# earshot: give your coding agent a pair of ears, 22 days to 4,000 stars · GitHub open-source project

> Source: https://stringers.io/en/github/gh_Leonxlnx__earshot.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

> Code-made video is hot and visuals can now be made well, but sound was a weak spot agents couldn't touch. The author already had an old project with 33k X followers and 110k stars. Two demo-backed posts (167k and 270k views), plus reposts from repost accounts and aggregators, pushed it up.

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

Leonxlnx/earshot · Leonxlnx

# earshot: give your coding agent a pair of ears, 22 days to 4,000 stars

**What it is** An open-source tool that lets coding agents like Claude Code listen to sound, score and critique it, and synthesize sound effects with code itself. Pure CPU, no keys required.

**Why it took off** Code-driven video is hot, and while visuals have become workable for agents, sound is a blind spot. The author already had a 33k X following and an older project with 110k stars; two tweets with finished demos (167k and 270k views), plus repost accounts and aggregator sites, pushed it along.

**B** **How you could follow it** Don't build yet another sound-effects library. Use its playbook to find another "can't see, can't hear" gap in agent workflows (motion timing, layout taste, subtitle alignment, etc.), and build a local, key-free tool that can "generate, self-evaluate, rewrite," then launch it with a finished demo. Or build a JS/npm version or a near-instant-startup version that it can't reach.

B grade: the playbook is clear and can be copied, and the "give agents senses" category is still wide open. But its explosive growth relied heavily on the author's 30k followers and an older 110k-star project; unknown followers in the same direction have stalled at a few hundred stars, and the sound slot is now taken. It spreads in small circles

Data (updated daily) · Repo created 2026-10-15 · 4,158 stars · 7 days +782

GitHub · stars

Data 2026-10-16 → 2026-11-08 (24 days, 24 observations). Points before 10-28 come from deeply / archive backfill, not every day has one

earshot is an open-source tool that lets coding agents like Claude Code "listen" to a piece of audio, describe in words and scores what it sounds like, whether it's good, and what to change, and even synthesize sound effects with code. It was created in Oct 15 and reached 6 3,981 stars and 255 forks by Nov. Below: what it is, why it's this one, where the stars came from, who's following it, and where to start if you want a project that earns stars the same way.

### A tweet: "Opus 5.5 can make a full launch video, but the sound effects are still rough"

On the evening of Oct 15, 2026 (UTC 23:40), Munich developer Leon Lin (@LexnLin on X) posted:

> Introducing earshot. Opus 5.5 can build a whole launch video in code but still produces sloppy sfx. so we built earshot. it's ears for AI coding agents… every sound in this video was made with code. (sound on!!)

It accompanied a launch video of roughly a few dozen seconds, where every keypress, whoosh, and impact sound was synthesized from code, with no recordings. By Nov 6 the tweet had 167k views, 2,928 likes, and 3,348 bookmarks (X, 11-06). Three days later, the Oct 18 v0.3 tweet did even better: 270k views, 6,025 likes, and 7,121 bookmarks. Both tweets had more bookmarks than likes, which usually means "save it, I'll need it later."

The opening line was well chosen. In the fall of 2026, "have Claude Code make launch videos with code" was hot, and GitHub was full of visual-generation agent skills (video-shotcraft 17k stars, html-video 4,810 stars, ffmpeg-skill 4,594 stars). Visuals had become decent, but sound was something agents couldn't touch: they could write code that plays a sound, but couldn't hear what they were playing. earshot's first line hit that pain point directly.

### What it actually does

The README's first paragraph is blunt: agents can now write code that renders a film, a demo, or a game, "but they can't hear what they made. They can't tell a premium keypress from a cheap one, they don't notice a landing that's 80 ms late against the cut, and they can't hear the music swell in the wrong place."

earshot turns sound into evidence that agents can read and reason about:

- **Listen** : `describe` says what a file sounds like (e.g., "most like a mechanical keyboard press, z +5.4"); `match` checks whether a description fits the sound; `find` locates the best-fitting moment in a long recording; `critique` compares a whole piece against 7 professional launch videos and returns a timestamped revision list ("first fix: no sound reaches main volume before 0:01.01").

- **Make** : `forge` lets an agent write a sound recipe in code, render it, score it itself, revise the recipe, and render again; `fit` goes the other way, turning a recording into code with tunable parameters.

- **Use** : it ships with 252 code-made sound effects (v0.4, Nov 6), `sfx` aligns a sound to a frame at a given moment on screen, and `kit` scores an entire piece in one go.

It runs on pure CPU with no API keys, offers CLI, Python, and MCP interfaces, and plugs into Claude Code with a single `claude mcp add` line. Only one optional subcommand calls Gemini to "listen," and that requires your own key and explicit consent to upload.

### Where the stars came from

Daily star counts line up with the tweets at both steps:

| Date | Cumulative stars | What happened |
|---|---|---|
| 10-15 | 0 | Created, launch tweet posted that night |
| 10-17 | 240 | First wave from the launch tweet |
| 10-18 | 602 | The v0.3 tweet that night |
| 10-20 | 1,347 | +603 in a single day, the biggest of the whole run |
| 10-21 | 1,854 | Aftershocks of v0.3 |
| 10-28 | 3,082 | Then +60 to +190 per day |
| 11-06 | 3,981 | Back to +100 to +185 per day from 11-03 |

(GitHub stars per day, as of 11-06; the daily figures for 10-15 and 10-16 are missing.)

**First, the author's own X account is the main engine.** Leon Lin is no newcomer: his taste-skill has 111k stars, he has 33k followers on X and 2,838 followers on GitHub, and his whole account is a run of "agent skill + pure-code visual" projects. One post drew hundreds of thousands of impressions, so cold-start cost was close to zero. Not every post took off, though: the v0.2 tweet only got 3,405 views; the two that did had finished demos with playable sound.

**Second, his projects cross-promote each other.** His other project, cinetic (1,050 stars, a skill for making motion-graphics videos with code), lists earshot 0.4 as a dependency, and every sound effect in its videos comes from the earshot kit. The v0.3 release post even has a line: "earshot is now used in cinetic".

**Third, repost accounts and aggregators relayed it.** After Oct 19, Instagram filled with reels using "Comment 'sound' for link" (keyword-gated links, a common follower-growth trick), with captions like "1,500 developers fixed Claude's hearing." Threads, Facebook, YouTube explainers, and LinkedIn all reshared it; alphasignal, faun.dev, dev.to, Medium, and tech sites in Japanese, Korean, and Turkish all covered it, and a post on reddit r/BestGitHubRepos titled "3.1k stars" also appeared. The steady one or two hundred stars a day in the second half most likely came from this secondary distribution (inference; we couldn't verify the view counts of each post or how many stars they brought in).

**Absent:** Hacker News and Product Hunt never featured it, and no paid promotion turned up.

### Who it's competing with

Before earshot, the "agents listen to sound and give evidence" niche was almost empty.

| Project | Launched | Scale (stars) | How earshot differs |
|---|---|---|---|
| ElevenLabs MCP | 2025-03 | 1,548 | Official big-tech offerings: cloud voice and sound-effect generation, requires a key and pay-as-you-go; no listening or scoring |
| audio-studio-mcp | 2026-10-18 | 591 | Local generation of music and sound effects with Stable Audio 3, needs a GPU or Apple silicon; no "listen, then revise" loop |
| vibe-motion/sound | 2026-10-28 | 288 (7 days +239) | Searches ready-made sound effects on stock sites like Pixabay and Freesound and re-ranks them; no synthesis or analysis |
| Audacity-MCP | 2026-03 | 132 | Lets agents edit audio in Audacity; it's an editing tool, not ears |
| bryllim/fun-sfx | 2026-11-02 | 40 | Agent skill plus a sound-effects catalog; licensing sources aren't clearly stated |
| claud-ear, mcp-listen, mcp-audio-server, and similar | From ¥2025-06 | Single digits | Mostly speech-to-text or microphone capture |
| Multimodal models like Gemini that can process audio | Already there | — | They can listen, but you have to upload, results vary each time, and there's no comparable score |

The video-generation skills that make visuals aren't rivals; they're upstream and downstream of it.

Worth noting on timing: the same-category audio-studio-mcp, vibe-motion/sound, and fun-sfx all showed up after Oct 18. Whether they're related to earshot is unclear, but they've all stalled under a few hundred stars. The work isn't necessarily much worse than earshot's. What they lack is an author with 30k followers.

### What it still gets wrong

- **Slow.** The README says it plainly: every CLI call is a fresh process that spends 20 to 40 seconds loading the model before answering. For continuous use you need to run the MCP server or write a Python script.

- **Not easy to install.** The #5 issue is titled "Easy install". Others have reported that model loading clears users' Hugging Face offline settings, and that the weights download without a pinned version (10-18 is closed).

- **Python only.** Many people making code-driven video live in the JS ecosystem (Remotion, HTML animation), so they'd have to set up a separate Python environment.

- **Unknown real usage.** Stars and bookmarks are high, but pip download counts and MCP install numbers aren't public.

### If it were you

**Bottom line:** earshot has already claimed the sound slot. Another "sound effects for agents" library will most likely stall at a few hundred stars. The better bet is to use the same playbook and look for the other "can't see, can't hear" gap in agent workflows.

**Who it's for:** developers already using Claude Code or Cursor for concrete work (video, UI, games) who can name the exact step where "the agent needs me to check it by eye." Ideally they already have a few hundred to a few thousand followers on X or GitHub.

**Who it's not for:** people hoping to ride the heat by building "another earshot", and people without a demo that makes the idea obvious at a glance.

**How to do it:**

1. Look for sensory gaps. Turn a subjective "is this good?" into something an agent can read: scores, timestamps, revision checklists. Candidate areas (inferred, not checked one by one for overlap): whether motion timing and easing feel right, whether typography and color look "professionally made", whether subtitles and voiceover are in sync, game feel, and readability of UI screenshots.

2. Close the loop. Don't just critique: generate → self-review → revise. earshot's forge is one reason its v0.3 tweet got more attention than the launch.

3. Zero friction. Runs locally, needs no key, and plugs into Claude Code or Cursor with one command.

4. Or build the part earshot did poorly: an npm version, startup in seconds, "ears" that embed directly in a Remotion workflow. That audience, JS developers, is exactly where earshot doesn't reach.

**How to get stars:** pin the launch copy to the hottest model and the hottest use case (his was "Opus 5.5 can make a whole launch video, but the sfx are sloppy"). Ship a finished demo so people see the result without installing. Post a separate demo tweet for each major version, not just a changelog. If you have other projects, have them depend on each other and send traffic back and forth. After launch, repost accounts and aggregator sites will pick it up on their own.

**How long the window lasts:** the "agents making video with code" trend is still climbing, roughly the next two or three months. Once official tools or big companies build this kind of review capability into their products, the slot closes.

**Signs you picked the wrong direction:** a GitHub search already turns up projects with several hundred stars or more; or the launch tweet with the demo doesn't pass ten thousand views within a week and stars stay in the double digits. That means the gap isn't painful enough, or the demo didn't make the idea clear. Change direction. Don't just post more times.

[GitHub repo ↗](https://github.com/Leonxlnx/earshot)

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

Competitors

| Name | Where | Launched | Scale | How it differs from this one |
|---|---|---|---|---|
| ElevenLabs MCP | Big-company features | 2025-03 | 1,548 stars | Cloud TTS/SFX generation, paid with a key; doesn't listen or critique |
| audio-studio-mcp | Open source | 2026-10-18 | 591 stars | Local Stable Audio 3 generates BGM/SFX; needs GPU/Apple Silicon; no review loop |
| vibe-motion/sound | Open source | 2026-10-28 | 288 stars | Searches existing SFX libraries and ranks them; doesn't synthesize or analyze |
| Audacity-MCP | Open source | 2026-03 | 132 stars | Lets agents edit in Audacity; not auditory review |
| claud-ear / mcp-listen / mcp-audio-server and others | Open source | 2025-06–2026-05 | Single-digit stars | Mostly speech transcription or microphone capture |
| Gemini and other audio LLMs | Big-company features | Already there | — | Can listen, but requires uploads, has no calibrated scores, and isn't reproducible; earshot only offers it as an optional subcommand |
| video-shotcraft / html-video / ffmpeg-skill | Open source | 2026-05–09 | 17,238 / 4,810 / 4,594 stars | Handles visuals and editing but has no sound component; complementary to earshot |

Where users come from

- **Verified** **author's X tweets** : launch tweet 10-15:2,928 likes, 3,348 bookmarks, 166,759 views; v0.3 tweet 10-18:6,026 likes, 7,121 bookmarks, 270,122 views (fxtwitter); the star growth steps match

- **Verified** **author's existing assets and cross-promotion** : taste-skill 111,042 stars, X 33,242 followers; cinetic's README lists earshot 0.4 as a dependency

- **Verified** **short-form video and social reposts** : multiple Instagram reels with "Comment sound for link", Facebook videos, Threads @nick_saraev, YouTube explainers, LinkedIn

- **Verified** **SEO/aggregator sites and tutorials** : alphasignal, faun.dev, dev.to/Medium, coderefer, frontiernow, Japanese/Korean/Turkish article sites, r/BestGitHubRepos

- Inferred **HN / Product Hunt / ads** : our hackernews and producthunt databases don't include this project; no ads found

## Why earshot (Leonxlnx/earshot) took off

**In one line** : an open-source tool that gives coding agents "ears" (CLI / Python API / MCP, CPU-only). Agents can describe, match, locate, and score a sound in text and numbers. They can also synthesize sound effects with code, listen and revise (`forge`), reverse-engineer a recording into code (`fit`), and ship with a library of 252 code-generated sound effects and a `kit` that adds sfx to launch videos.

**Conclusion** : it didn't come out of nowhere in a "new category". An author with an existing 110k-star project (taste-skill) and 33k X followers filled the most obvious gap in the "write code with Claude Code to make launch videos" workflow at the height of that trend: sound. Two X tweets pushed it (the launch got 167k views; v0.3 got 270k views), and then a large number of Instagram/Threads repost accounts and SEO blogs redistributed it.

### 1. Data

- GitHub (our github database, repo_profile / repo_day, as of 2026-11-06): 2026-10-15,3,981 stars since the repo was created, 255 forks (fork/star 6.4%); +7 over the last 759 days, +7 over the first 1,113 days, largest single day +603 (2026-10-20). No suspect flag.

- Curve (repo_day): 10-17 240 → 10-18 602 → 10-19 744 → 10-20 1,347 → 10-21 1,854 → 10-24 2,420 → 10-28 3,082 → 11-01 3,376 → 11-06 3,981. Both steps line up with the tweets: the launch tweet (10-15 later) brought the first wave, and the v0.3 tweet (10-18 later) brought the biggest jump, 10-20/21. After that, stars rose steadily at 60–190 a day, with a small rebound from 11-03 (+100~185/day) that matches v0.4 and the timing of external articles and short-video reposts (inferred).

- Author Leon Lin (Munich; 2,838 GitHub followers, X @LexnLin with 33,242 followers; GitHub API 2026-11-06): taste-skill 111,042 stars, unlazy 4,316, agentic-ai-prompt-research 2,566, cinetic 1,050, athenaion 685… The whole account is a series on "agent skills + making visuals purely with code".

### 2. Competitors

| Name | Where | Launched | Scale | How earshot differs |
|---|---|---|---|---|
| ElevenLabs MCP(elevenlabs/elevenlabs-mcp) | Open-source / big-company APIs | 2025-03 | 1,548 stars | Cloud TTS/SFX generation, requires a key and pay-per-use; doesn't "listen" or score sound |
| audio-studio-mcp(kanaworksai-hue) | Open source | 2026-10-18 | 591 stars, +7 in 57 days | Local BGM/SFX generation with Stable Audio 3; needs a GPU or Apple Silicon; no review loop |
| vibe-motion/sound | Open source | 2026-10-28 | 288 stars, +7 in 239 days | Searches Pixabay/Freesound/Mixkit for existing sound effects and ranks them; asset retrieval, no synthesis or analysis |
| bryllim/fun-sfx | Open source | 2026-11-02 | 40 stars | Agent skill + sound effect catalog; licensing not verified |
| xDarkzx/Audacity-MCP | Open source | 2026-03 | 132 stars | Lets agents edit in Audacity; an editing tool, not "ears" |
| Null-Phnix/claud-ear, mcp-listen, mcp-audio-server, media-context-mcp and others | Open source | 2025-06–2026-06 | Single-digit stars | Most are only transcription (Whisper) or microphone capture; they don't judge sound effects semantically |
| Gemini and other audio LLMs | Big-company features | Already there | — | Can listen, but requires uploads, isn't repeatable, and has no calibrated scores; earshot only offers it as an optional `llm` subcommand |
| Video skills: video-shotcraft (17,238 stars), html-video (4,810), ffmpeg-skill (4,594), scenario-labs/skills (2,941) | Open source | 2026-05–09 | Big | They handle visuals, editing, or calls to generative models. earshot fills the sound gap they leave, so it's more complementary than competing |

Conclusion: the "agent listens to sound and gives reasoned evidence" slot is nearly empty. Similar MCP tools are either transcription or generation, with very low star counts. The only comparable-scale projects are generation tools (ElevenLabs) and video skills, and those complement earshot rather than compete with it. Sources: GitHub API, our github database (2026-11-06), Exa search.

### 3. Growth tactics (evidence)

1. **The author's own X tweets (main driver, verified)** : launch tweet 2026-10-15 23:40 UTC "Opus 5.5 can build a whole launch video in code but still produces sloppy sfx. so we built earshot": 2,928 likes / 141 reposts / 3,348 bookmarks / 166,759 views. v0.3 tweet: 2026-10-18 6,026 likes / 343 reposts / 7,121 bookmarks / 270,122 views (fxtwitter API, read via r.jina.ai, 2026-11-06). The v0.2 tweet had only 3,405 views, so not every post takes off. What works is a major release with a demo video. browser-use co-founder @gregpr07 replied under the launch tweet.

2. **Author's existing assets** : taste-skill's 111k stars bring GitHub and X followers; sister project cinetic (1,050 stars, a "code-driven launch video" skill) lists earshot 0.4 as a dependency in its README, with all its sound effects coming from the earshot kit. Projects cross-promoting each other (confirmed in the cinetic README).

3. **The demo is the ad** : the README's first line is a 22-second launch video. It says "every sound is made with earshot forge from code, no recordings, no music", and the tweet says "sound on!!". The shareable finished video is itself the distribution.

4. **Repost accounts / short video (confirmed to exist, scale not verified)** : multiple Instagram reels ("Comment \"sound\" for link" keyword-gated follower growth, "1,500 devs fixed Claude's hearing"), two Facebook video pages, Threads @nick_saraev (1.6K views), YouTube explainers, LinkedIn shares.

5. **SEO / aggregator sites (confirmed)** : alphasignal.ai, faun.dev (toolbox + 11-04 news), themenonlab, coderefer, dev.to/Medium (dedupedai tutorial), frontiernow, crazycoderslab, Japanese ai-kidou.jp, Turkish yapaytu, Korean kaitabase, and the reddit r/BestGitHubRepos post ("3.1k stars"). These are mostly second-wave coverage published after 10-19, and they sustained the steady star growth in the second half.

6. **Not found** : HN (our hackernews database lists three unrelated projects named Earshot), Product Hunt (none), paid ads (none found). GitHub trending doesn't pick up repos younger than 60 days, so its absence means nothing.

### 4. Why it took off

- **Timing** : In 2026 autumn, "Claude Code/Opus 5.5 makes launch videos with code" was blowing up (video-shotcraft at 17k stars, html-video, a pile of Remotion/HyperFrames skills). The visuals could already be made well; sound was the visible weak spot. earshot's launch copy went straight at that pain point.

- **Author resources** : The author of taste-skill (110k stars) also has 33k followers on X. One post drew over a hundred thousand impressions, so cold-start cost was close to zero.

- **The product itself** : It turns "does it sound good" into evidence an agent can read (calibrated z-scores, timestamps, a fix list, annotated charts). It's pure CPU, needs no key, and hooks in with one line, `claude mcp add`. Add forge (write code to make sound, listen, revise) and 252 code-made sound effect libraries, and it can both judge and make audio.

- **Frequent iteration + a demo for every version** : 10-15 at launch, 10-16 at v0.2, 10-18 at v0.3, and about 10-22 at v0.4. Each major version came with a demo post with sound, and the v0.3 one did better than the launch.

- **Shareable output** : "Every sound here was made with code" is itself a topic, and it suits short-video repost accounts doing "comment for link."

### 5. Differentiation

Similar MCPs either do transcription (listen to people talk), generation (ElevenLabs, Stable Audio), or asset search. earshot's difference is that it gives an agent a **sound reviewer it can call repeatedly** : describe, match, locate, judge real vs. fake, transcribe a full track, and score it against 7 professional release tracks. It uses that reviewer to drive a closed loop of "synthesize code → score → rewrite," all offline, on CPU, for free. It also slots into the "code-made video" workflow that's hot right now (cinetic depends on it directly). That difference is why people bookmarked it (the launch post got 3,348 bookmarks, v0.3 got 7,121, and bookmarks/likes exceed 1, which suggests "save it to use later"). But what got it **seen** was mainly the author's distribution and timing. The same thing from an unknown author would most likely have stalled at a few hundred stars (compare audio-studio-mcp at 591 stars and vibe-motion/sound at 288).

### 6. Visibility and copycats

- Visibility: **It's spreading in small circles** . On X among AI coding and agent-skill people, it has tweets at roughly the 270k-views level, and a dozen aggregator sites and repost accounts have covered it. But it never made Hacker News or Product Hunt, and no mainstream tech outlet or big account ran a long piece on it. It's open source and free, so there's no revenue.

- Copycats: After 10-18, similar "give agents sound effects" libraries appeared: kanaworksai-hue/audio-studio-mcp (10-18,591 stars), vibe-motion/sound (10-28,288 stars), bryllim/fun-sfx (11-02,40 stars), sarpstar/cinecode (11-03,397 stars, code-made film). I haven't verified whether earshot directly inspired them, but their timing clusters right after it blew up.

### 7. Takeaways

- Find a sensory gap (agents can't see or hear) in a hot agent workflow, turn subjective quality into a score an agent can read, with timestamps and fix suggestions, and offer a "generate → self-score → rewrite" loop.

- Launch copy is pinned to the model and usage that are hot right now ("Opus 5.5 can make a whole launch video, but the sound is rough"), with a finished demo that has sound.

- One author builds a chain of interdependent projects (cinetic ↔ earshot) and posts a demo-backed update for each major version.

- Zero-friction setup: pure CPU, no key, one MCP command.

### 8. Uncertain

- Actual usage (pip downloads, MCP install counts) is unchecked. Stars aren't the same as use.

- I haven't verified the play counts on Instagram/Facebook repost accounts or how many stars they drove. I found no evidence of paid promotion by the author.

- I don't have day-by-day star counts for 10-15 to 10-16 in our database (data starts at 10-17).

- I haven't verified whether "we built" implies co-authors.

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