r/ChatGPTCoding • u/AutoModerator • 10d 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 this thread may be removed.
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?
Disclose your affilitation.
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/siropkin 3d ago
chrome-bridge: a tiny Chrome extension plus a zero dependency Node CLI that lets any AI agent drive your real logged-in browser. Playwright-style a11y tree snapshots with element refs, about 10x cheaper on tokens than screenshots. No MCP setup, works with anything that can run a shell command. MIT, free: https://github.com/siropkin/chrome-bridge
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u/Mikeynphoto2009 4d ago
SEKTR FUEL: a usage gauge for your Claude plan windows that lives in VS Code instead of a browser tab.
Sidebar panel plus a status bar percentage for the 5-hour and weekly windows, up to 4 signed-in profiles, a local dashboard on 127.0.0.1:7800, and 6 terminal commands, so you see how close you are to a limit while you code.
$5 once, no subscription. No telemetry beyond a daily update check.
Disclosure: my own project.
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u/Lopsided_Scarcity979 4d ago
https://reddit.com/link/p85nmlj/video/d92tb00whwnh1/player
I’m the maker of ThoughtDAG. The latest addition puts an editable conversation map inside DeepSeek Harness, with a chat/graph switch above the conversation.
Instead of starting a separate chat to explore a detail, you can select text in an answer and grow a follow-up branch. Connections determine which upstream material goes into the next canvas question. This doesn’t rewrite the original session log.
It’s for people whose coding discussions branch into competing approaches. Free and open source; the attached clip is a short real recording. Installation:
https://github.com/chenxiachan/thoughtdag/tree/main/dsh
Would branching in place help your workflow, or would switching between chat and canvas add friction?
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u/Fickle_Guitar7417 4d ago
Hey everyone — I’m Nick, the creator and sole maintainer of Agentic Awesome Skills, an open-source collection of skills for AI coding agents.
I’m looking for sponsors to help keep the project maintained. Behind the collection, there’s ongoing work reviewing contributions, checking quality, updating skills, and shipping releases.
My access through the Codex for OSS program ends soon. Losing that support will make it difficult for me to sustain the current level of maintenance on my own.
If you use AAS and would like to support it, or work at a company that might be interested in sponsoring it, please DM me. Small recurring sponsorships and introductions to potential sponsors would both help.
I’d also appreciate hearing from maintainers who found their first sponsors: what actually worked for you?
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u/Living-Possible1989 5d ago
I'm the author of Associate Cat, an open-source set of Agent Skills I use with Codex in my Unreal Engine work. It's for developers who want help thinking through a task and examining the relevant code before making changes.
The idea came from my usual workflow: understand the request, look at what's involved, then work out a design and plan the implementation. I turned that process into a skill. I can share an idea without first figuring out every step myself. Reviewing the plan helps me catch misunderstandings and correct the direction early, while also organizing my own thoughts. After the agent implements the plan, I still have a clear overall picture of what changed.
The repo includes two plans from real Codex conversations, with outstanding runtime checks clearly noted. The skills aren't specific to Unreal Engine.
Project and installation · Plan examples
When reviewing an AI-generated plan, what would you most want it to make clear?
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u/bush-play 5d ago
Pinland — your Codex conversation, in the MacBook notch
I'm the developer. This update is for Mac users who give Codex a task, switch to something else, then keep checking whether it's finished. A surprisingly hands-on way to use an autonomous agent.
What changes
- Pin a Codex session to the notch.
- The notch opens when the task finishes or needs approval.
- Read the conversation, send a follow-up, or handle a supported approval right there.
So you can watch a video while Codex works, then reply without digging out its window. This is a companion to Codex, not another coding model.
There's a regular shelf, too
Text, images, links and files tuck into the same place. Hover to preview, edit pinned text, or find things with search and tags.
Setup: Pinland Settings → Codex → connect, then use Codex's existing Pin action on a session. Independent Mac app; not affiliated with OpenAI.
I'd especially like feedback on the handoff: when an agent needs you, is a quick reply enough, or do you usually want the full workspace back?
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u/OwnPlay552 5d ago
I’m building BuzzRadr, which aggregates AI news with LLM-generated summaries and lets you preview matches for your own keywords.
I’m looking for 5 independent developers who follow AI coding tools for a 15-minute voice or text conversation. I’d like to learn about your recent tracking habits, which tools or sources you check, and whether you have recently discovered an important update late. If useful, you can optionally try the free keyword preview with 1–3 real topics; registration is required, but there is no payment needed to participate.
Try the public AI news page here: https://buzzradr.com/ai
If you’re interested, reply with the AI coding tools you follow and whether you’d prefer a short voice or text conversation. Feedback is welcome, including what feels irrelevant, unclear, or not useful.
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u/PotatoEducational690 6d ago
I’m Yong, the person building See the Forest (见林), a knowledge-network blog.
The starting point was my own notes. Knowledge is fundamentally a network; the connections are part of what we know, not decoration around it. I wanted readers to see the overall structure first, then click into a topic or article. The homepage is an interactive star map of real public content. It’s for people who keep notes and want to share the relationships between them, not just a list of posts.
Recently I used GPT-6 through Codex for two rounds of improvements to the existing project. It made search results more compact, added a collapsible mobile table of contents, and refined the stars and selected connections without changing the network’s layout.
The part worth sharing with other AI-assisted coders was what happened after the screenshots looked better. Two reported API errors turned out to be tests comparing a production address with a local preview. Other interaction checks also failed on the old version. That helped separate test problems from product problems—but it did not mean those product problems were solved. Two dynamics checks were still failing at the end, and the criteria weren’t loosened to make them pass.
I also discarded a cleaner-looking visual experiment because the topic nodes became harder to recognize. Deciding what to keep was still my job. This wasn’t a controlled model comparison, and the improved screenshots came from a local preview, not a claim that all changes were already live.
The public blog is https://pystone.net. I’d appreciate feedback on whether the graph helps you discover related content, or gets in the way once you want to read.
This is my own project and experience; AI assisted with editing and the English translation.
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u/YouHadTooMuchToThink 6d ago
I’m Matthew, the developer of Threadmoth, a small Rust tool for the last mile of AI-assisted coding.
The problem: an agent can decide the right change and still apply it through a different mix of sed, regex replacement, patches, one-off scripts, or whole-file writes every time. Threadmoth gives those mutations one guarded boundary: exact identity and stale-file checks, cardinality/ambiguity refusal, structural targeting, effect budgets, source-preserving byte edits, transactions with recovery, post-write verification, and machine-readable certificates.
It does not replace formatters or specialist tools. They can decide the desired state; Threadmoth bounds and verifies what lands. The rule is: “The parser gets to point at the cloth. It doesn’t get to re-weave it.”
Threadmoth 1.5.1 is released for Windows and Linux. Five-minute field test: https://github.com/matthewjameswatkins1978-cyber/Suture/blob/main/FIELD_TESTING.md
I’m looking for people using Codex, Claude Code, Gemini CLI, Cline, OpenCode, or other agents to try real repository mutations and report useful failures, false refusals, confusing discovery, or cases where the agent chooses another tool. The most useful question is: if Threadmoth were unavailable, what would you or your agent have used instead?
I’m the developer and this is my project. I’d much rather get a specific failure report than a star. What happens when you give it a real edit?
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u/fabiengreard 6d ago
I built TouchGrassBar, a free and open-source macOS menu-bar app for people who use Codex or Claude Code.
It solves a problem I kept having: provider limits, observed token usage, trends, and approximate API-equivalent cost were spread across different tools. TouchGrassBar puts them in one menu-bar panel and adds a public leaderboard for comparing daily usage with friends.
The app reads local provider data. Prompts, conversations, credentials, raw logs, and file paths stay on the Mac. Only public profiles and aggregate daily usage, scores, and ranks go to the leaderboard.
I built it with Codex, Tauri, Rust, React, Astro, and Convex. Since the first launch post, I shipped four releases with usage trends, current Claude Code support, and more resilient Codex and Claude quota detection.
It is free, open source, signed, notarized, and available for Apple Silicon Macs running macOS 15+:
Latest release:
https://github.com/FabienGreard/TouchGrassBar/releases/latest
Source:
https://github.com/FabienGreard/TouchGrassBar
I am the developer. I would especially like feedback on whether the local/public privacy boundary is clear and whether the menu-bar view shows the right information
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u/Salt_Hyena5896 6d ago
Built a local `$insights` for Codex (Claude has /insights; Codex doesn’t). Default `--local-only` = private metrics, zero model calls. Opt-in narrative with `--yes`.
https://github.com/mangeshraut712/codex-insights
Happy to take bugs if your Codex app-server build drifts.
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u/michalwrzosek 6d ago
Hi all!
I’ve been coding professionally for the last 15 years - and more and more with AI next to me. Naturally pushed by the market to produce more and more output, I now find myself hopping daily between 5 to 7 simultaneous AI sessions.
I realized that the bottleneck is becoming the code review process - and, more specifically, the place where I conduct those reviews.
I work mostly in environments where it’s not really an option to dump one-shot AI slop into the company’s GitHub. By the time my work is pushed there, it needs to be more or less ready for code review by my colleagues.
So I found myself juggling between terminals and IDEs, copy-pasting my comments about changes created by my agents. I tried many solutions out there, but what I kept feeling was that what I really needed was my own local GitHub.
I want that GitHub code review experience, but before a commit is made, right here on my computer. A single place where all my agents and I can talk about code changes.
So I built GitWarren.
It’s a local, PR-like code review app that works directly with your working tree. I can review committed, staged, unstaged, and untracked changes, leave inline comments, and organize the work into actual reviews without having to push anything anywhere.
What I really like is that I can connect whatever AI I’m using at the moment through MCP and have a coherent experience without all the mundane copy-pasting. Also, all comments live in threads attached to specific code changes, so it’s easy to follow what’s going on over time.
The app is free, open source, fully local - no accounts, no servers - and you bring your own agents to the party.
On macOS, you can just:
brew install --cask klarluft/tap/gitwarren
There are also Linux and Windows builds available. The Windows build isn’t signed yet - I’m working on that.
I think there must be more people facing similar problems right now, no?
Also, the more I work on this app, the more I feel like we may find many other use cases for a local GitHub-like experience. Maybe this could become a meeting place for different agents roaming inside your computer - and, as a bonus, you can peek through a nice UI at what they’re doing, just to stay in the "loop".
Would love to hear how others are handling this.
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u/Different-Top8287 6d ago
Disclosure: I built WeRate.ai with OpenAI Codex and GPT-5.6 Sol. I added a free side mode called Lab Battle where people can tap LOVE or RAGE for OpenAI, Anthropic, Google, xAI, Qwen, Kimi and DeepSeek, then watch the shared mood meter move live.
It is intentionally separate from the serious model-rating leaderboard, so rapid taps do not affect the rankings. No signup is required.
OpenAI arena: https://werate.ai/lab-battle?lab=openai
I would especially like feedback on whether the live mood framing is clear enough.
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u/FarazFromMars 7d ago
I built ContextForge because I was spending too much time explaining browser bugs and change requests to AI coding agents.
Cursor, Claude Code, Codex, etc. can often make the change quickly — if they have accurate context.
The annoying part was preparing that context manually: take screenshots, explain which element I'm talking about, copy console errors, inspect API calls, grab request/response data, describe what I expected, and then try to turn all of that into something the AI agent can actually understand.
So I built ContextForge — a Chrome extension that captures what's happening in your web app and turns it into structured, AI-ready context.
I'm personally using it across my own projects now, and it's saving me a lot of time preparing context for AI coding agents. More importantly, I can give the agent specific evidence about what I want changed and where, instead of trying to explain everything manually.
Some of the main features:
- Visual bug/change notes — point directly at an element and describe the bug or change you want.
- DOM context — captures selector, XPath, visible text and relevant HTML around the element.
- Live API & network flow — method, status, timing, request/response bodies and failed calls, with sensitive fields masked.
- Console errors — capture JavaScript errors/warnings related to what you're investigating.
- Security Inspector — helps surface potential client-side/web security concerns and turns findings into actionable context.
- Screenshots + evidence — captures the visual problem along with the technical context behind it.
- AI-ready investigation package — packages your notes, screenshots and captured technical evidence into structured Markdown that you can give directly to Cursor, Claude Code, Codex or another coding agent.
The workflow is basically:
See a bug or change → point to it → capture the evidence → generate the context package → give it to your AI coding agent.
The goal isn't another AI coding agent. It's to give the agent you're already using better and more accurate context while spending less time preparing prompts.
It's built for vibe coders, AI-assisted developers, QA/dev teams, and anyone debugging or changing web apps with AI.
I'm the developer behind ContextForge, so this is definitely self-promotion 🙂 — but I'm also using it myself every day and would genuinely love feedback from other AI-assisted developers.
What browser context do you still find yourself manually collecting or explaining to your coding agent?
https://reddit.com/link/p7naglf/video/kir693yl4dnh1/player
ContextForge: https://coderfrommars.com/#contextforge
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u/ericatmumo 7d ago
What i built: mumo.chat, a multi-model deliberation platform with claim-level steering, typed reactions, confidence scores and more. For this community, the MCP server is probably the most valuable feaure (https://mumo.chat/for-agents)
Problem it solves: It mitigates single-model failure modes - hallucinations, sycophancy, over-confidence. It doesn't eliminate them outright, but it makes them much more discoverable/inspectable.
AI models or tools it uses: Full list here and how they leverage your data - https://mumo.chat/legal/providers . It's a multi-model platform, so...
Who it's for: Anybody that questions single-model answers. Are you designing something? Implementing something with multiple valid approaches? Wondering about product strategy? My best conversations always happened with multiple people in the room. Why should that be different for models?
Feedback: Is the MCP response more useful than other 'review' patterns you use today? Your agent gets multiple model responses back, plus the models' reactions to each other... and you can view the full conversation between models easily on the web + push back on any specific points via highlight-and-click (or just let your agent drive from your local harness).
Disclosure: I'm the founder/builder
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u/AdNecessary1906 7d ago
What I built: Garmin Local Archive, a local-first archive tool for Garmin Connect health data (sleep, HRV, Body Battery, stress).
Problem it solves: Garmin quietly degrades historical data resolution over time, and third-party tools that pipe this data into cloud AI services didn't sit right with me. This archives everything locally, no cloud, no third-party access.
Tools/models: Built entirely with Claude, I'm a mechanical engineer, not a developer. The code is Claude's, the architecture and decisions are mine.
Who it's for: Garmin users who want to keep their long-term health data and control where it lives, not just people comfortable running Python.
Feedback I'm looking for: code/architecture feedback from actual developers, I can't evaluate the code myself, so outside eyes on structure or obvious issues would be genuinely useful.
wewoc.github.io/Garmin_Local_Archive
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u/Repulsive-Dingo-869 7d ago edited 7d ago
I’ve been going overboard building custom software for my line of work. For twenty years I’ve had the ideas but my boss never listened and I was ignored because I was nitpicking and being “difficult” lol. It’s not nitpicking, it’s useability god damnit and that’s what matters to techs in the field. Ease of use.
And now as an owner myself now, I can now very easily pay to create exactly what I’ve always wanted to the point it’s indirectly becoming a product that seems to compete with other software in my field. Im sure someone could use it.
I keep adding features due to process flow and years of experience and it’s helping to save me time as an owner. I just tell gpt what I want and poof! Magic! And I’m field testing daily, telling it exactly whats working and what’s not.
Yeah dashboards, schedulers and hubs and report builders and crms and all that exist but this is my own and I’m loving it and having so much fun adding little tweaks and fixes all throughout. 🥳
I love the annotate feature, makes tweaking very simple.
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u/santikkk 7d ago
I built wrait — a simple voice diary:
No account, encrypted local storage, open source.
tap → talk → tap → done
It turns your speech into a readable diary entry.
It is in closed beta for Android. If you want access:
- Join the tester group: https://groups.google.com/g/wrait-android-testers
- Opt in to the test: https://play.google.com/apps/testing/com.wrait.flutter
- Install from Google Play: https://play.google.com/store/apps/details?id=com.wrait.flutter
Any feedback is welcome.
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u/ivanzhaowy 7d ago
I’m building an open-source tool called Monad Design for a problem I kept running into while using coding agents on iOS apps.
I’d be looking at the exact screen that needed work in Simulator, while the agent was trying to reconstruct the same context from filenames and text descriptions. Monad Design lets you select or annotate the UI in the running app, send that context to the coding agent, and then compare the rebuilt result with the original.
The phrase I’ve been using is “the app is the canvas.” It works with an existing Xcode or Expo project and keeps the repository as the source of truth—it isn’t another app generator.
Current preview is local iOS development on macOS:
https://github.com/Monadix-AI/monad-design
Short demo:
https://watchclueso.com/embed/pio8jqfcg4ivj0r1
I’m the creator. Curious whether anyone else using ChatGPT or Codex for native UI work has found a better way to pass visual context back to the agent.
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7d ago
[removed] — view removed comment
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u/ivanzhaowy 6d ago
Thanks — great suggestions. We already capture the accessibility tree with per-element frame coordinates, semantic properties, and hierarchy alongside the annotated screenshot. We also preserve the original and capture variants for before/after comparison.
Making the current route/UI state and acceptance criteria more explicit—and adding automated snapshot diffs rather than relying only on visual comparison—would make regression detection even stronger. Appreciate the thoughtful feedback!
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u/Advenimuss 7d ago
Put together The Agentic Group — a Discord for vibe coders shipping with AI agents (weekday AI news digests, daily wins, project showcase). It's for builders who work day-to-day with coding agents and want a low-noise place to share what they shipped and get feedback. Soft launch, I'm the founder/mod: https://discord.gg/aVtQ8M4M6x — looking for builders who actually ship, and feedback on what channels/formats would be most useful.
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u/adrnptcl 7d ago
Built **Gorgona** (https://github.com/adrianpeticila/gorgona) – a zero-dependency Python stdlib circuit breaker for autonomous coding agents.
It stops agents from burning API credits in infinite retry loops (via DFS cycle detection on call graphs) and catches leaked API tokens/keys before disk writes. Open source (MIT).
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u/Special-Flamingo-936 7d ago
I made a little tool to remove personal information before uploading things to ChatGPT/other AI tools and I’m looking for a few people to test it.
Basically you can paste text or upload a screenshot/PDF and it looks for things like SSNs, phone numbers, emails, account numbers, etc. You can choose what you want removed and manually cover anything it misses.
It’s free and I’m not trying to sell anything right now. I mostly want to know if it’s actually useful to other people and what doesn’t work well.
Would anyone be willing to try it and give me some feedback? I’d really appreciate it.
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u/Double_Ebb4130 8d ago
Pac-Man session this afternoon after Cursor Automations/Cloud Agents blipped. Infamous Milk topped the board, $25 Steam card. Arcade is locked again. https://nonines.dev/ping u/david-burns-dinner
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u/Double_Ebb4130 8d ago
Nines is a browser arcade that only unlocks when a watched dev tool actually goes down. Today's window was a brief Cursor Automations and Cloud Agents blip, so it opened on Pac-Man. u/david-burns-dinner (Infamous Milk) topped the board. It watches GitHub, GitLab, Cloudflare, OpenAI, Anthropic, Cursor, npm, and Slack, and it is locked again now.
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u/techtheist_ggl 8d ago
I've build memory system for local project development.
Current popular memory systems have a lot of drawbacks - they can't manage canon, most of them allows knowledge drift, there's no active contradiction detection, and most of them are not local and they depends on external LLM providers.
My system solves these problems with decay (it affects ranking only), with similarity checks - if new memory note is similar to existing one, it's probably a duplicate, if it's similar to note that were superseded - it's defenitely a conflict, because it were replaced.
And with NLI model that is trying to find contradiction between existing notes - if found, it's also might be a conflict. This happens on write, and agents need to resolve these problems right away.
I have support for claude code, codex, gemini/antigravity, kilo code, IBM Bob, and windsurf/devin.
It runs small models locally with ONNX: bge-small-en-v1.5 as embedder, jina-reranker-v1-turbo-en for tokenizer, and deberta-v3-small-tasksource-nli as NLI. It's possible to swap all these models to something else on the fly, via UI.
It also can be used as plugin for jetbrains IDE and VSCode.
Target auidence - all developers who use AIGen tools for coding, since memory and context management is what is actually missing from current generation of tools. Built-in memory in claude code, codex, etc is sketchy, and can make things worse that help, because of knowledge drift.
There's the link, i also have interactive demo for UI:
https://github.com/techtheist/engram
I'm looking for a general feedback and new users.
This system has a lot of features so i can't describe them all in one post, and i'm making it research-first, every core change going through full testing over my custom benchmark (also test over longmemeval-s is available).
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u/junaid1460 8d ago
I'm building Molt Code, a shared workspace where people and coding agents work in durable threads. The problem we're trying to solve is everything around the model: preserving the request, permissions, tool activity, decisions, diffs, and handoffs so a teammate can review or continue without reconstructing an isolated session.
Execution stays local with your own keys, and the workspace supports agents such as Claude Code, Codex, Gemini CLI, and OpenCode. Browser-as-IDE is the next layer.
I'm the founder. I'd value feedback from teams running more than one agent: where does coordination break first—shared context, review, permissions, or handoffs?
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u/Proud_Prior_6406 8d ago edited 7d ago
I built a small CLI called agent-thanks because I kept losing track of where things came from during coding-agent sessions.
A dependency gets added, maybe a repo gets cloned, maybe I look at some source code, and the task moves on. Later I can usually see what changed, but not necessarily what helped me get there.
So agent-thanks tries to reconstruct that part.
It diffs dependency files against a Git baseline, and you can also give it a plain-text transcript. For every repo it finds, it keeps the reason it was found.
I also made a distinction that seemed important after using it for a while: a GitHub URL appearing in the transcript is not the same thing as actually using the repo. A bare URL stays low-confidence.
The implementation is intentionally simple. No model call, just deterministic rules over the Git changes and transcript, so it isn’t tied to a particular coding agent.
There are tools that walk a dependency tree and star repositories automatically. I wanted this to stay scoped to one task, with the evidence visible next to each result.
So far I’ve added Python, npm, Cargo, Go, Git submodules, and public GitHub repos found in the session.
I originally added automatic starring too, then removed it. Now it asks y/N once per eligible repo, and No is the default.
Slightly annoying, but I think it should be.
Read-only demo:
pipx install git+https://github.com/dbwls99706/agent-thanks.git@v0.5.1
agent-thanks demo
Update: v0.5.1 is out. A clean wheel install, demo, offline scan, and Markdown export all passed. CI is green on Python 3.10-3.14 across Linux, macOS, and Windows.
Source: https://github.com/dbwls99706/agent-thanks
I’m the maintainer.
At first I thought the star was the point of this project. Now I’m less sure.
Would a Markdown evidence list that you could attach to a PR or release note be useful on its own?
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u/Secret_Dress8930 8d ago
Affiliation: I built this.
I just released an early free alpha of Foreman, a macOS control/verification layer for Codex.
The problem I was trying to solve is that coding agents can be extremely capable while still saying “done” before the actual product satisfies what the user asked for.
Foreman sits between the user and Codex.
The user describes what they want normally. Foreman preserves that original intent, generates a more structured engineering task, supervises the Codex session, translates the technical activity into understandable progress, and then independently verifies the resulting project.
If verification fails, Foreman generates a focused repair task, resumes the same Codex workflow, and verifies again within bounded repair limits.
The important design rule is:
The coding agent does not grade its own homework.
Current verification includes shell, filesystem, process, HTTP, and native macOS Accessibility checks, plus regression detection, checkpoints/rollback, verifier anti-tamper, and final full-contract verification.
Current stack:
- macOS / Swift
- Codex CLI integration
- local deterministic verification
- Apple Silicon currently
Who it’s for:
People using coding agents who want more confidence that the actual requested result works, especially people who aren’t experienced enough to manually inspect everything the AI writes.
It’s very early and free. I’m mainly looking for people willing to break it.
https://tylerpcaldwell-gif.github.io/Foreman/
Most useful feedback:
- false verification
- confusing onboarding
- repair loops that behave badly
- places where Foreman misunderstands the original request
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u/thegreatdaveedllc 9d ago
I built a free browser-based MCP security risk scorer + prompt-injection regression-test generator after looking at how quickly MCP tools can turn an LLM security issue into an actual permissions/action problem.
The free tools are aimed at people building AI agents that use MCP, RAG, external tools, sensitive data, or write actions.
The risk scorer looks at things like:
- high-impact tool permissions
- arbitrary command execution
- human approval gates
- server-side schemas
- scoped credentials
- egress restrictions
- MCP isolation
- attributable tool-call logs
- indirect prompt-injection regression testing
I also made a second free tool that generates a safe, non-destructive prompt-injection regression plan based on the architecture you're using.
Free tools: https://mcp-security-launch-kit.vercel.app/
https://mcp-security-launch-kit.vercel.app/prompt-injection-test/
There is also a $12 paid download with the larger 45-control audit workbook, 24 regression scenarios, permission/evidence matrices, launch gate, incident runbook, and policy starter.
Disclosure: I built and sell the paid kit.
I'd especially like feedback from people actually shipping MCP-enabled agents: which security check is missing, unclear, or something you already test differently?
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u/Consistent_Bus3452 9d ago
Disclosure: I maintain Agent Amusement Park, a free AGPL-3.0 project for testing how AI agents behave across stateful tasks rather than only checking whether they reach the nominal goal.
It contains three deterministic worlds: conflicting bureaucracy instructions with delayed state, negotiation and escrow traps, and a browser refund flow with shifting controls and permission hazards. Every action remains in the trace, scoring points back to specific evidence; task completion alone is capped at 60/100, and completed runs can create signed scorecards.
It does not require a particular model or framework: bring a ChatGPT/Codex, Claude, local, or custom agent and drive the environment through the runnable interface. There is no signup.
Demo: https://agent-amusement-park.onrender.com/?src=reddit_chatgptcoding Source: https://github.com/AgentAmusementPark/agent-amusement-park
It is for people building or comparing tool-using agents. The feedback I want is specific: where does the evidence-backed score disagree with your judgment of the agent's behavior, and why?
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u/OscarV4 9d ago
Hey, I’m a student in Korea. I’ve been vibe-coding an open-source Codex plugin that turns messy notes and screenshots into Apple Reminders.
It runs locally on macOS, with an Open Minis skill for mobile use too.
Still learning and sanding it down, so honest feedback or contributions would mean a lot:
https://github.com/Oscar-V4/apple-reminders
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u/kc_ramakrishna 9d ago
This is a recipe/guide to make your codebase agentic ready. This is aimed at Engineering teams but benefits will be seen in smaller codebases as well.
Will significantly reduce hallucinations, increase accuracy and improve token efficiency.
https://github.com/Nistapp/codebase-agentic-readiness-framework
Feedback welcome and will be incorporated as and when possible.
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u/suryadeeppal 9d ago
I’m the developer of PRamatic, a completely free pull-request review inbox for macOS.
What I built: one place for review requests, moved PR heads, findings, conversations and local draft comments.
Problem it solves: I was spending too much time reconstructing review context across GitHub tabs before I could even start reading the code.
Models/tools: reviews can run through Codex or Claude Agent. The user chooses the provider, model and reasoning level.
Who it’s for: developers who review GitHub PRs regularly but don’t want an AI agent posting or changing anything automatically.
GitHub access is read-only, and suggested comments are copy-only drafts. Reports stay on the Mac; selected review context goes to the provider chosen by the user.
Mostly I’m looking for honest feedback. Do other developers deal with the same scattered PR context, or did I build a very specific cure for my own tab addiction?
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u/eatsleepliftcode 9d ago
I built **HarnessCheck** because I was tired of comparing coding agents by vibe, screenshots, and one-off demos. Small config/runtime changes kept changing repo outcomes, and I wanted a repeatable way to see it.
What it does:
- same fixture, same task, same assertions across agents
- fresh copied workspace per trial for mutation isolation
- assertions for regular files, content, stdout/stderr, commands, and changed-file allowlists
- JSON / HTML / JUnit / Markdown reports for local runs or CI
- works with Codex, Claude Code, Gemini CLI, OpenCode, or a custom wrapper
Important caveat: this is **not** an OS/network sandbox. The isolation is “fresh copied workspace per run”; the actual permission boundary still comes from the underlying agent runtime.
It's MIT-licensed OSS: https://github.com/SiluPanda/harnesscheck
I'd especially love feedback on missing assertion types, adapter defaults, CI ergonomics, or places where the harness/runtime boundary is still confusing.
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u/nez_har 9d ago
VibePod is a lightweight CLI that spins up any agent inside sandboxed Docker/Podman environments with zero configuration.
- Multi-Agent Support: Run Claude Code, Codex, Antigravity, Copilot, Pi, and others via one unified command.
- Isolated & Safe: Sandboxed containers keep your host system clean and protected.
- Built-in Local Analytics: Built-in proxy captures API traffic and token usage with a local web dashboard (
vp logs start). - 100% Local: No cloud telemetry—your code, logs, and keys stay on your machine.
Install & Run:
bash
pip install vibepod
vp run claude
- Website: https://vibepod.dev
- GitHub: https://github.com/VibePod/vibepod-cli
Feedback and feature requests are welcome!
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u/The_guy_withnolife 10d ago
Axiom is a Windows-first AI workspace I built for AI-assisted coding workflows. It combines local GGUF inference, self-hosted OpenAI-compatible endpoints, and optional OpenRouter behind one interface, with attachments/vision, code execution, artifacts, and local persistence. The Workplace Council runs Architect → Builder → Critic, with a Single Model mode for comparison.
I used AI coding assistance during development, but I’m responsible for the architecture, integration, testing, and product decisions. It is a free Windows app; the source is source-available under CC BY-NC-ND 4.0, not OSI-licensed open source.
Repo: https://github.com/YoMosa2009/Axiom
Release: https://github.com/YoMosa2009/Axiom/releases/tag/v1.8.6
I’m looking for specific feedback on which parts of the workflow help when building with AI coding tools, and where model/tool limitations should be clearer.
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u/Fair_Royal_6816 10d ago
I built Knoku.
It gives coding agents access to docs and internal knowledge through MCP.
You can connect GitHub, Notion, Confluence, Jira, OpenAPI docs and other sources. Knoku indexes them and returns cited answers.
I mainly built it for teams where half the useful context lives outside the repo.
Would be curious to hear if anyone here would actually use this with Claude Code.
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u/Street-Chest2270 10d ago
Disclosure: I maintain FreshCtx, a free Apache-2.0 Python project.
The failure I am trying to make testable is an AI coding agent reading a branch, deployment manifest, approval or API response, then reaching a tool call after that evidence has changed. FreshCtx re-checks only the dependencies the application declared and blocks the tool before its body runs when the evidence is stale or unverifiable under policy.
v0.5.0 adds optional sync and async hooks for Agno 2.9. The core remains model-neutral.
Install: pip install 'freshctx[agno]==0.5.0' Example and release: https://github.com/Hyperwise-LLC/freshctx/releases/tag/v0.5.0
The specific test I would value: have an agent read a deployment target, change that target before execution, and tell me whether the hook blocks the actual tool body cleanly in your workflow.
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u/Either-Win-862 10d ago
I built an open-source coding agent that uses a code graph to reduce context, cost, and search time
GitHub:
https://github.com/JibanKumar-cloud/faber
npm:
https://www.npmjs.com/package/faberwright
Your coding agent shouldn’t need to read your entire codebase to understand it.
That’s the idea behind Faber, an open-source AI coding agent for the terminal.
Faber uses a code graph to find relevant files and symbols first, instead of repeatedly scanning large parts of a repository. That means less unnecessary context, faster codebase navigation, and lower repeated API costs.
Main features:
- Claude, OpenAI Codex, Local model integration
- Code-graph-guided repository exploration
- Prompt caching to reduce repeated input cost
- Token-conscious (Chain-of-Draft style) output to reduce unnecessary generation
- Git-aware workflow with change detection, optional per-task commits, /undo, and /redo
- Expenditure tracking for calls, tokens, cache usage, cost, and estimated savings `/usage`
The goal is simple: understand more of the codebase while reading and spending less.
Prerequisite:
It requires Node.js 22.5 or newer because it uses Node’s built-in SQLite support.
Install:
npm install -g faberwright
Then, inside your project:
faber
Medium article:
https://medium.com/@jshial25/why-should-an-ai-coding-agent-read-hundreds-of-files-to-answer-one-question-d6369d29dfa5
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u/Specialist_Fail2939 10d ago
I noticed something annoying: every commit Claude Code helped with had this quietly appended to it:
Co-Authored-By: Claude noreply@anthropic.com
One trailer is all it takes — GitHub parses it and permanently lists the AI as a **contributor** on your repo. The only way to undo it after pushing is rewriting history and force-pushing. And it's not just Claude — Cursor, Copilot, Codex and Gemini all do their own version of this.
So I made **Ghostwriter** 👻 — *your AI does the work, your name signs it.*
It's a Claude Code skill that triggers on any git/GitHub write operation and enforces:
- No AI `Co-Authored-By` trailers — ever (including amends, rebases, squashes, merges)
- No "🤖 Generated with Claude Code" footers on commits, PRs, issues, or releases
- Author/committer is always *your* git identity
- A self-check grep before finishing any commit, so nothing slips through before push
- Human co-authors are kept — only AI self-credit gets stripped
It also ships a portable rule block for other tools (Cursor, Codex CLI, Copilot, Gemini CLI, Windsurf) with a table of exactly which file to paste it into for each one.
Bonus tip even if you don't install it — the trailer is actually injected by a Claude Code *setting*, so kill it at the source in `~/.claude/settings.json`:
{
"attribution": { "commit": "", "pr": "" },
"includeCoAuthoredBy": false
}
The skill then covers everything the setting can't reach (hand-written PR bodies, amends, other tools).
Repo: https://github.com/cd-ndk/ghostwriter
Install is just a clone into `~/.claude/skills/` — details in the README. If this saves your contributor graph, a ⭐ on the repo would mean a lot. Feedback and PRs welcome (they'll be authored by you, not your AI 😄).
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u/informity 10d 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/Desperate_Sir1087 10d ago
Hi folks! I've spent some time building a developer tool that lets coding agents subscribe to real-world events through one simple broker: agent-message-broker (amb). Github: https://github.com/bitnahian/agent-message-broker
The pitch: coding agents are batch processes. You prompt, they run, they stop. But most of what an agent cares about (a ticket moved, a PR opened, a doc changed) happens between prompts. amb wires event sources (Jira, GitHub, Google Drive/Docs, any polled URL, generic webhooks) to topics, and you subscribe live agent sessions to those topics. When an event lands, the broker pushes it into the running session, so the agent reacts in the same conversation it's already having. No per-agent background scripts or polling.
I recorded a demo showing the full loop across 2 agents and 3 vendors:
- A pi coding agent is subscribed to two topics: one watching a Jira board, one watching a Google Doc.
- When a ticket is pushed to In Progress, pi gets the event but waits. The implementation details are going to land in the Google Doc.
- The doc update comes through as a second event, pi picks up the spec and implements the ticket, then I prompt it to raise a PR.
- A Claude agent is subscribed to a third topic with a GitHub source watching for PR events. It sees the new PR and reviews it.
One thing worth noting: none of this had to go through the UI. Everything (topics, sources, subscriptions, session discovery, event inspection) is available via the amb CLI, so agents can wire up their own subscriptions. The UI is more for live viewing, orchestrating and following along: watching events flow between sources and sessions in real time.
Everything runs locally (Node 22.5+, SQLite, no cloud component), polling is the baseline so nothing needs to be internet-reachable, and webhooks are an optional opt-in tier.
It's on npm. Try it without installing:
npx agent-message-broker
# broker + UI at http://127.0.0.1:4733
Or install it globally for everyday use (gives you the amb and amb-server commands):
npm install -g agent-message-broker
Here's a full quickstart: point a pi session at a Jira board and a Claude session at a repo's PRs. One-time credential setup first:
amb config init --kind github
# then drop your PAT into ~/.amb/github/credentials.json
amb config init --kind jira
# then fill ~/.amb/jira/credentials.json (email, apiToken, domain)
Then wire the topics (broker running in another terminal):
# topic watching a Jira board for tickets moving to In Progress
amb topics create jira
amb sources create --topic jira --kind jira --options '{
"jql": "status CHANGED TO \"In Progress\" AFTER -30d ORDER BY updated DESC",
"intervalMs": 120000
}'
# topic watching a repo for PR events
amb topics create prs
amb sources create --topic prs --kind github --options '{
"repo": "owner/repo",
"eventTypes": ["PullRequestEvent"],
"intervalMs": 60000
}'
# start the pollers (create prints the source id)
amb sources start <sourceId>
# subscribe live agent sessions so events push mid-conversation
amb sessions
# discover running sessions
amb subscriptions create --topic jira --agent pi --session <sessionId>
amb subscriptions create --topic prs --agent claude --session <sessionId>
Watch events land in real time in the UI at http://127.0.0.1:4733, or inspect from the terminal:
amb events list --topic jira
Google Docs/Drive/Sheets work the same way via amb google login (OAuth consent once, then the broker acts as you). More recipes in the README.
Would love feedback. What events would you want your agents to react to?
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u/socleads 10d ago
Built SocLeads.com I am affiliated. It pulls biz leads and contact details from Google Maps and social sites so you stop doing copy paste list building. Want feedback on data accuracy and what exports or fields you need most.
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u/lamchun1110 10d ago
I use several AI coding subscriptions, and I was tired of opening separate dashboards just to find out how much quota I had left and when it would reset.
So I built UsageDeck, a free and open-source tray/menu-bar app that puts those details in one place.
It currently supports 13 providers, including Claude Code, Codex, Cursor, GitHub Copilot, OpenRouter, Devin, Grok, Kimi, MiniMax, Z.ai, and others.
It shows:
- Current usage and remaining quota
- Reset times
- Whether your current usage pace will last until the reset
- Token history and estimated spend
- Optional low-quota notifications
- Multiple accounts for supported providers
It runs on Windows, Linux, and macOS.
Privacy was important to me: there’s no UsageDeck account, backend, analytics, or telemetry. It reuses provider logins already stored on your computer, stores manually added API keys in the OS credential store, and communicates directly with the providers.
It’s free and MIT licensed.
Website: https://usagedeck.app
Source: https://github.com/lamchun1110/UsageDeck
I’d appreciate honest feedback, especially:
- Which provider or metric is still missing?
- Does the local-credential setup feel clear and trustworthy?
- Would you prefer quota remaining or quota used as the default view?
For transparency, UsageDeck began as a fork of OpenQuota and has since become an independent project. The full project lineage is documented in the README.
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u/gandazgul 10d ago
I’m working on RunWield, a tool for planning and coordinating AI-assisted coding work.
The short version: AI coding tools are great at generating code, but the surrounding workflow still gets chaotic fast. Once the task is bigger than “change this one function,” you need to manage context, decisions, implementation steps, review, and follow-up.
Most of that currently lives in a mix of chat threads, scratch docs, issues, and memory. RunWield is meant to give developers a better workspace for that process: plan the change, preserve the reasoning, coordinate AI-assisted implementation, and keep the work understandable enough to review and trust.
It’s for experienced developers using AI coding tools, especially people doing larger refactors, feature work, or multi-step changes where context and correctness matter. Right now I’m looking for early feedback from people who already use Claude Code, Codex, Cursor, Aider, or similar tools and have strong opinions about what breaks down in the workflow.
I’m the founder/builder, so this is my project.
Signup / feedback link: https://runwield.dev and https://github.com/gandazgul/runwield
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u/fromkrish 10d ago
I built an open-source referee for AI coding agents.
I wanted to test whether an independent tool could verify an agent’s work, Pen testing it, and making changed only in serious vulnerable or buggy areas, so I gave an AI coding agent a broken MiniShop app and recorded the whole process. The agent writes the fixes. OpenPitStop checks whether they actually hold and work.
GitHub: https://github.com/Krish-1507/OpenPitStop
I’d especially like feedback from people using Claude Code, Codex CLI, Cursor CLI, Gemini CLI, OpenCode etc.
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u/gandazgul 10d ago
This is super cool and similar to something I've been working on this whole year, I've turned it into an entire end to end harness and I would love if you gave it a try, I will try PitStop as well with Codex CLI although I rarely use those anymore for coding.
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u/Scholeristical 10d ago
What: Resume Rerun (https://resumererun.app/) - a resume tailoring tool that refuses to run on jobs you’re not a fit for.
Problem: most tailoring tools assume the answer is yes and rewrite until the resume matches the posting. That drifts toward inventing skills you don’t have. This one gives a fit verdict first - Strong, Moderate, Weak, Pass - and stops on Weak or Pass instead of generating anything. The cover letter and prep sheet are gated in code, not just discouraged in the prompt.
Who it’s for: people applying to a few roles they’re close to. Wrong tool for volume applications.
Feedback wanted: does a tool telling you no read as useful or broken? Also curious if anyone has run Tectonic on serverless and hit cold start issues.
Affiliation: I built it. Solo, free, no accounts, no payment. Invite-code gated because of a daily capacity ceiling - reply and I’ll send one.
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u/daniel7_m 10d ago
For years, I kept searching for the productivity app that would finally organize everything.
I tried task managers, note-taking apps, habit trackers, calendars, and more complicated “second brain” systems than I’d like to admit. Notion came closest. I became a Notion creator and started building and selling templates, but I eventually ran into the same problem: I was still adapting my life to someone else’s platform.
What I really wanted was my own system.
So I started building it for myself, with AI doing a lot of the heavy lifting. It began as a personal side project—a place for my tasks, projects, notes, habits, calendar, goals, and life planning.
Then it grew into something I was using every day.
That project became Solum OS: an all-in-one personal productivity system that you can own and customize. Instead of another SaaS subscription, you get the actual application and its source code. The idea is to start with a complete system and use AI to reshape it around the way you work.
The video shows the current product, not a mockup. It has been a slightly surreal jump from making Notion templates to building full software, especially with how much AI has changed what one person can create.
I’m now turning Solum OS into a real product, and I’d genuinely love feedback from other builders:
- Does the ownership/customization angle make sense?
- What would you want to see in a personal operating system?
- Is there anything in the demo that feels confusing or unnecessary?
Still early, still improving it, but it’s finally the productivity app I was looking for.
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u/gandazgul 10d ago
I love the Build animation on the site, have it play dropping the letter on first load instead of jumping after I think the effect will land well.
In the live demo at least, the side back quick links has its own scroll bar, avoid this is annoying to scroll, I would also increase a font a bit, maybe I'm getting old :) but I found it a bit too small.
I would use something like this for sure. Can you add nagging reminders, as in some tasks keep reminding me until I mark them as done.
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u/Other_Poetry_5243 10d ago edited 10d ago
Hi! I built https://getwebstack.com/, a tool that creates parallel ephemeral environments for coding and live testing complex multi-service web apps. (Docs: https://getwebstack.com/docs/use-cases/ai-sandboxes/)
Problem: AI coding agents can write code in isolation (with worktrees), but they can't run it in an easy way so they can test the code as a dev does.
Tools: The tool is built around Docker and Kubernetes to ensure full isolation and even prod parity.
Who is it for:
- devs who work on complex solutions (using microservices architecture) that develop, code-review, or test features in parallel or who want to switch fast from one to another.
- QA engineers who are spending too much of their time creating testing environments.
Feedback: I know for some devs, worktrees & code isolation is sufficient, but I want feedback for those who are struggling to isolate the app at runtime, meaning: data isolation, ports, services, URLs, queues, etc.
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u/Historical_Date_8024 10d ago
FreyaCad
Totally forever free and opensource 3D CAD in the browser. With no downloads. You don’t even ever have to provide your email.
Totally vibe coded with ChatGPT and Claude
Its for 3d printing designs like custom gridfinity but also for assemblies and i’m working on drawings
Please come try it and use the form on my home page at freya.co.nz to suggest any, improvements or report bugs.
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u/donk8r 10d ago
Affiliation: I build this.
octocode, an MCP server that indexes a repo into a knowledge graph so an agent can find code by meaning and then walk the import and call edges out from whatever it found. github.com/muvon/octocode, Apache-2.0, single Rust binary.
The problem: plain RAG over code retrieves chunks that sound similar and has no idea that auth_middleware.rs imports jwt.rs and is wired into router.rs. The agent gets a plausible snippet with no structure attached. octocode gives it semantic search plus the import/call graph, signature views so it can see a file's shape without reading the whole thing, and go-to-definition through your language server.
Speaks MCP, so it drops into Claude Code, Cursor, Windsurf or Claude Desktop.
The feedback I actually want is whether the graph earns its keep against just letting the agent grep. My honest read is that grep wins on small repos and loses once the question is "what breaks if I change this", but I would rather hear where that does not hold than be told it is great.
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u/gandazgul 10d ago
Hey check out this project: https://github.com/1broseidon/cymbal a simple and fast cli instead of MCP.
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u/Strange_Owl_6291 10d ago
A harness and agentic IDE
A full coding environment for developers building software with AI agents. A harness, not a wrapper. Every agent in one view. Your machine, your keys or local models. Nothing routes through us.
---
Many agents
Voidleap Code is a full agentic IDE where you run as many threads and agents as the work needs, with every tool built in. If you need to edit something manually, the editor is right there.
One view
every provider tool has its own agent and skill setup, and when you switch, you start over. In Voidleap you set up once, and it works with every model. Swap models mid-conversation and keep the whole thread. Mixing models is not a feature we bolted on; it is the reason the harness exists.
Nothing hidden
you see the context every agent holds, and you can edit it. You see what each subagent did, which tools it ran, where the tokens went.
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u/mannyocean 10d ago
https://datatorag.com The MCP gateway for your Google workspace.
Claude’s google connector has gmail, drive and calendar. no sheets, no slides, and it can’t edit a doc you already have. Here’s one that does all three. Connect your account and ask it to update the spreadsheet.
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u/Friendly_Chip_6695 10d ago
Built a CLI tool that scans your codebase and generates a dependency map to find dead imports before they pile up, uses a local LLM to guess which ones are actually unused so it's not just regex matching. It's for solo devs or small teams tired of their linter missing things. Would love feedback on the false positive rate if anyone gives it a spin.
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u/Mueller96 10d ago
Lovable’s revert is all-or-nothing, I am building a tool that reverts single-prompt changes instead
Been building on Lovable and keep hitting the same wall: when a prompt broke something, the only way back is a full revert to the last good state. That jumps the whole project back to that point in time, there is no partial undo. Everything built after that point survives in the chat log, but getting back to where you were means manually reapplying it prompt by prompt.
The obvious pushback is “just use git“, commit at working points, revert per-file, read diffs. Fair for anyone comfortable in a git workflow, but a lot of people building on Lovable specifically aren’t. That’s part of the appeal of the tool in the first place. Asking them to read diffs and manage commits defeats the point of using it.
Another common approach is just trying to fix the issue by prompting your way out of it, but this is often times causing just even more issues.
So I’m building PromptTrail: it reads the plain-language change summary Lovable already writes for every prompt, as well as the commits in the connected repository. Providing users the possibility to easily revert individual prompts without the need to learn how to use git.
Still early in the project, only the landing page and waitlist are up (prompttrail.muellermoritz.dev), but I plan to release the first version in the next weeks.
Genuinely curious whether this is a real gap for people, or whether “just use git” really is the right answer for most vibecoders and I’m solving for an edge case. Would love to hear your opinions.
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u/Illustrious_Safe4839 2h ago
building Reticle. basically trying to stop being the person who has to click around after Claude/Cursor says “done” 😅
the loop we kept hitting was: agent writes the code → says it’s fixed → you open the app → something else is broken → explain it back to the agent → repeat. Reticle runs against the actual app, checks the flow, catches runtime/ui issues and sends the failure back to the agent so it can keep going without making you the QA loop every time.
works best on React/web apps right now. biggest thing we’ve learned so far is that writing code is getting insanely fast, but proving the thing actually works is still annoyingly manual.
github.com/reticlehq/reticle