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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 Aufrufe • vor 3 Monaten •via X (Twitter)

36 Kommentare

Profilbild von Kelvin Lee
Kelvin Leevor 3 Monaten

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

Profilbild von CodeRabbit
CodeRabbitvor 3 Monaten

🫂

Profilbild von S.A.LONGTIN🐉🐦‍🔥🥷🫵😂🙏🙏🙏🤲🙏Smaugly.Sπuggles.
S.A.LONGTIN🐉🐦‍🔥🥷🫵😂🙏🙏🙏🤲🙏Smaugly.Sπuggles.vor 2 Monaten

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

Profilbild von CodeRabbit
CodeRabbitvor 2 Monaten

🤝

Profilbild von S.A.LONGTIN🐉🐦‍🔥🥷🫵😂🙏🙏🙏🤲🙏Smaugly.Sπuggles.
S.A.LONGTIN🐉🐦‍🔥🥷🫵😂🙏🙏🙏🤲🙏Smaugly.Sπuggles.vor 2 Monaten

Orange bunny is fren 😂

Profilbild von Toufiq Qureshi
Toufiq Qureshivor 1 Monat

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. 🤔

Profilbild von Borboleta silenciosa
Borboleta silenciosavor 2 Monaten

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

Profilbild von Dipanshu Kushwaha
Dipanshu Kushwahavor 2 Monaten

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

Profilbild von Talha Raza
Talha Razavor 1 Monat

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

Profilbild von Shashank Bhardwaj
Shashank Bhardwajvor 2 Monaten

You are my best friend, bro

Profilbild von Noah Sheldon
Noah Sheldonvor 2 Monaten

Customisation of review agents are amazing thanks

Profilbild von CodeRabbit
CodeRabbitvor 2 Monaten

Glad you like it!

Profilbild von Ariel Lillie
Ariel Lillievor 1 Monat

dial in quiet when codebase reviews get noisy

Profilbild von Salise
Salisevor 1 Monat

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

Profilbild von BiOne_98
BiOne_98vor 1 Monat

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.

Profilbild von ag
agvor 2 Monaten

this is awesome massive respect for tuning review depth

Profilbild von dophp.dev
dophp.devvor 2 Monaten

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.

Profilbild von Chris Petersen
Chris Petersenvor 2 Monaten

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Profilbild von CryptoSuggest
CryptoSuggestvor 2 Monaten

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

Profilbild von Amanda Lauren Machen
Amanda Lauren Machenvor 2 Monaten

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 🌧️.

Profilbild von Blondie Spark NFT
Blondie Spark NFTvor 1 Monat

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.

Profilbild von Jone smitt
Jone smittvor 3 Monaten

From code rabbit Ai please help for me

Profilbild von Navneet Kaur
Navneet Kaurvor 2 Monaten

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

Profilbild von nellyd
nellydvor 1 Monat

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

Profilbild von RajX-dev
RajX-devvor 2 Monaten

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

Profilbild von していたー
していたーvor 1 Monat

これめっちゃ便利そう!👍

Profilbild von Bia Bia
Bia Biavor 1 Monat

👏👏

Profilbild von 汤姆
汤姆vor 2 Monaten

可以可以

Profilbild von PD_KoDak
PD_KoDakvor 2 Monaten

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.

Profilbild von Chris
Chrisvor 2 Monaten

J

Profilbild von Ajcrowlex1177
Ajcrowlex1177vor 2 Monaten

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

Profilbild von mohan lal
mohan lalvor 2 Monaten

B. Vo kabhi PM nahi banega

Profilbild von Mrfuszy
Mrfuszyvor 2 Monaten

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

Profilbild von Parvez
Parvezvor 2 Monaten

BAS

Profilbild von kong
kongvor 2 Monaten

70

Profilbild von SD House Mafia
SD House Mafiavor 2 Monaten

Lmao no thx

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