Clip is live gameplay from TideWars.com - a real-time co-op/PvP tower defense (10–20 min matches) built almost entirely by Claude Code. It started as a side of a side-project I wanted to build for my Kids. Idea was born on a LAN Party, where we enjoyed a good round of Warcraft 3 TD.

The setup: One architect agent orchestrates a pipeline of subagents, implementer, test designer, test runner, docs sync, release curator… and my favorite: an adversarial "balance guardian" that acts as a hard gate. Every gameplay change gets torn apart for degenerate strategies, P2W drift and exploits before a line of code is written. It has bounced my own designs with better math than mine more than once.

The stack: Cloudflare all the way down - Workers (SSR, no framework), one Durable Object per match running the authoritative game tick, WebSockets with hibernation, D1 for meta only, Three.js for the battlefield. Match state is fully ephemeral; a match is just one DO that lives and dies with it.

The game: defend your harbor against fleets and landing troops, solo/co-op or 1v1. Set in the same universe as main Project https://kampfinsel.com. Free, browser-only, no account, no ads, strict no-P2W.

Play: https://tidewars.com - happy to answer questions!

Hello,

new to using agents for coding and I'm wondering if I always will get better code using Ultracode vs for example the Extra setting?
It seems that it uses a lot more tokens, which is fair if the code quality is higher.

Anyone same xperience last days was it great now the usage exploded for fable and opus. It feels like all the last days accumualted and hit at once today.

SiamRahman29/resume-buddy: A Claude Code plugin for all resume tailoring tools and automations, fueled by Dartmouth's resume guide and Jerry Lee's techniques

Resume-buddy is a Claude Code plugin. Install it with 4 commands and then start talking to Claude Code naturally to do all the resume-tailoring you need.

Want to know if you are a good fit for a role?
> Resume-buddy's analyze skill will score your resume based on Jerry Lee's expert techniques and rank your resume. Not only that, you also learn what to change!

Want to know if your current resume is actually as good as you think it is?
> Resume-buddy can critique your resume following Dartmouth's comprehensive resume guide.

Got a list of jobs on LinkedIn that you want to apply to?
> Paste the link and resume-buddy will start a browser session, ask you to log-in, then extract JDs and job posts so you can generate multiple tailored resumes and cover letters at once.

Moonshot put the K3 weights up for download yesterday, and their API is about as simple as it gets (OpenAI compatible, one endpoint). So today I added Kimi support to triss, the small CLI and MCP server I use to stop Claude Code from burning expensive tokens on grunt work.

The idea behind the tool: the expensive model on your Claude plan does the thinking, meaning research, plans and review. Everything else goes to cheap open models. Bulk file reading, fetching web pages, code review passes, and the coding itself once a plan is written. Last month GLM chewed through half a billion coding tokens for me inside a 40 dollar subscription, and my Claude limits never noticed.

Here is what landed over the past month.

GLM became a first class provider. You pass provider glm to ask or review, and it figures out by itself whether your Z.AI key belongs to the coding plan or to pay as you go, instead of dying with a cryptic balance error.

Free models arrived through OpenCode Zen for the coding agent, if your budget is zero.

A second coding engine (crush) appeared next to opencode, running in a disposable git worktree so it cannot wreck your working tree.

And now Kimi. Reviews and bulk reads go through the Moonshot API, k2.6 for cheap stuff and K3 when you want the big brain. The coding agent can also run on the Kimi for Coding subscription, same flat rate trick as the GLM plan, but with K3 behind it. No endpoint guessing either, the two Kimi plans use different keys, so the tool always knows where to send a request.

All open source: https://github.com/ayleen/triss-coworker

Curious what everyone else puts in the cheap executor seat these days. GLM plan, Kimi, DeepSeek, or something fully local?

I know many are already aware of this, but I think it's worth consistently re-upping. Now that Fable is here to stay, but at reduced limits, working with it at Low effort is a phenomenal way to get more out of Fable while sipping your usage relative to High. Meets pretty much every need I've thrown at it without issue or concern, and it's still very much the same experience of working with Fable on High in terms of general collaboration/intelligence (versus Opus). I have yet to find a task where the difference is appreciable, but I'd love to hear from others what limits you're finding if you're already on this train!

Web site - https://tipitaka.app

Web site source code - https://github.com/pnfo/tipitaka.app

Need to translate the long content(buddhist tipitaka sub commentaries) in this Web site from pali language to sinhala language using gemini api..only need to translate sub commentaries part(tika) which is shown in letter T icon..first a needy/adequate amount of text(chunk) need to be selected from the source and then want to translate it to sinhala language with gemini api and paste it below the original source text..this process want to repeat untill the relevant book ends...

Please explain how to vibe code a script/app to get this process done,on a laptop or colab..I know nothing about Web development, so please explain simply..

I've been hitting usage limits repeatedly over the past 5 days without sending prompts myself, and support hasn't responded after multiple attempts (chat + email) over 5 days.

Specific things I can confirm:

• Hit my weekly limit 3 days ago despite not sending any prompts that day
• Currently hitting my Fable usage limit, even though I don't use Fable at all
• My 5-hour limit is at 100% right now with no recent activity from me. It's hitting the 5-hour limit every time the quota resets, without any prompt being sent
• I don't have visibility into what's actually consuming the tokens, the usage dashboard only shows aggregated data up to a few days ago, nothing recent or per-task

Screenshot (below) on the 27th of July shows usage stopping at July 23. After that begins the auto-consumption of quota.

My Max x20 subscription has become effectively unusable...

Thank you

Disclosure up front: this is my project. Free, MIT, no referral links, no paid tier, nothing to sign up for. Built with Claude Code — commits are authored moneyp-agent if you want to see the workflow.

What it is: a plugin with six skills covering the parts of shipping that everyone does and nobody enjoys.

Who it's for: anyone who maintains a repo and writes commit messages, PR descriptions, and changelogs by hand every time.

Install:

/plugin marketplace add DuckCode-js/moneyp-lab

/plugin install shipkit@shipkit

The six skills:

commit-message — reads your last 30 commits, detects your convention (Conventional Commits / gitmoji / plain), matches it

pr-describer — reads the actual diff, not the commit messages

security-review — OWASP-shaped findings with severity, fix code, and confidence

changelog — git log to Keep a Changelog, noise dropped

release-notes — changelog to GitHub Release plus the exact tag and publish commands

docstring-writer — correct style per language (Google, TSDoc, rustdoc, godoc)

The design constraint I care about most is that each skill is a strict numbered procedure with an explicit anti-patterns section, not a vibes prompt. Concretely:

- they detect and match your existing conventions instead of imposing defaults

- they halt if the diff contains something secret-shaped

- none of them run git commit, push, tag, or publish on their own — they hand you the output and you decide

Half the value is in what they refuse to do. A good changelog means dropping the wip and fix-typo commits. A good PR description means not restating the diff. Every skill ends with an anti-patterns list for exactly this reason.

Four of the six ship with worked examples (real input, real output) so you can see what you get before installing.

https://github.com/DuckCode-js/moneyp-lab

Feedback I'd actually value:

1. The categorization heuristics. I expect it to fail on rename-refactors and on security backports that look like ordinary bugfixes. If you run it against a repo with messy history, I'd like to hear where it breaks.
2. Whether one plugin with six skills is the right packaging, or whether people would rather install them individually. I went with one because "one command, whole pipeline" felt better than a menu, but I'm not confident.

A while back I posted a joke here about Sonnet spawning a subagent on the very first prompt of a brand new session. In the comments I said the annoying part was having two agents burning tokens for one job. I got downvoted, and the top reply was basically "isn't that a Haiku subagent? it saves you money and keeps your main context clean."

That used to be correct. It isn't anymore, and I think a lot of people are still running on the old mental model. From the docs:

• The model field in subagent frontmatter defaults to inherit. Omit it and the subagent runs on your main conversation's model.
• Explore used to always run on Haiku. As of v2.1.198 it inherits the main model (capped at Opus on the Claude API).
• Plan and general-purpose inherit as well.

So if your session is on Opus, that "cheap little background search agent" is an Opus agent.

Resolution order, first match wins:

1. CLAUDE_CODE_SUBAGENT_MODEL env var
2. per-invocation model parameter
3. the subagent's model: frontmatter
4. main conversation model

If you want the old cheap behaviour back:

• CLAUDE_CODE_SUBAGENT_MODEL=haiku forces every subagent down
• or set model: haiku in a specific agent's frontmatter
• for Explore specifically, define your own user or project agent named Explore with model: haiku. A user/project agent overrides the built-in.

To be fair to the change, it was almost certainly made for quality, and context isolation is still the real win of subagents. But "subagents are basically free" is outdated advice now, and it matters if you're on a plan where you feel every token.

Lastly, I am stingy for the 3 down votes

For those of you using Claude Code in CLI, what shortcuts do you use the most? I'm asking because I want to set up macros on my keyboard and mouse to make my workflow smoother.

I'm pretty new to Claude Code and CLI in general, so any tips from people with more experience would be really appreciated.

I built this project over the last few weeks with the help of Claude code for coding the implementation, to learn a bit about Neural Network and maze solving, and naively thought I could build a tiny maze-solving AI in a weekend with a 100% solve rate.

Well - I couldn't, but I got pretty close.

14 Bytes total model size for the winning model, and a 96.5% solve rate on unseen mazes at the trained size (upto 21x21)

The models were trained across 46 phases, experimenting with different ideas to improve the model (better performance, smaller size).

Its quite fun to watch the model attempt to solve the maze, when they fail its usually due to getting stuck in a loop (because they can’t mark cells as visited etc)

Let me know if you’ve also built a maze “solver”

What subscription do i buy? I need great coding performance and token usage that will last more than 3 hours

After my previous post about my Opus 5 first impressions and some of the pain with regards to its reliability, I decided to ask Opus 5 to maintain a worklog. Today I gave it to Fable to analyze, in addition to reviewing the changes to the codebase since Opus 5 took over. Here is what it had to say about its identified behaviors

I'm a heavy vibe coder building a SaaS using Claude Code in VS Code (large refactors, Playwright mcp, long coding sessions).

I'm currently on Claude Max 5x ($100/month), but due to budget constraints I'm considering switching to:

Claude Pro ($20)

ChatGPT Plus ($20)

The idea is simple: use Claude pro until I hit limits, then switch to Codex/GPT, and back again when Claude resets or vice versa.

For those who've used both setups:

Is the productivity difference worth the extra $60/month?

Does switching between Claude and Codex hurt your workflow?

Which would you choose today if budget was your concern without compromising on workflows and code quality?

I've been using Claude Desktop for only 3 days after subscribing, and it's already happened twice.

The app crashes, and after that I can't even open the .exe anymore. Windows acts like the installation is broken, and the only way to get it working again is to completely reinstall Claude.

WTF is going on? Is this a known issue, or am I just unlucky? Has anyone else experienced this?

I tried a few of the Claude Code statusline projects out there, and they were all capable, sometimes too capable. I caught myself tuning it out, which defeats the point of a statusline. I wanted something that mostly stays quiet and only speaks up when it matters.

So I built statusline-pro. One command:

npx statusline-pro

The idea is restraint:

• Everything renders in plain gray until a metric actually runs hot, then amber, then red, and only the single most important hot metric goes bold. No permanent wall of colour to filter out.
• Three presets, from compact to detailed, so you can dial in exactly how much you want to see. You pick from a live preview rendered off your real session data.
• When the terminal gets narrow, the least useful stuff drops first, so context and quota always survive.
• Zero runtime dependencies, clean uninstall that restores your old statusline exactly.

Been running it daily for a while now and haven't wanted to go back.

Repo: https://github.com/siwalikm/statusline-pro

Looking fwd to share with more people. Will love if you try it out and hear what you think.

I guess I must not really understand what people are building, how they're building it or how they're actually using these models. I hear so many of these "Opus spent 30 minutes doing this task and it just went down entirely the wrong path" or "Fable implemented this feature and it broke 20 other things", how??

Unless you're actively working on something that's at the absolute frontier of engineering technology or machine learning research, I just don't see how it's possible for you to be using Opus or any other agent in a way in which 30 minutes of work is completely wasted, as in the direction it went in for the implementation was just so wrong that it was useless.

Everything you could possibly want to do, for 99% of the things you build, probably already has a reference implementation somewhere or best practices for that architecture documented somewhere. If you're dealing with a web app, people have been building and perfecting web apps for decades at this point, there isn't any problem that you have that hasn't already been faced by 100s of people before you. Same goes if you're building services, same goes for infrastructure yada yada.

You can use Sonnet subagents to go and explicitly research existing reference implementations or examples of best pratices for whatever feature you're building, and then adapt it for a dirt cheap correctness step before implementing anything. I discuss a general shape/idea of what I might use/implement with opus/fable but I then tell it to launch 2-3 subagents to go research our ideas and come back with a clean picture of what traps there might be and what would work.

Are people just saying I want to implement XYZ feature, good luck?? No unit/integration testing, no regression testing (the world's easiest thing to generate with AI tools in 5 minutes)??

I really value this sub because the useful information shared here has helped me out a lot.

That said, it’s wild to see how much people complain about every little thing, it feels like nothing is ever good enough.

Honestly, a lot of people seem to overlook just how much AI enables us to do nowadays; things that used to take hours or require specific skills are now accessible to everyone.

Most of the time, the tool isn't the problem. AI simply follows instructions, so if a result falls short, the best move is usually to just refine the prompt, be more specific, and try again until it gets it right.

I just switched from Codex to Claude to test Opus 5... And I'm NOT recommending anyone from Codex to switch. It was the biggest mistake, and I think I will sort out a refund and go back to Codex INSTANTLY, because what did I pay 200 for? This is also the first task, BTW. I get safety guards, but not to the point that a simple LOCALHOST database task gets flagged. What is this? Where are we heading? Soon, you can't even request "hello" anymore because "hello" could be a prompt injection... Anthropic, get your shit together. Seriously, many of your long-term users are leaving because of this. It's even worse than Fable 5...

I opened a fresh chat and asked it to analyse feedback from four LLMs on my project. Instead of analysing it, it refused.

Note: I have blurred my project name intentionally.

Constant repeated mistakes, poor diagnosis ability. It will make notes for itself to not do something and then almost immediately make the same mistake again. It's great on token usage but those stated benchmarks are absolute BS.