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One codebase, three identical PRs, three different CodeRabbit review profiles quiet - only the most important feedback chill - balanced (the default) assertive - most comprehensive Dial in the review depth that fits your team. More signal, less noise, tuned to your team.

21,927,402 次观看 • 3 个月前 •via X (Twitter)

36 条评论

Kelvin Lee 的头像
Kelvin Lee3 个月前

I had a message today saying my trial was ending , very sad moment until I subscribed. Guys thank you for such awesomeness 🤙🏻 🫶🏼 sending some man love

CodeRabbit 的头像
CodeRabbit3 个月前

🫂

S.A.LONGTIN🐉🐦‍🔥🥷🫵😂🙏🙏🙏🤲🙏Smaugly.Sπuggles. 的头像
S.A.LONGTIN🐉🐦‍🔥🥷🫵😂🙏🙏🙏🤲🙏Smaugly.Sπuggles.2 个月前

Ok this is leaning more towards my style. Will dive in once I have a proper set up.

CodeRabbit 的头像
CodeRabbit2 个月前

🤝

S.A.LONGTIN🐉🐦‍🔥🥷🫵😂🙏🙏🙏🤲🙏Smaugly.Sπuggles. 的头像
S.A.LONGTIN🐉🐦‍🔥🥷🫵😂🙏🙏🙏🤲🙏Smaugly.Sπuggles.2 个月前

Orange bunny is fren 😂

Toufiq Qureshi 的头像
Toufiq Qureshi1 个月前

Genuine question for CodeRabbit 👀 I’m using Claude Code to write my code, and then CodeRabbit reviews that same code and says: “Here’s an issue with your code.” So I’m curious — what makes your review different? If the underlying AI reasoning is similar, why can one AI confidently write the code while another confidently flags it as wrong? Is it the context, system prompt, tools, review methodology… or something else? Would love to understand what’s actually happening under the hood. 🤔

Borboleta silenciosa 的头像
Borboleta silenciosa2 个月前

Confesso que só agora fui descobrir o que é o @coderabbitai 😂 Uma IA que revisa códigos, encontra erros e sugere melhorias. Pelo tanto de elogios que vejo por aqui, parece que os programadores ganharam um ótimo parceiro de trabalho! 🤖🐰 vou indicar para meu filho que é TI Conheça o CodeRabbit

Dipanshu Kushwaha 的头像
Dipanshu Kushwaha2 个月前

This is a neat way to customize the review process. It's great to have options for different needs.

Talha Raza 的头像
Talha Raza1 个月前

three profiles, same codebase, but who decides what counts as signal. the quiet mode isn't less noise, it's less accountability. teams tune out what they don't want to hear

Shashank Bhardwaj 的头像
Shashank Bhardwaj2 个月前

You are my best friend, bro

Noah Sheldon 的头像
Noah Sheldon2 个月前

Customisation of review agents are amazing thanks

CodeRabbit 的头像
CodeRabbit2 个月前

Glad you like it!

Ariel Lillie 的头像
Ariel Lillie1 个月前

dial in quiet when codebase reviews get noisy

Salise 的头像
Salise1 个月前

this sounds super useful for tailoring feedback to team needs. nice way to cut through the noise

BiOne_98 的头像
BiOne_981 个月前

This is not three reviewers and not three analysis depths on the same PR. It is one pipeline — change graph, tools, agent pass, judge — with a publication threshold and some static-analysis strictness cranked up or down. Docs make that explicit: PHPStan under chill is roughly level 3 (real type/offset bugs); under assertive it jumps to level 8 (dead code, null safety, typehints). The “intelligence” does not change. The policy for what is worth a comment does. “One codebase, three identical PRs” is a weak claim for three reasons. 1. LLM review is stochastic. Without a fixed SHA, model version, identical knowledge-base/learnings context, and a comment-level diff, this is a montage, not an experiment. Three chill runs can already diverge. 2. If analysis is identical and only the emission filter changes, the comparison is fair — then say that: you are cutting output. If the agent is re-run with a different system prompt, the findings are not comparable: coverage and hallucinations both move. 3. “Most important” is undefined. Importance without a risk model (prod impact × likelihood × blast radius) is prompt taste. Quiet mode cuts noise and raises false negatives on the hard stuff: cross-file logic, races, API contracts, migrations. That is already where AI review is weak — decent precision on individual comments, poor completeness. The two extremes are not symmetric. • assertive burns trust faster than it catches bugs. Alert fatigue on a bot is worse than missed nits: the team starts skipping every comment, including security. • quiet creates a false “all clear.” No comment ≠ no defect. Especially dangerous for junior-heavy teams. A three-level enum is too coarse. A real review policy needs orthogonal axes — some of which CodeRabbit already has, and which the tweet hides: • category: correctness / security / observability / style / docs • severity + confidence (block merge vs nit) • path policy: src/api/** ≠ **/*.test.ts ≠ generated/lockfiles • dedup against CI you already run (ESLint, Ruff, Semgrep). Repeating a failing pipeline check is noise, not “comprehensive review” • separate max-depth analysis from filtered publication. Otherwise quiet does not just stay silent — it searches worse Practical setup for a mature team: chill or quiet + path_instructions + style tools disabled if they already live in CI + hard pre-merge checks only on security/correctness. Keep assertive for onboarding, legacy audits, or repos with no linters. Not as the rabbit’s personality. As an SLO: how many comments per 100 LoC of diff the team will actually triage. Short version: useful as an SNR knob. Not evidence of deeper engineering. It is prompt/policy routing with three labels. The real question is whether quiet drops only nits, or also the defects a human reviewer was supposed to catch.

ag 的头像
ag2 个月前

this is awesome massive respect for tuning review depth

dophp.dev 的头像
dophp.dev2 个月前

I would love assertive but credits don’t even last on chill. Frustrating as I want to use the tool but it is so restrictive in its availability for my code for some reason.

Chris Petersen 的头像
Chris Petersen2 个月前

Sentinel Fuel Yield ($SNFY) is a Solana-based security infrastructure token designed to protect crypto users from scams, rug pulls, and malicious transactions in real-time. Built by someone who got scammed and decided to fix the problem instead of walking away, Sentinel uses AI-powered transaction analysis to flag dangerous wallets, phishing attempts, and suspicious smart contracts **before** users lose their money. This isn't a meme coin. This is a security layer the entire Web3 space desperately needs. --- ## 💔 **THE PROBLEM** **Crypto scams stole $5.6 billion in 2023 alone.** Every day, thousands of people: - Connect their wallets to fake dApps - Send funds to scammer addresses

CryptoSuggest 的头像
CryptoSuggest2 个月前

Revenue → Buyback → Burn. That's a model worth watching. Execution will decide everything. 👀

Amanda Lauren Machen 的头像
Amanda Lauren Machen2 个月前

Cloud flare needs constant repair , so much ! My mind is creating rain with thoughts and projecting plasma from the sun into the air to make rain 🌧️.

Blondie Spark NFT 的头像
Blondie Spark NFT1 个月前

Great to see customizable review profiles! Quiet, chill and assertive on the same codebase – how do these practically affect team productivity and the number of issues found long-term? More signal, less noise.

Jone smitt 的头像
Jone smitt3 个月前

From code rabbit Ai please help for me

Navneet Kaur 的头像
Navneet Kaur2 个月前

Having options for how much feedback you get is a great idea.

nellyd 的头像
nellyd1 个月前

I really need $550 and I just will appreciate so I not broke and stessed out every. Day

RajX-dev 的头像
RajX-dev2 个月前

I made something better than you guys Reach out to me . This is my website

していたー 的头像
していたー1 个月前

これめっちゃ便利そう!👍

Bia Bia 的头像
Bia Bia1 个月前

👏👏

汤姆 的头像
汤姆2 个月前

可以可以

PD_KoDak 的头像
PD_KoDak2 个月前

This is exactly how AI code review should work. Not every team needs more comments. They need the right comments. Quiet when you want signal. Chill for balance. Assertive when you want to leave no stone unturned. More signal, less noise.

Chris 的头像
Chris2 个月前

J

Ajcrowlex1177 的头像
Ajcrowlex11772 个月前

Where is my apology? (Mothers side of family) (Liberal friends from college) (Two girlfriends) Fuck all of you bastards, the truth shall prevail

mohan lal 的头像
mohan lal2 个月前

B. Vo kabhi PM nahi banega

Mrfuszy 的头像
Mrfuszy2 个月前

Ones on meth, ones on coke, the others on Adderall! Help is out there my friend stay strong were gonna get thrw this

Parvez 的头像
Parvez2 个月前

BAS

kong 的头像
kong2 个月前

70

SD House Mafia 的头像
SD House Mafia2 个月前

Lmao no thx

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