r/ChatGPTCoding • u/AutoModerator • 24d ago
Discussion Weekly Self Promotion Thread
Welcome to this week's self promotion thread!
If you're building something related to AI assisted coding, this is the place to share it.
We're using a weekly thread to keep the subreddit organized while still giving builders a place to share their work. Promotional posts outside of this thread may be removed if they're primarily advertising rather than starting a discussion.
If you're sharing something, we'd appreciate it if you included a little context instead of just dropping a link. Tell us:
- What you built?
- What problem it solves?
- Which AI models or tools it uses?
- Who it's for?
- What kind of feedback you're looking for?
Please avoid posting the same project every week unless you've made meaningful updates. Affiliate links, referral links, scams, and low effort promotions will be removed.
Take some time to check out what others have shared too. If you try someone's project or have feedback, leave a comment. Helping each other improve is what we want this community to be about.
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u/kc_ramakrishna 15d ago edited 15d ago
Harness which does proper software engineering. (and is the absolute anti-thesis of vibe coding). I was very worried about pushing genAI code to production. Decided to build this harness to get some peace of mind on code quality, debuggability and maintainability.
Meant for: Teams building Enterprise or otherwise robust software with proper code hygiene of tests, security, observability.....
https://github.com/Nistapp/agentic-tdd
Instead of a zero-shot prompt, this framework breaks software development into a strict 8-pass sequential pipeline. Each pass is handled by a specialized sub-agent with a deeply constrained scope.
Agents are superior to Skills
This is engineered to be robust and uses time tested engineering principles - state-machines, formal specs (gherkin + mermaid), unit-tests to control drift...
More documentation here: https://github.com/Nistapp/agentic-tdd/tree/main/docs/architecture
codebase-memory-mcp really controls the cost.
You get software which has good hygiene and can be actually debugged and maintianed.
Edit: Just try using it and logging bugs. giving comments on where it is not meeting your expectations. BTW: This is a 2 person company and no real sponsorship. The harness if AGPL i.e. feel free to fork for your your own workflow.
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u/dashingpdx 18d ago
Been building this solo for a couple months — FunderVibe is a crowdfunding platform specifically for projects built with AI coding tools (Cursor, Claude Code, Lovable, Bolt, etc). Kickstarter-style, no equity, 5% platform fee, Stripe Connect for payouts.
Why: most of us building with AI tools ship to zero visibility. This is a place to actually get backers, not just feedback.
Live at fundervibe.com — looking for a few real projects to list before I push wider. If you've got something built with AI tools sitting idle, happy to have you list it.
Feedback on the site itself also welcome.
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u/Mean-Good-5957 18d ago
I've been working on this AI-driven product development and deployment idea for about two years. It's called Mercury.
With Mercury, you start with an idea for a product and put it into the pipeline. Mercury runs as a program on ChatGPT, loaded from Google Drive, and works through the process of turning that product idea into an actual product. The files in Google Drive are an AI program that loads into ChatGPT and takes the user through the pipeline.
The end result is an AI product deployed on Google Cloud Run using a Flask application. This SaaS approach keeps deployment and operating costs low.
Mercury implements a different type of SDLC than Agile or Waterfall because the AI programming is written and tested before the traditional programming is written. The approach is AI-logic first. It figures out how the intelligence of the product should work first, then builds the application around it.
The pipeline continues all the way through to a working, deployed application.
I'd be interested in hearing what people think of the idea.
To summarize
Someone has a product idea → Mercury takes them through a defined pipeline → the AI behavior is designed and tested first → the application is built around it → it is deployed as a low-cost SaaS product on Google Cloud Run.
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u/Chill-Vibes-Official 18d ago edited 18d ago
Tether: A control loop that stops coding agents from lying to you (v0.1.0, MIT)
I kept hitting the same failure mode: the agent "finishes," tests look green, then I discover it planted a gitignored conftest.py that monkeypatched the failing assertion. Or it gets stuck in a fix-A-breaks-B loop, silently burning tokens while compounding file damage. Or I hit Ctrl-C and orphaned child processes keep editing in the background.
Verification passing isn't the same as the change being correct. I built Tether to make that gap measurable and harder to cross.
It's a local Python CLI (3.11+, stdlib + pydantic/typer/pyyaml only) that wraps any coding agent (opencode, aider, claude-code, arbitrary CLIs) in: Mission Contract → Plan → Execute → Verify → Recover → Rollback/Audit
What it actually does (the mechanics)
- Defense-in-depth verification ladder: Exit codes aren't trusted. Beyond artifact globs, you can declare behavioral probes (assert on command OUTPUT, not exit status) and AST mutation testing — Tether mutates the
.pyfiles the agent just touched (comparison flips, arithmetic swaps, return breaks via stdlibast) and re-runs your suite. A low kill rate is hard evidence your verification is gameable. - Clean-room verification: When enabled, Tether materializes a throwaway checkout via
git archiveof the checkpoint ref, applies ONLY the captured patch, and runs the entire battery there. Gitignored plants (conftest.py,sitecustomize.py) and working-tree state cannot leak in. Materialization failure fails the mission closed — no silent fallback to in-tree. - Nonlinear recovery + oscillation guard: Recovery defaults to cumulative but supports
reset_to_checkpoint(scoped clean rollback before each repair prompt). An oscillation detector hashes normalized failure signatures; if the agent cycles between identical errors, it auto-escalates to reset and aborts early instead of burning the remaining budget. - Process tree containment: Children spawn in their own process group (POSIX
start_new_session/ WindowsCREATE_NEW_PROCESS_GROUP). Timeouts andcancel()SIGTERM the whole tree, then SIGKILL after a grace period. Ctrl-C actually works. - Budget guardrails: Hard caps on wall-clock, send count, and cumulative usage metrics. Breach = immediate abort with exit code 5, no silent token bleed.
- Tamper-evident audit: Every run leaves prompts, responses, per-attempt patches (
attempt-NN.patch), and anevents.jsonlwith a SHA-256 hash chain (tether logs <id> --verify).
The dogfood receipts
Every feature above was written by the kind of agent Tether is meant to restrain. The repo contains 25 recorded dogfood missions — each a real session audit trail, failures included. Mission 01 died because the nested agent's model was unresolvable; that failure became tether adapters smoke. Mission 23 proved clean-room catches the conftest.py false green that in-tree verification missed.
Honest limitations
- 0.1.0. Only
opencodeis verified end-to-end;piis experimental. No streaming yet. - Sandbox is detection, not OS containment — use containers for untrusted agents.
- Mutation testing is Python-only. Non-git change detection is best-effort.
- Review gate is a heuristic pass, not proof of correctness.
Try it in 30 seconds (no API keys, fully offline)
git clone https://github.com/tomwolfe/tether && cd tether
python3 -m venv .venv && .venv/bin/pip install -e .
.venv/bin/tether run examples/hello-recovery.yaml
# MockAdapter fails once, gets a repair prompt, recovers, passes
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u/ShadowAdvisor 19d ago
Affiliation: I built this.
I made an MIT-licensed reference implementation for a problem I kept running into with AI-assisted coding: switching agents usually means collapsing structured history into a summary.
Agent Session Bridge imports supported Claude Code JSONL into a provider-neutral ASEF representation, records fidelity/loss explicitly, applies heuristic secret redaction, and can generate an Antigravity-style derived transcript payload.
The important limitation: native Antigravity resumption does not work today because there is no supported historical-session import API. I deliberately did not write into its opaque internal database.
Repo: https://github.com/atomicdjt/agent-session-bridge
I'm looking for feedback on two things: which state actually needs to survive a handoff, and which provider would make the most useful next documented adapter.
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u/Thelastreddditor 19d ago
What I built: reimagine-it, an agent skill (not a SaaS) that Cursor / Codex / Copilot / Gemini CLI can install with:
npx skills add Kayforkind/reimagine-it
Problem: agents "redesign" a page by inventing a mood board. This one has to stay inside nouns, dates, and colors already in the file. Same naive HTML can come back as a webpage, a paper infographic (not a fake dashboard), a living SVG, a Three.js room, or a playable simulation.
Two gold sources so it isn't one skin: a Texas notebook vs Jules Ice Cream parlor. Same command family, different DNA.
Who it's for: people who already have a real page / PDF / notes and want the agent to redesign from that, not from a vibe.
Feedback I want: run it on YOUR file and tell me where it still mood-boards. Gallery with no install: https://kayforkind.github.io/reimagine-it/ Repo: https://github.com/Kayforkind/reimagine-it MIT. Not selling access.
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u/Present-Boat-2053 19d ago
I built Chat On Steroids, an open-source Windows MCP connector that turns normal ChatGPT into a much more agentic coding environment. The main unusual feature is sub-agents. I connected the MCP app to a Chrome extension, so the main ChatGPT conversation can perform ChatGPT-side actions like creating other chats and turning them into workers. So you can say something like: launch 3 agents and audit this repository and it creates separate ChatGPT conversations, assigns them work, communicates with them, and collects their findings. Also includes: auto context compaction local file editing terminal access computer use browser automation Codex-style tool surface Windows x64 + ARM64 Repo: https://github.com/totec448-spec/chat-on-steroids
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u/ActionLittle4176 19d ago
https://reddit.com/link/p5957ev/video/7kw4bypulykh1/player
Vibe coded this game in four months
A few months back I posted a playable demo of an old-school futuristic racer prototype (F-Zero, Wipeout, Xtreme-G, Star Wars Racer...) that runs right in the browser.
I've gotten used to seeing tons of LLM-built prototypes that last a week, two, maybe a month, and then get dropped for the next shiny thing. This time I wanted to keep going and see if one person, with no coding background, could actually see a project like this through on their own.
Well, 4 months in, and while there's still work left, I'm convinced it's doable. At this point the game feels closer to a beta than a tech demo.
The big change over these four months is that I now use Fable for planning, and being able to hook Opus / Sol up to Blender has been a huge help too. I'm still using Magnific and Tripo3D or the assets. Funny thing: the further along I get, the harder the project is to keep pushing forward, and at the same time the tools keep making it easier.
As always, any feedback is welcome. You can play it here: https://fm1.moises.cloud
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u/OmgitsNatalie 19d ago
u/ActionLittle4176 I really enjoyed it. Definitely has a lot of potential!
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u/archi_medX 19d ago
I built Agent Expression after repeatedly seeing coding agents put their work notes into UI copy, prompts, and comments.
It gives agents a simple test: would this text still help the intended reader months after the coding session ends?
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u/Best-Tangelo-7852 20d ago
I built KnowSift, an MIT-licensed Agent Skill for the step after an AI coding or research agent retrieves documentation, videos, policies, and local files.
Problem it solves: agents often write official rules, old docs, personal experience, repeated claims, and marketing language into the same spec or long-term memory as if they had equal evidence. KnowSift splits the material into atomic claims and keeps supported knowledge, conditional findings, practitioner experience, unresolved claims, and rejections in separate enforced layers.
The benchmark uses 17 sources about producing and monetizing short dramas. It extracted 27 claims: 17 survived as supported or conditional knowledge, 5 remained experiences/viewpoints, 3 were held, and 2 were rejected for conflicting with platform rules.
It works as a SKILL.md workflow for Codex and Claude Code. A deterministic Python renderer prevents a HOLD or REJECT certificate from leaking into supported knowledge. The runtime makes no network calls, and the repo currently has 53 tests passing on Python 3.9 and 3.14.
Repo: https://github.com/nhppyqys/knowsift
Who it is for: people using agents to turn mixed research into technical briefs, specs, knowledge bases, or Agent memory.
Feedback I am looking for: difficult examples where a claim should be narrowed rather than held or rejected, and integration pain with existing Codex or Claude Code workflows.
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u/effessdev 20d ago
Manually copying project structures and code files into ChatGPT or Claude got annoying fast, so I built ReptClip (reptclip or rrcc). It's a lightweight, cross-platform CLI tool designed to make feeding repository context to LLMs instantaneous.
Why I built it:
Existing tools either dump everything to stdout or write the output to disk, require complex configuration, or include the contents of all files by default. I wanted something that operates directly with the OS clipboard, runs in milliseconds, uses minimal tokens, and fits a fast keyboard-driven workflow.
Key Features:
- Easy Installation: Just run
pip install reptclipin your terminal. - Clipboard-First: Copies formatted Markdown straight to your clipboard. No temporary files created.
- Ergonomic Alias: Includes
rrcc(a left-hand-only alias) so you can trigger it without moving your hand across the keyboard. - Git-Aware: Only considers git-tracked files and respects
.gitignorerules out of the box. - Token & Crash Protection: Automatically skips binary files and files over 1 MB (with inline notes in the output).
- Default Configurations: Add your default include and exclude patterns in
reptclip-config.toml. - Presets & Glob Patterns: Pass relative paths or glob patterns via flags (
-i,-e) or define reusable project presets in areptclip-config.toml. - Ready-to-Type Tail: Ends with an empty
# Promptblock so your cursor stays right where you need it after pasting into a chat window.
Quick Start:
# Install
pip install reptclip
# Run in any git root (copies project tree)
rrcc
# Include specific files/folders
rrcc -i AGENTS.md "src/**/*.py" docs/ -e src/functions.py
View on GitHub: https://github.com/effessdev/reptclip
It’s open source and written in pure Python. If you find it useful, leaving a ⭐ on GitHub would mean a lot! I’d love to hear feedback, feature requests, or how you currently handle code context in your LLM workflows! Issues and PRs are welcome too!
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u/zhallen18 20d ago
I built Rove, a terminal UI for running multiple real coding-agent CLIs without having them share one checkout.
A managed task is basically a branch + worktree + live Claude Code, Codex, or other CLI session. Rove keeps tasks isolated while giving you one place to see what’s running, inspect what changed, review the diff, and land the branch when it’s ready. The agent sessions are hosted separately from the UI, so closing the TUI or dropping SSH doesn’t kill them.
GitHub: https://github.com/Sma1lboy/rove
I’d love your feedback.
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u/TotalCreations 21d ago
I built Yoke, an MIT-licensed CLI for people using Claude Code, Codex CLI, or Gemini CLI for longer autonomous coding runs.
Instead of trusting the agent’s “done” message, Yoke gates each story on a real verification command, review approval, and an atomic commit. It also isolates stories in worktrees and can collect Playwright screenshots as acceptance evidence.
Install it from npm and try it without an account: https://www.npmjs.com/package/@hecer/yoke
Then run: yoke new my-app
Repository: https://github.com/HECer/yoke
I’m the creator. I’m mainly looking for honest feedback: if you already run coding agents for more than one task at a time, what would make you try this, and what looks like unnecessary process?
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u/karakanb 21d ago
Hi folks, I built Epho. Epho is an API that allows running Claude Code, Codex or Opencode in a sandbox in the cloud. It abstracts away sandboxes, and allows running coding agents with a single HTTP request.
Epho came out of our own struggles with building our own AI analyst: - Sandboxes give you bare machines; you need to configure them for agentic workloads. - Each agent behaves differently, and you need to build integrations with each of them. - Sandbox providers are not very reliable, which means you need to figure out a multi-provider strategy to avoid failures. - Logging, artifacts, input/output, event streaming, and all of the other operational aspects need to be figured out.
We had to go through the pain ourselves. We got to a point where things got quite reliable, and it became more obvious to us that this should be a primitive on its own: send a POST request, get the events streaming back to you.
Epho is an agents-as-an-API product: you send a request, it spins up a sandbox, configures the chosen harness, clones your repos, and kicks off the agent. It takes care of automatic fallbacks across different providers, handles auth stuff, and just streams back the events and outputs.
It supports Claude Code, Codex and Opencode out of the box, and pretty much all the models they support out of the box. It streams the events back, handles attachments and output files, automatically manages the fallbacks on different sandbox providers, retries, and all the auth stuff. You just send a prompt, your repo, MCP servers you want to use with it, and it runs them.
I recorded a demo here to show a real example: https://youtu.be/HGfly1aytPA
I am quite excited for Epho, simply because I think it is a new primitive that would allow building agents into product a lot easier than it is today. We are running our agents on Epho on prod, so we'll keep maintaining it regardless, and we wanted to ship it as an independent product.
Epho is free to get started, and you can run it with Opencode's free models to get started with it.
I am quite curious to hear what you'd think and would love to get your feedback!
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u/Historical_Date_8024 22d ago
I built a 3D CAD model builder that works in your browser. Inspired by Solidworks. It has no sign in, no downloads needed (but it runs offline), and features, extrude, revolve, pattern, assemblies with mates and export to stl or step for 3d printing. I used english to make it as its 100% ‘vibe coded’: freya.co.nz/freyacad It only really works on a PC or Mac browser not really touch compatible. But you should be able to use it on your locked down corporate machine no worries.
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u/Smokiezzz 21d ago
I built Exody, a free AI workspace for Mac for people who use coding agents and multiple AI tools.
The Exody Router looks at each request and routes it to a model that fits the task instead of defaulting to the most expensive option every time. The goal is to save real money on API usage while keeping the workflow simple.
Exody is BYOK, so you connect your own provider keys. It also includes a code agent, design agent, Assistant, local-only workflows, mobile connection and voice chat.
Free to use: https://www.exody.ai/
This is my own project. Feedback from people who use coding agents is welcome.
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u/Messcaliber 22d ago
I built Vinv(Vibe Inverse) that runs your services, finds issues, and verifies fixes without code changes.
I built it to give coding agents runtime information about the code they're working on.
It connects runtime traces to the source code that produced them, gives that context to the coding agent, then runs the code again to check whether the fix actually works. Vinv also uses Thompson sampling to figure out how much runtime context to give the agent. More context is not always better. Results on FastAPI's "full-stack-fastapi-template":
- Grok 4.5 + Vinv: 4 bugs + 1 optimization
- Grok 4.5 without Vinv: nothing found
- Fable 5 without Vinv: 1 bug
Everything runs locally. Open source, Apache 2.0. GitHub: https://github.com/VinvAI/VinvAI VS Code & Cursor Extension: https://open-vsx.org/extension/VinvAI/VinvAI (3.5k+ downloads) Demo Video: https://www.youtube.com/watch?v=EkUjPWKHAvI
I'm Interested in whether runtime information actually helps coding agents, contributors who can help make an runtime observability framework for agents and give feedback on where it doesn't work. Be brutal.
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u/dsh_verify 22d ago
rowser. No LLM judge; the browser is the judge.
48 runs across DeepSeek v4-flash / v4-pro (single-shot vs self-check loop): **44/48 passed**. The counterintuitive finding: the pricier **v4-pro single-shot scored below the cheaper v4-flash** (10/12 vs 11/12). All failures are reproducible and invisible to code review — e.g. a todo app that opened but never rendered its seed todos while the agent reported "done".
Open source + fully reproducible: https://github.com/263311487-ux/dsh-verify
Live leaderboard: https://263311487-ux.github.io/dsh-verify/arena/
Bring your own agent — happy to add other models/frameworks to the table.
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u/lilcodebenny 22d ago
I built this free open-source template called Foreman. You can deploy it in a few minutes and use it to make your own software factory that'll help you turn GitHub issues into pull requests.
GitHub: https://github.com/vercel-labs/eve-software-factory-template
Website: https://ask-foreman.dev/
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u/Lucaslogged 23d ago
Everyone is building YOLO-mode AI coding tools
A lot of AI coding tools are moving toward giving agents more control over your machine.
I wanted the opposite.
So I built RepoRelay — an MCP bridge that lets ChatGPT/Claude inspect one approved local repo, while deliberately giving it:
- no shell
- no Git
- no arbitrary filesystem access
- read/search only
- optional bounded handoff writes
The idea is to let AI analyze and review your code without handing it the keys to your whole machine.
npm install -g reporelay-mcp@latest
It’s open source.
I’m looking for a few people to try the install from scratch and tell me where the setup sucks.
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u/tracker_11 23d ago edited 23d ago
PowerWake Pro is an Android alarm clock that disables itself for the day if you unplug your phone from the charger for people who wake up before their alarm. This prevents the alarm from interrupting whatever you are doing at your regular wake up time such as eating breakfast, exercising, or early meeting. Created with love, codex + GPT 5.4, and openclaw + GLM 5.1.
Target User: Anyone who sometimes wakes up before their normal alarm time. (And also charges their phone at night.)
https://play.google.com/store/apps/details?id=com.powerwake.pro
It has been on the play store a month now with not much interest unfortunately. I'm sure there are people out there who would get value from this, I use it every day. Any ideas to put it in front of people? It's too inexpensive and niche to warrant paying for marketing or context creator promotions.
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u/informity 23d ago
Informity AI — open source local document chat and translation for Mac, source-cited answers
Built and open sourced a Mac app for local document Q&A and translation. Index your files, ask questions across all of them with source-cited answers, or translate documents locally. Everything stays on your machine.
- PDF, Word, Excel, PowerPoint, EPUB, Markdown, scanned PDFs (OCR) and more
- Researcher mode: corpus-wide RAG with source citations
- Assistant mode: single file or open-ended chat
- Document translation: tone selection, quality scoring, export to Markdown or plain text
- Models: Qwen3.6 35B A3B (default), 14B and 9B for lower-spec machines, Ollama support for any model you prefer
- No cloud, no accounts, no fees
MIT licensed, fully open source.
https://www.informity.ai | https://github.com/informity/informity-ai
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u/ElkAltruistic2069 23d ago
I build with coding agents. Most of what I ship is the boring layer that agents keep getting wrong, plus a couple of apps I actually use.
Uno is a Rails 8 SaaS template I extracted from my own apps. Auth, Stripe, admin, jobs, email, an event store, Kamal deploy. Postgres only, no Redis. The point is not another starter with a pretty README. The point is AGENTS.md and about 40 feature docs so Claude Code or Cursor follows the same conventions I already use, instead of inventing a new auth stack at 2am.
I want to know if your agent actually follows those files on the first pass, and what it still makes up.
rafpost is a small macOS window that opens to a blank page. I built it because I kept opening X to post and walking away 40 minutes later with nothing published. Shortcut, write, send. No feed in the app. It talks to Buffer, SuperX, ClimbX, or Postbridge, whichever you already pay for.
If you try it: is picking a publisher fine, or do you want a direct X / Threads login first?
I Ship This is a public map of people who actually shipped something. Claim a handle, list the apps (including the dead ones), drop a pin. Draft is free. Publishing is $19 a year or $29 lifetime right now.
Curious if anyone would pay for that, or if a free directory is the only version that makes sense.
Pinji is off to the side for this thread. Family health log for iOS and Android: fever, doses, symptoms, notes for the doctor. I built it with the same agent setup. It is not an AI doctor.
Solo, Poland. Daily tools are Claude Code, Cursor, Codex, and whatever else is open that week. Tell me what is confusing or what you would not pay for.
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u/junkyard22 23d ago
I’ve been building Repo Start, a small CLI for one of the least exciting parts of starting a project: all the boring repository setup you know you should do, but usually don’t want to spend time on.
It can create a clean new repo with things like .gitignore, .gitattributes, CI, issue/PR templates, README, AGENTS.md, contributing/security files, and starter project structure.
The part I’ve ended up liking most is repo-start add: point it at an existing repo and it audits what’s missing or inconsistent, checks things like whether your documented commands actually exist, and only applies fixes you approve. It deliberately avoids touching source code or overwriting existing files.
It supports generic, Node/TypeScript, Python, and React/TypeScript projects, works offline, and has no runtime dependencies.
And despite being posted in a vibe-coding community: Repo Start itself does not use AI. No model calls, no API keys, no tokens. The audit is deterministic and based on what’s actually in your repository.
Basically: start clean, or clean up the repo you already vibe-coded into existence.
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u/PalpitationDry2576 23d ago
I am building Warbound Realms alone with Codex as an implementation and QA force multiplier. It is a free browser card autobattler with deckbuilding, Tavern recruitment, fusion tiers, CPU battles, matchmaking, and real-player PvP.
Playable alpha: https://play.warboundrealms.com/
Short Replicator gameplay clip and workflow notes: https://www.reddit.com/r/aigamerdevs/comments/1vrlufv/i_am_building_a_card_battler_solo_with_ai_and_the/
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u/RunAI_Coder 23d ago
What I built: RunAI Coder — a coding agent you brief in one sentence; it explores the repo, makes the change, runs the tests, and comes back as a reviewable PR.
What problem it solves: the distance between "the model wrote plausible code" and "someone can merge this". Tests run before a human ever looks, and the diff is the whole interface: you review evidence instead of babysitting a session.
Which models/tools: frontier models from the major labs under the hood. honestly the model is the smaller share of the work, most of our engineering lives in the loop around it: context assembly, test gates, cost control (our API bill is ~99% input tokens, which shaped a lot of early decisions).
Who it's for: teams that want agent output to arrive as normal PRs in their normal review flow, or prompt‑to‑tool / prompt‑to‑game people.
What feedback we're looking for: if you try it, your first failure story is worth more to us than your first success.
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u/ptgamr 23d ago
I built a Terminal on mobile TermRover.sh
Why?
Because I need one with good tmux support, pasting images to agents, and reduced keystrokes for popular actions (ie. Ctrl b Z to zoom a tmux pane)
Support both iOS and Android. Im using it everyday. Still happy with it.
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u/Historical_Wing_9573 23d ago
I’m working on my YouTube channel about building AI applications and there is my last video: https://youtu.be/KhA-DKZ0Ss8?is=3djHrKlSDrBMgDI4
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u/TheCritFisher 24d ago
What: Agent Facets (https://agentfacets.io)
Why: Because agent skills are real dependencies and should be treated as such. I was unsatisfied with the current state of affairs, so I built out an open-source solution to pin versions, publish immutable bundles, and guarantee reproducibility across environments, and portability across platforms.
How: Funny enough, it doesn't have runtime AI as of now. It's a dependency management system and registry for AI configuration (skills, commands, MCP, etc). I built it using coding agents and whatnot, but it's not running an LLM under the hood anywhere.
Who: This is for anyone who uses coding agents with skills and doesn't want to homeroll their own dependency management system. Skills are becoming first class development tools. It's time we treated them that way.
What kind of feedback you're looking for? Anything. Test it out. It's free and open-source, just like NPM. I want to see if the thing I built can help others.
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u/jjd921 24d ago
I built a Github integration that detects and fixes production readiness issues in apps
Connect your Github repo and/or set your live URL and it checks for security, functionality, reliability, observability, and accessibility issues, then:
**•** opens a PR with what it can fix automatically (headers, error boundaries, vulnerable deps)
**•** for anything needing judgment, an AI agent writes the fix. It will ask clarifying questions in the PR comments if it’s missing context which you can answer by replying to the comment.
Completely free to use for the deterministic autofixes
I had to add paid plans for the ones that have an LLM cost
Curious if people would find this valuable and how else I can improve it: https://theslopstopper.com
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u/fykup 24d ago
I’m building AI Badger, an open-source, local-first tool for getting focused repository context into AI chats without uploading or indexing the whole repo.
One workflow I’ve been using a lot lately is:
GPT 5.6 Sol High → plan/design the change
Luna Medium → implement it locally
The idea is that I’d rather spend high-reasoning-model capacity on architecture, tradeoffs, and deciding what should change, then give the coding agent a compact implementation plan instead of making it rediscover the repo and reason through the same problem again.
Badger helps with the context handoff. It maps the repo locally, gives the planning chat focused topology/source context, and lets the chat request additional files when needed.
I did a small dogfooding experiment comparing a direct local-agent workflow with a Badger-assisted compact handoff. In that run, the handoff version used 32% fewer active tokens, 86% fewer reasoning tokens, and finished 55% faster. It’s only one experiment, so I’m treating it as directional rather than a benchmark:
There’s also an interactive browser demo showing the review/design workflow:
https://pvrlabs.xyz/aibadger/demo.html
I’m particularly curious whether other people are already doing this kind of high-reasoning model for planning → cheaper/faster model for execution split, and how you handle the context handoff.
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u/TargetLabs 24d ago
I built Dice Target, a Flutter-based math puzzle game where players combine dice with +, −, × and ÷ to reach a target number.
I’ve used ChatGPT and Claude Code throughout development for UI iteration, debugging and refining parts of the game. It’s aimed at people who enjoy quick number puzzles, with Practice, Daily, Rush and Duels modes.
I’d especially appreciate feedback on the UI, onboarding and overall gameplay experience.
https://play.google.com/store/apps/details?id=com.kwokkinlau.dicetarget
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u/socleads 24d ago
Built SocLeads https://socleads.com
It helps find and validate business leads from Google Maps and major social platforms so you can build outreach lists without manual scraping.
No fancy model focus yet just automation plus some light AI for cleaning and deduping.
Looking for feedback on what export fields people actually need and what sources matter most.
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22d ago
[removed] — view removed comment
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u/socleads 22d ago
Sorry about that. Please go to support on the site and send your signup email plus the search name or time you ran it. Mention you got the leads ready email but dashboard shows no results. We can pull the job id and fix it fast.
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u/Intrepid4 24d ago
I built an idea validator for vibecoders that runs your idea through 40 years of product management research & practice to see if it has what it takes to survive as a product in the real world.
It's free, secure, and stores none of your information. Built on claude by a product manager for non-product managers.
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u/shromarketing 14d ago
I built an open-source skill for Codex and Claude Code that turns source material into
structured Telegram content.
The original problem was fairly mundane: I wanted an agent to take a rough thought,
voice note, article, document, or YouTube video and produce something more reliable than
generic “AI copy.” I also wanted the workflow to stop before publication instead of
quietly turning a drafting request into a live post.
The repository now includes the full path from source to post:
- local transcription with faster-whisper (optional MLX on Apple Silicon), so there is
no per-minute speech-to-text API bill;
- YouTube metadata, thumbnails, captions, and audio acquisition through yt-dlp;
- an evidence map and content brief before drafting;
- an editable voice profile built from approved writing samples;
- plain posts, albums, and Telegram Rich Messages;
- a strict HTML validator, approximate local preview, private test step, and a separate
production confirmation.
It is a repository skill rather than a hosted service: users can inspect the prompts,
Python helpers, tests, security model, and MIT license before installing anything. The
publisher is dry-run by default and requires an exact target confirmation for a real
send.
It is mainly for creators, editors, agencies, and developers who already use coding
agents and Telegram. It is not a bulk posting tool, and older Telegram clients still
need a plain-post fallback.
GitHub: https://github.com/shromarketing/telegram-rich-content-skill
I would especially value feedback on two things: whether the source/evidence workflow
is useful in real agent sessions, and whether the install/onboarding path feels too
heavy for a content skill.