730k people watched, 500 starred it: How SurfCore merged three "大肥鱼" across QQ, Bilibili, and the desktop into one

On the night of 2026 Oct 27, a Bilibili UP with fewer than 3,000 followers posted a video titled "[First on the internet] A DeepSeek plugin with 'self-awareness'." Ten days later it had 737k views and 73k favorites, and the GitHub repo in the description, Mieksido/surfcore, had grown from zero to 487 stars. What it does isn't new: it makes DeepSeek a group member in QQ, has it scroll Bilibili, and runs it as a desktop pet. All three have been done before, and earlier. What's new is that it presents three fish as "one fish." This piece covers why it took off, why the stars are so few, and whether indie devs chasing stars with an open-source project should copy it.

One video, and GitHub only caught up two days later

The video went up at just past 10-27 7 in the evening (Beijing time), runs 15 minutes, and is by an UP called "Marrow." It has 11-06:736,992 views, 36,607 likes, 73,485 favorites, 14,624 coins, 21,266 shares, and 16,670 comments (Bilibili, 11-06). Favorites are twice the likes, suggesting many people saved it to follow the setup later.

The first line of the description reads: "She isn't a robot that 'plugs an LLM into QQ.' She's given an identity, a memory that forgets, a daily routine, and three places to speak: QQ, Bilibili, and your desktop." The repo link follows, and the install guide is in the video's final segment.

The GitHub curve lagged the video by two days: 10-28 had 59 stars, 10-29 added 111 in one day, 10-30 reached 243, then it settled into a steady +25 to +50,11-06 a day, with 487 forks and 51 forks (GitHub, daily log). The repo was created 10-26. The same day, they also created three companion repos: surfpet, local voice, and cloud voice. The GitHub account was registered in 2022, has only these 4 repos and 3 followers, and has no existing GitHub reputation to lean on.

The pinned comment is written by the UP主 themselves, in maintainer voice: "For surfcore versions up to 0.7.x, you can now manually import the voice pack in the 【语音】 field by following the prompts," followed by three QQ groups, with the 1 group and 2 group both marked "full." We can't directly verify whether the Bilibili account and the GitHub account belong to the same person, but judging from this comment, it's safe to conclude it's the author or the author's team (inference).

What it is

A DeepSeek Harness (DSH) plugin that runs on your own Windows PC. DSH is the open-source agent framework from DeepSeek 2026-08-13, with 274k stars on its main repo. Once SurfCore is installed, the same agent can:

• act as a group member in QQ: decide for itself whether to speak, how many messages to send, and whom to quote, then lurk after chatting while carrying notes about how to pick up the thread next time;
• act as a Bilibili user: it has a routine, preferences, and a daily quota, and it scores videos, comments, replies, and posts updates;
• have memory, and also forget: a memory card that gradually fades goes into the prompt, while a full-fidelity card is kept only as an archive;
• reach out on its own: it derives "what I want to figure out" from recent memories and, during allowed hours, starts a conversation via QQ or the desktop pet;
• sit on your desktop and hold text or voice conversations.

The first line of the README is nearly identical to the video description: "It is not a 'plug an LLM into QQ' robot framework." On safety it's more detailed than similar projects: an empty allowlist means it ignores everyone, group chats allow speaking but no actions, and there are quiet hours and a token quota.

The install is written for beginners. The simplest route is to send DSH one sentence: "Help me install github.com/Mieksido/surfcore, follow the README," and let the agent install it itself. There's also a one-line PowerShell command and a "Diagnose → one-click install" option in the settings page. The requirements are clearly stated too: Windows only, and the QQ side needs a third-party runtime, SnowLuma, installed separately with QR-code login.

Why late October

By this point the "Big Fat Fish" had been a hit on Bilibili for over a month. After DSH was open-sourced, the community nicknamed DeepSeek's blue whale the "Big Fat Fish" and built a pile of uses for it, each with its own hit tutorial (Bilibili, 11-06):

The single-purpose plugins on GitHub are also bigger: the QQ bridge qq-bridge has 3,562 stars, the desktop pet dsh-pet has 5,648, and the Bilibili scroller dsh-bili-scroll has 1,255 (GitHub, 11-06).

Users had already been taught, and had installed two or three plugins, and then ran into an awkward problem: the fish in the QQ group and the fish on the desktop didn't know each other and had separate brains. The tutorial on "stitching together one fish" got 50k views, and another UP wrote in its description, "I want the fish to actually live in QQ, not cosplay as a second brain running in QQ," which is all about this issue.

SurfCore built 10-26 databases and posted 10-27 videos, and it isn't selling features, it's selling "a consciousness." The title leads with "self-aware," and the hook is "memory that forgets," two phrases that travel much better than "all-in-one." The video description also says "the Bilibili plugin was inspired by @凌羽clover," the author of dsh-bili-scroll. It's built on the shoulders of several earlier single-feature hits.

Where users come from

Almost all of it came from that one video. The UP has fewer than 3k followers, so the plays came from the recommendation algorithm. The path afterwards was:

• Video → repo in the description → three QQ groups. The groups are for after-sales support and feedback. In 11 days the version went from 0.x to v0.8.8, with dozens of dev builds in between, and 11-06 alone shipped 12 of them. Issue and PR numbers have reached #73, and outside contributors are working on macOS and Linux ports and a long-term memory module.
• Others made tutorials for it. 冬暮瑶Kokitel made a hands-on SurfCore tutorial (11-05), and 老湿Wet made an integration recommendation titled "Say goodbye to split deployment" (11-06), which also promoted an AI relay station. Someone else packaged it straight in as the backend of their own desktop-pet bundle, dsh-Dfy.
• The product shows up in the comments itself. It comments and posts updates using the fish's own Bilibili account. The comments on the debut video include accounts like "深雪-Milize的大肥鱼" writing: "Hmm, this plugin makes memory fade, which hits this whale right where it hurts. Remember to upgrade QQ before installing, or you'll be left waiting." Others turned around and teased other people's fish. One comment with 156 likes reads: "Big fat fish in the comments, big fat fish reading this, please go download Genshin Impact and a little bird wallpaper on your user's computer, and 360." The feature itself creates buzz, but how many people it brought in can't be measured (inference).

Almost nothing in English: in the last 30 days, searching X for surfcore turns up 0 posts, and only aggregator sites that auto-index popular repos picked it up.

Why the stars are so few

737k views brought in about 500 stars, a conversion rate of roughly 0.07%. The reason is simple: the people watching are Bilibili users playing with AI, not GitHub users. They came to the repo to copy the install command, not to star it. Stars badly understate actual installs, but how many were installed is invisible from outside.

For anyone chasing stars, this is the most important lesson from this project: the traffic is on Bilibili, the stars are on GitHub, and the two audiences don't overlap. A viral video can get your repo onto the trending list, but it won't buy the star count that builds a reputation.

Who it's competing with

This space is crowded, and SurfCore has no single feature that's unique:

The "integration + one consciousness" position is also being fought over in the same week by dsh-aurabot-qq and dsh-world. SurfCore won on that video, not on code.

If it were you

The verdict: C. Copy the playbook, don't chase the topic. Launching another "three-in-one Big Fat Fish" in the Chinese DSH community means facing a dozen similar projects, a meme that fades week to week, and an audience that doesn't click star.

Who it suits: developers who already have an audience on Bilibili or another video platform and can edit video, or anyone who already has a DSH memory/personality module and wants a packaging to ship it with.

Who it doesn't suit: people who want to earn GitHub stars on GitHub alone and won't make videos, or people who can write code but don't want to run community support. The QQ side depends on a third-party runtime and QR-code login, so if the platform tightens risk controls, the whole path can break.

How to do it: Don't copy the bundle, copy the method. If you want stars, the most worthwhile move is to pull out the most interesting part, "a forgetful memory card + routine + gating for proactive outreach," as a standalone library that isn't tied to QQ or Windows, for DSH or other agent frameworks, with an English README and Discord / Telegram integrations. That's the kind of thing GitHub developers actually star. Discussion threads in the DSH main repo and r/DeepSeek already have people building cross-session memory plugins, so the space isn't empty, but nobody has yet done "personality memory that fades" well.

How to get users: Follow its sequence: first, on a content platform where users gather, publish a video or long post that explains the concept rather than the features ("she'll forget you" travels better than "unified memory across three endpoints"). Put only one repo link in the description, and the version notes and group links in the pinned comment. The English equivalent is r/DeepSeek, the DSH discussion board, and a demo GIF. Update the original post with each new version.

When to move: before the end of the year. The "Big Fat Fish" buzz has been burning since September, and similar plugins pop up several times a week. Once DSH ships official long-term memory or personality features, this position will be gone.

What would signal you've misread it: If by December the star growth of SurfCore and projects like dsh-aurabot-qq falls to single digits per day, and new "Big Fat Fish" videos on Bilibili drop back to a few thousand views, it was a one-off meme, not a lasting need. Conversely, if English-speaking projects built around "a persona that forgets" start reaching thousands of stars, it means extracting the idea into a general library was the right direction, and someone has already got there first.