead of blindly uninstalling

One thing that surprised me:

I had 4 wallet extensions enabled at the same time
which is… probably not ideal

Also realized:

“unused” is actually hard to measure

so instead of guessing usage, I focused on:

→ permissions
→ duplication
→ whether you’ve reviewed it recently

https://preview.redd.it/iym7n8ms7uyg1.png?width=708&format=png&auto=webp&s=690ccb396d0c87a3afcade17813653eb870ce54e

https://preview.redd.it/sl99q8br7uyg1.png?width=2048&format=png&auto=webp&s=918e10adafacfc82fe42b45c8d09792779a139fa

It’s still early, but already helped me clean things up a lot: https://chromewebstore.google.com/detail/extension-manager-cleaner/kkkbalogfpcbhmgobjohlcamikmaedia

curious how others manage this?

Do you just leave extensions there forever or actually review them?

reddit.com
u/lingya22 — 12 days ago
▲ 0 r/iosdev

I used to just delete random stuff in ~/Library whenever my Mac got full.

Caches, logs, Xcode data… I *thought* it was fine, but I never really knew what would break.

Sometimes nothing happened.

Sometimes something weird slowed down or reset.

That made me realize:

most Mac cleaners tell you how much space you can free…

but not what actually happens after you delete things.

So I built a small tool for myself that tries to make this clearer:

– what the file is

– why it exists

– what happens if you remove it

It’s not trying to clean faster — just make the process less of a black box.

I’m still figuring out whether people actually care about this level of explanation

or if most users just want a one-click clean.

https://github.com/oeljeklaus-you/cleanlens

u/lingya22 — 12 days ago

everyone says:

→ comment early

→ be helpful

→ engage authentically

and yeah… that works sometimes

but I kept noticing something weird:

I’d reply early on a post

put real effort into the comment

…and still get nothing

---

then I tried the opposite:

I ignored timing for a bit

and started looking at *who is still in the thread*

that’s when it clicked:

early doesn’t matter if the conversation is already dying

---

some patterns I kept seeing:

• OP posted… then disappeared

• comments kept growing anyway

• new replies got buried instantly

looks active, but it’s basically a graveyard

---

on the flip side:

• smaller threads

• OP still replying

• fewer comments

but replies actually get noticed

---

so now I don’t ask:

“am I early?”

I ask:

“is this thread still alive?”

---

I’ve been experimenting with ways to measure that:

• OP activity

• last reply timing

• how fast new comments show up

• whether replies still get responses

still figuring it out, but it already changed how I approach Reddit completely

---

curious how others think about this:

do you prioritize timing

or whether the thread is still alive?

reddit.com
u/lingya22 — 13 days ago

everyone says:

→ comment early

→ be helpful

→ engage authentically

and yeah… that works sometimes

but I kept noticing something weird:

I’d reply early on a post

put real effort into the comment

…and still get nothing

---

then I tried the opposite:

I ignored timing for a bit

and started looking at *who is still in the thread*

that’s when it clicked:

early doesn’t matter if the conversation is already dying

---

some patterns I kept seeing:

• OP posted… then disappeared

• comments kept growing anyway

• new replies got buried instantly

looks active, but it’s basically a graveyard

---

on the flip side:

• smaller threads

• OP still replying

• fewer comments

but replies actually get noticed

---

so now I don’t ask:

“am I early?”

I ask:

“is this thread still alive?”

---

I’ve been experimenting with ways to measure that:

• OP activity

• last reply timing

• how fast new comments show up

• whether replies still get responses

still figuring it out, but it already changed how I approach Reddit completely

---

curious how others think about this:

do you prioritize timing

or whether the thread is still alive?

reddit.com
u/lingya22 — 13 days ago

everyone says:

→ comment early

→ be helpful

→ engage authentically

and yeah… that works sometimes

but I kept noticing something weird:

I’d reply early on a post

put real effort into the comment

…and still get nothing

---

then I tried the opposite:

I ignored timing for a bit

and started looking at *who is still in the thread*

that’s when it clicked:

early doesn’t matter if the conversation is already dying

---

some patterns I kept seeing:

• OP posted… then disappeared

• comments kept growing anyway

• new replies got buried instantly

looks active, but it’s basically a graveyard

---

on the flip side:

• smaller threads

• OP still replying

• fewer comments

but replies actually get noticed

---

so now I don’t ask:

“am I early?”

I ask:

“is this thread still alive?”

---

I’ve been experimenting with ways to measure that:

• OP activity

• last reply timing

• how fast new comments show up

• whether replies still get responses

still figuring it out, but it already changed how I approach Reddit completely

---

curious how others think about this:

do you prioritize timing

or whether the thread is still alive?

reddit.com
u/lingya22 — 13 days ago

I used to think Reddit growth was simple:

find active threads → write good comments → get users

but I kept hitting the same wall:

• posts with tons of comments

• still getting replies

• looks super “alive”

…and yet:

→ no clicks

→ no users

→ no conversions

after digging into it, I realized something:

“activity” is not the same as “opportunity”

---

what actually matters more:

• is the OP still replying?

• are new comments getting visibility?

• is the discussion still anchored to the original problem?

because I kept seeing this pattern:

threads with high comments but dead OP = zero conversion

---

so I started building something for myself:

instead of asking

“is this post hot?”

it answers

“is this post still worth replying to?”

---

it now shows things like:

• OP activity (active / inactive)

• last reply timing

• fake active risk

• reply window (fresh / crowded / dead)

basically trying to avoid wasting time on threads that *look* alive but aren’t

---

curious if others noticed this too:

do you manually check if a thread is still alive

or just go by gut feeling?

reddit.com
u/lingya22 — 13 days ago

everyone says:

→ comment early

→ be helpful

→ engage authentically

and yeah… that works sometimes

but I kept noticing something weird:

I’d reply early on a post

put real effort into the comment

…and still get nothing

---

then I tried the opposite:

I ignored timing for a bit

and started looking at *who is still in the thread*

that’s when it clicked:

early doesn’t matter if the conversation is already dying

---

some patterns I kept seeing:

• OP posted… then disappeared

• comments kept growing anyway

• new replies got buried instantly

looks active, but it’s basically a graveyard

---

on the flip side:

• smaller threads

• OP still replying

• fewer comments

but replies actually get noticed

---

so now I don’t ask:

“am I early?”

I ask:

“is this thread still alive?”

---

I’ve been experimenting with ways to measure that:

• OP activity

• last reply timing

• how fast new comments show up

• whether replies still get responses

still figuring it out, but it already changed how I approach Reddit completely

---

curious how others think about this:

do you prioritize timing

or whether the thread is still alive?

reddit.com
u/lingya22 — 13 days ago

I used to think Reddit growth was simple:

find active threads → write good comments → get users

but I kept hitting the same wall:

• posts with tons of comments

• still getting replies

• looks super “alive”

…and yet:

→ no clicks

→ no users

→ no conversions

after digging into it, I realized something:

“activity” is not the same as “opportunity”

---

what actually matters more:

• is the OP still replying?

• are new comments getting visibility?

• is the discussion still anchored to the original problem?

because I kept seeing this pattern:

threads with high comments but dead OP = zero conversion

---

so I started building something for myself:

instead of asking

“is this post hot?”

it answers

“is this post still worth replying to?”

---

it now shows things like:

• OP activity (active / inactive)

• last reply timing

• fake active risk

• reply window (fresh / crowded / dead)

basically trying to avoid wasting time on threads that *look* alive but aren’t

---

curious if others noticed this too:

do you manually check if a thread is still alive

or just go by gut feeling?

reddit.com
u/lingya22 — 13 days ago

I used to think Reddit growth was simple:

find active threads → write good comments → get users

but I kept hitting the same wall:

• posts with tons of comments

• still getting replies

• looks super “alive”

…and yet:

→ no clicks

→ no users

→ no conversions

after digging into it, I realized something:

“activity” is not the same as “opportunity”

---

what actually matters more:

• is the OP still replying?

• are new comments getting visibility?

• is the discussion still anchored to the original problem?

because I kept seeing this pattern:

threads with high comments but dead OP = zero conversion

---

so I started building something for myself:

instead of asking

“is this post hot?”

it answers

“is this post still worth replying to?”

---

it now shows things like:

• OP activity (active / inactive)

• last reply timing

• fake active risk

• reply window (fresh / crowded / dead)

basically trying to avoid wasting time on threads that *look* alive but aren’t

---

curious if others noticed this too:

do you manually check if a thread is still alive

or just go by gut feeling?

reddit.com
u/lingya22 — 13 days ago

Hey everyone,

I’m looking for a few alpha users to test a small tool I’ve been building.

---

What it is:

A CSV cleaner + inspector focused on one thing:

making data changes visible.

Instead of just cleaning data silently, it lets you:

• remove duplicates, normalize values, fix formats

• detect data issues (missing values, invalid entries, inconsistent types)

• see a diff (before vs after for every change)

• preview data in a high-density table

• track transformations (so changes are reversible)

---

Why I built it:

I kept running into the same issue:

cleaning data is easy, but trusting the output isn’t.

Most tools don’t show what actually changed,

so I ended up double-checking manually anyway.

---

What I’m looking for:

• people who work with CSV / exported data

• feedback on real workflows (where it helps / where it doesn’t)

• anything confusing, missing, or unnecessary

---

Link:

https://chromewebstore.google.com/detail/csv-clean-inspector/nnnpjnplnfaeehpaokpboikhnfgimmjo

---

Happy to hear any feedback — even if it’s “this is useless” 😄

u/lingya22 — 14 days ago