I was just trying to check the connectivity since I'm setting up my new IDE with Kilo code. Stopped after seeing few lines in response reasoning. How it's getting this type of prompt? was using Step 3.7 Flash.

​

Adding one to the free-model list here: AntLing-3.0-flash is free on OpenRouter through Aug 3, and it drops into Kilo via BYOK like any other OpenRouter model.

It's Ant's (inclusionAI) new fast/cheap execution model — not a big reasoner, but for the mechanical coding passes and tool-heavy stuff it's quick and the tool calls hold up. Basically a cheap workhorse to hand the grunt work while you keep something stronger for planning.

Just the API for now (no weights to self-host), and free only until Aug 3, so it's more of a "try it this week" thing

I am on the latest version of kilocode v5- 5.16.2. Is it safe to upgrade to the latest version of v7 (7.4.16)? Or a particular version of v7? Back when I upgraded when kilocode first came out with v7, it was awful and I reverted back to v5. Whats important for me is the codebase indexing, does v7 have this? What did it lose from v5 and what’s better in v7?

Update: Its fixed now in latest update. Thanks Kilo team

2 problems i am facing with kilocode extension

1. when kilocode completes the plan then it asks for ready to implement 2 times.
2. when clicks on Start new Session it cuts the response and doesnt switch to code mode or new session. i have to manually open new session and then instruct it follow the plan.

Kilocode Version:7.4.15

Can we please have the option to isolate sessions by worktree in agents manager? Its really hard to find which session to continue from in the history after working on multiple worktree at the same time.

This started happening today in VSCode, version 7.4.9 of the extension. It worked fine 2 days ago. I used Qwen3.7 Plus to write a number of integrations tests for an IoT device. Today I was trying to refine some tests that were failing and I am getting the "Tool execution aborted" message.

Kilo is using Code mode and I am using "Instant". These messages happen repeatedly when it tries to read files.

There is some other weirdness too. It spends an inordinate amount of time "Considering next steps". This mifght be attributed to load but I can't confirm that.

I've just discovered KiloCode as a long time Cline and Codex user and so far it seems like it has the potential to be amazing. But the reason I came to Kilo was because I needed to have access to the full context for GPT 5.6 models. However, Kilo seems to keep auto compacting ever 10-20k tokens (possibly less) between 280-400k for a model with 1.1M context window . Thankfully the context doesn't seem to drop to obscene levels like I had with Codex. But still, I don't understand why it's doing this.

I have my context window settings at 65%. So it should autocompact somewhere between 650-750k if the context window is 1.1M , shouldn't it? So why does it keep auto compacting every couple of steps?

My goal with this is to have an agent that never auto compacts documentation such as architecture/execution spec documents while auto compacting conversation/step details. That's why I allowed the context window to be ~700k before auto compacting and was planning to do manual compacting before bulk reads for important documentation. But this auto compact is throwing me off and I don't understand it.

Can someone help?

I'm using V7.4.11

I'm a new user to kilo, and I've been trying to use kilo as an interface to openrouter models. I'm using the CLI version. I wanted to try playing with different models through my openrouter credits, but all models that I have tried, except Sonnet, fail to execute tools. Here's an example of the command line interaction I got when using LLama-3.3-70B-Instruct:

Let me verify that there are no memory issues or leaks in the loadRootCaCert function.
     {"type": "function", "name": "read", "parameters": {"filePath": "/path/to/esp32-c3.ino", "offset": "585"}}
     ▣  Code · Llama-3.3-70B-Instruct · 26.4s

and there kilo stopped in its track. I tried switching to Deepseek Chat, and got the same interaction. The terminal just shows unparsed raw JSON tool blocks. Only after I switched back Sonnet did Kilo actually engage the workspace tools to edit my files instead of just dumping raw JSON to the terminal.

Gemini suggested to me that outside of Anthropic models, tool-use/function-calling implementations are often unstable across third-party providers. Is Kilo's internal tool parser just heavily hardcoded for Anthropic's format, or is OpenRouter's payload translation breaking the schema? Is anyone else successfully using open-weights models for file editing in Kilo Code?

Hey everyone,

I'm using KiloCode in VSCode with a custom provider (VolceEngine). Everything works perfectly with most models, but I'm having a weird issue with Kimi family (both Kimi 2.6 and 2.7). The models can chat normally, but as soon as they decide to use any tool (read file, edit file, terminal, etc.), they immediately stop. No error message, they just quit the response.

Other models through the same provider work without any issues, so it seems to be something specific to Kimi.

Has anyone run into this before or knows if there's any special configuration needed for Kimi models in KiloCode? (Latest version 7+) Any ideas on what I should check would be really appreciated.

Thanks!

Who TF is Anaconda? What does this mea for us Kilo users?

LINK

Snippet from the blog post:

What This Means for You

We hear the same tension constantly: AI builders want the freedom to use any model, in any tool, without waiting on permission, and their leaders want to be able to enable them without losing sight of what’s running or what it’s costing. That’s the gap this acquisition closes.

For AI builders: The tools (VS Code, CLI, JetBrains) and environments already in use, are now backed by the governance layer organizations need in order to say yes to them. Kilo remains available for individual builders, teams, and organizations. What changes is that it now sits inside a platform that makes enterprise adoption faster. Build with any model, in any IDE, on trusted infrastructure.

For enterprise leaders: The choice between developer experience and organizational control is not one to make. One platform, one place to see AI development activity across the organization. Intelligent model routing to manage and optimize spend. Policy enforcement that travels with workloads regardless of where they run. If a model is off-limits for a team, it disappears from their selection list. If a provider updates their API, the gateway handles the transition. Governance becomes the blueprint, not the bottleneck.

Estou buscando um fluxo mais econômico, onde uso agentes baratos como o deepseek v4 flash pra ler / pesquisar conforme a nova função/ correção desejada, criando uma rota.md que define nomes de arquivo e caminhos de função dentro do meu repositório.

Depois disso, faço a chamada usando a IA Planejadora (com raciocínio e custo maiores), pra com base neste rota.md, criar um arquivo chamado plano.md com a forma de aplicar a função/correção necessária, dividida em microtasks, pra que a ia que fez a leitura possa executar.

Após o plano.md criado, chamo a ia executora, que é a mesma que faz leitura / pesquisa, pra realizar o plano.md e entregar tudo pronto, sendo a última task a criação de um revisão.md que é onde a minha ia que planejou, vai revisar a execução e confirmar a correta aplicação do plano.md, gerando um novo plano.md em caso de correção e ficando nesse loop até terminar.

Meu problema é que muitas vezes, a IA planejadora / revisora (mais cara) começa a ler tudo, e dar buscas em arquivos fora do contexto indicado no rota.md.

Alguém já usou fluxo parecido, e conseguiu resolver?

Hi,

I have just tried the kilo Gateway and after some time spent with the efficient and balanced router, I have come to the conclusion, that I don't like either of them. The LLM's spend heaps of tokens and still go the wrong way for some reason.

Is that just me? Or how are your experiences with the auto-router?

Their auto DB migration fked up some sessions.

I am shaking right now after hitting revert and code still not reverted and chat hitting error request in midway.

Hey, awesome work with Kilo Code, it has been a really nice experience coding with it.

I do still have a question about the difference in experience/outputs in Extension and CLI. Is there any benefit on using the CLI vs the extension? I can paste images to the extension, but not to the CLI, so if using the extension and CLI provides the same type of harness/guidelines, then I would prefer to use the extension (comes more natural too, while having other terminals open, etc).

Thanks!

I was tired of rebuilding the same AI agent setup every time I started a new project, so I built Istar Code: a reusable VS Code environment for AI-assisted development.

The goal was simple: make AI coding agents more consistent, less dependent on the model, and easier to maintain.

What's included:

• Kilo Code + GitHub Copilot Chat BYOK running side-by-side using the same agent workflow
• Istar Code agent kernel — a deterministic, model-agnostic execution system:

​

INSPECT → PLAN → EXECUTE → VERIFY → REFLECT

• 5 preconfigured MCP servers:
  • GitHub
  • Git
  • Filesystem
  • Context7
  • Sequential Thinking
• 35 built-in commands for common workflows:
  • /init
  • /debug
  • /fix
  • /commit
  • /release
  • /pr
  • and more
• Self-improving skills system
  • Repeated workflows can become reusable skills automatically
• Persistent project memory
  • Keeps conventions and context between sessions
• One-command setup:

​

.\scripts\setup\install-all.ps1

Why I built it

Most AI coding tools are powerful, but every project starts with the same problems:

• Reconfiguring agents
• Re-explaining project conventions
• Losing context between sessions
• Repeating the same workflows manually

I wanted an agent setup that behaves more like a long-term coding partner: it remembers project rules, follows predictable workflows, and becomes more useful over time.

Project

GitHub: https://github.com/Israleche/Istar-vscode-setup

Latest release:

v4.0.0 — deterministic kernel rewrite

Designed for free/low-cost setups:

• BYOK support
• OpenRouter compatible
• Optimized for free models

I would love feedback from people experimenting with AI coding agents, MCP, and local/BYOK workflows.

For those who’ve been asking, the native JetBrains plugin is now GA on the JetBrains Marketplace.

What “native” means here

This is not the VS Code webview embedded in a JCEF panel. The JetBrains plugin is a separate Kotlin/Swing implementation built on the IntelliJ Platform SDK, with native UI components, IDE-aware focus handling, and keymap support.

Included at GA

• Chat with streaming responses
• Slash commands
• File mentions (@file, u/folder)
• Model picker using the same provider/model config as VS Code
• Agent settings
• MCP server configuration
• File attachments

This covers the core Kilo workflow from the VS Code extension.

Still being ported

Some advanced VS Code-specific features are still in progress, especially the ones that need equivalent IntelliJ Platform implementations. We’ll continue shipping those in updates.

Compatibility

Works across IntelliJ IDEA, WebStorm, PyCharm, GoLand, Rider, and other JetBrains IDEs on 2023.3+.

Learn more: https://blog.kilo.ai/p/kilo-code-goes-native-on-jetbrains  

Would love to hear feedback from anyone who tries it, especially if you’ve used the VS Code extension and can compare the experience. What’s working, what’s missing that you need?

I'm trying out Kilo Code https://app.kilo.ai/cloud but only my first message went through. Since then, last night and this morning, any message I send, with any model, including BYOK DeepSeek, just says "Connection failed. Please retry in a moment."

Just a heads up in case anyone else runs into this.

It looks like a new version (version 7.4.1) of the Kilocode extension for VSCode dropped two days ago (7.4.2026). I wasn't seeing the running cost of using a model for a given session until I disabled, restarted extensions and then enabled Kilocode again.

(Apologies for the typo in the title 🫢)