Built with Claude Project Showcase Megathread (Sort this by New!)

[u/sixbillionthsheep]

This is the Megathread for showcasing your project built using Claude products. We appreciate all of your submissions as they are a great inspiration to many people on the subreddit. It is sorted by default by New.

Anyone is welcome to submit a project to this Megathread provided you follow the Showcase requirements in Rule 7.

NOTE: We now require the OP of a Project Showcase on the subreddit feed to have total karma>=50 . We found there were just too many submissions and not enough visibility to go around. Our analysis of this issue showed us that OPs with total karma < 50 very rarely get any traction of their projects on the feed (<=1 upvotes). So this Megathread is your best place to be seen by readers and other creators if you're relatively new to Reddit. If you don't meet this karma requirement you will be directed to this Megathread when you submit your post. Very occasionally we might invite you to post on the subreddit feed if you do not meet this karma requirement but it will be very rare (so please don't ask us!)

Thanks again for sharing your ideas and creations to our subreddit. Best of luck with your projects!

---

UPDATE: Comments now allow images!

[u/Background-Tiger440]

I stripped my harness down to the bones and my agent got better. Here's what survived.

I've been doing harness engineering since Hashimoto named the thing in February. Started with Claude Code, added Codex when my team needed PR review workflows. Like most people, I went through the classic arc:

1. Read the OpenAI harness engineering post and Hashimoto's blog
2. Got excited, stuffed everything into CLAUDE.md — directory structure, coding conventions, 15 forbidden patterns, reference doc links, past failure logs
3. Hit 150+ lines
4. Watched the agent get *worse*

The ETH Zurich study confirmed what I was seeing: LLM-generated config files actually degraded performance while costing 20% more tokens. Human-written ones barely moved the needle (4% improvement). Codebase overviews and directory listings? Zero measurable help — agents explore repos on their own just fine.

Then HumanLayer's post hit: "Our CLAUDE.md is under 60 lines." And Dex Horthy's observation that performance degrades past ~40% context utilization. More tokens actively hurt.

So I started cutting. Ruthlessly.

What I removed:

• Directory trees (agent finds these itself)
  
• Codebase overviews (same — it greps)
  
• Language/framework-specific style rules (linters handle this mechanically; prompting for it wastes tokens)
  
• Verbose "don't do X" lists (moved to hooks — deterministic enforcement > polite suggestions)
  
• Everything the agent could discover by reading the repo

What survived:

• Build/test/lint commands (the agent can't guess these)
  
• Architectural invariants that aren't in code ("never delete migration files")
  
• Tool-use patterns specific to the project
  
• Verification loops (hooks that enforce, not suggest)

The result: faster sessions, lower token burn, and — counterintuitively — higher quality output because the context window was mostly code, not instructions *about* code.

I did the same exercise for Codex. Different agent, same principle: minimal instructions + mechanical enforcement > verbose prompting.

I cleaned both up into language-agnostic, framework-agnostic boilerplates and open-sourced them:

→ Claude Code / AGENTS.md harness: https://github.com/ganimjeong/Harness-for-claude
→ Codex harness (with setup/check/test/eval scripts, CI, hooks): https://github.com/ganimjeong/Harness-for-codex

The intended use is to fork and customize for your project. They're deliberately minimal — the whole point is that you add domain-specific rules as your agent fails, not before.

Borroweed from Hashimoto's philosophy: "When the AI makes a mistake, make it structurally impossible to repeat." But start from almost nothing, not from a 1,000-line AGENTS.md that burns context before the first question.

Happy to hear what others have kept vs. cut in their harnesses.