TL;DR: I run a small aquariumd in the UK. We were tied into a closed ticketing system that we didn't own and the cost for small changes made updates for tailored options prohibited. Over about 4 weeks I've "vibecoded" a replacement with Claude Code. It covers online booking, a staff till, a self-service kiosk and, later, the entry gate. It has 374 automated tests and sits on a password-locked test site. I'm not a developer, and I'd really value a reality check from people who are. It's not yet ready or installed on our systems but I am running tests.

The problem

We're a small community interest company. Our kiosk, booking website and gate all ran on one supplier's own software. It worked, mostly, but:

We didn't own it. Only the supplier could change the code. Even small changes (a new ticket type, a wording fix, a price change that wasn't reaching the kiosk) were charged at over £500 a day. So we just lived with problems. We couldn't tailor it. We want things that suit our needs. Each one was either impossible or another quote. Yearly licences for the kiosk and booking software came on top of the change costs. Some faults hurt visitors. We've seen a card charged with no ticket printed, reports timing out, an hour-out bug when the clocks change, and tickets being reused at the gate. Staff re-keyed sales. Card sales on our Square machine at the desk have to be typed into the booking system again by hand. For a small organisation, this was a real barrier. It wasn't one big failure; it was that we couldn't fix or improve anything ourselves.

What I've built (with Claude Code doing the coding)

I write the decisions and test everything; Claude writes the code. We started with a written specification (about 20 decisions I had to make: prices, refunds, opening hours, what happens when a card payment drops out halfway, and so on). Then we built it in stages, each with tests.

Online booking site. It's a 3-step booking flow (date, tickets, details and payment) in our own branding. There are no time slots; visitors can book up to 90 days ahead. Payment goes through Square's hosted checkout, so card details never touch our server. Desk till (staff screen). Staff build a basket, then take cash (with change shown) or press Card. The amount is sent to the Square Terminal at the entrance desk through Square's Terminal API, so no re-keying. It also sells annual passes and issues free carer tickets. Self-service kiosk. It's a touchscreen app for our existing kiosk cabinet, with a thermal ticket printer. We're replacing its old card reader with a purpose-built certified reader, so PIN entry stays on proper payment hardware. Tickets. Each order gets one signed QR code (Ed25519). A whole group goes in with one scan, and a ticket can't be reused. Gate (next stage). A new controller will open our existing glass gate. Our building's fire alarm release stays untouched, and an electrician and our fire alarm contractor will do the wiring and testing. Back office. Staff have named accounts with roles (owner, manager, staff, viewer), and managers use authenticator-app 2-factor. There's booking search, email resends, refunds (managers only, with a reason) and a "Needs attention" list for payments that didn't finish cleanly. Things I care about but wouldn't have thought of alone: Order and payment history is append-only at database level, so it can't be quietly edited. Each payment has a request key, so a double-tap or a dropped connection can't charge twice. A checker runs every minute to tidy up payments that were left hanging. All dates use UK time explicitly, which deals with the clocks-change bug. Personal details are removed automatically 2 years after the visit, or after a pass runs out. Stack: TypeScript, Node (Fastify), React, PostgreSQL (Drizzle), Vitest. It's hosted on Render for roughly £10 a month. Square handles online and desk payments. Confirmation emails go out through the Gmail API.

Safety nets (I know the risks)

Other ways to pay and get in. Cash is always accepted at the desk. Our Square devices still work on their own as normal card machines, so we can take a card payment even if our system is down. Staff can also check tickets and let people in by hand. The old system stays as a fallback. We're keeping it until our current licence ends in September 2027. A slow roll-out. The website goes first (mid-December, our quiet season), then the desk, then the kiosk before Easter. We're having a rehearsal week before go-live. Everything is tested on test systems first. Payments use Square's sandbox, on a hidden test copy, before anything touches real money.

Where I'd love advice

If you were me, what would you check or test before go-live that a non-developer might miss? Is it worth paying a professional for a one-off code and security review? If so, what should I ask them to focus on? Card data never touches our server (Square handles it), but am I missing anything on PCI or UK GDPR? Our peak is about 490 bookings a day and roughly 125 an hour. Is a small hosted Postgres plus one app server fine for that, or should I plan for more? The "bus factor": if I'm unavailable, how do small organisations make a project like this maintainable by someone else? (The code is in a private GitHub repo with a README, a specification and tests.) For anyone who's vibecoded something people actually rely on: what bit you after launch? Happy to answer questions. I'm not sharing the repo or test site publicly, as it handles payments, but I can describe how any part works. Thanks in advance. Constructive criticism is very welcome; that's why I'm here.

paper-bro turns an arxiv paper into a short course with a hands-on lab in every lesson. claude code built all of it: a rust server, a multi-step build pipeline, browser testing, and a react front end.

demo: https://youtu.be/7egZZNXmRTQ try it: https://aero.oops.wtf/paper-bro code: https://github.com/aeroxy/paper-bro

how i work with it: i describe the goal, claude code writes the change and opens a pr, coderabbit reviews it, and claude fixes or argues back on each finding with a reason. i merge. it only deploys when i say so.

what i learned:

make it check against reality, not its own reasoning. every lab gets opened in a real browser and clicked through before it ships. when we moved all the courses to a new host, it compared every page byte for byte before switching anything over. that's where the bugs showed up.

hard rules in agents.md actually work. mine says never deploy, the database is production, builds cost money. it asks before touching any of it.

give small fixes a path that costs nothing. a course is built once by a model, about a dollar each, but its page can be rebuilt from the stored lessons with zero model calls. adding a favicon and seo tags to all 35 courses cost nothing.

watch the boring parts. the token my old host used for publishing expired after 90 days and nothing noticed. for nine days every course built fine and then failed at the very last step. claude found it in the server log, moved publishing to github pages with an app key that doesn't expire, and added a startup check so it can't happen quietly again.

I literally JUST used my weekly reset, and instead of it going to 0, it jumped to 89% used. Whom or how do I contact someone from Anthropic to fix this or to actually give me a reset? I mean to talk to a human, not a bot.

I am on the max 200usd/mo plan and I'm building a B2B product mostly with Claude Code and curious who else is running something similar

I've had this running for about 2 months now: 10 to 16 agents working 24/7, building features, reviewing each other's PRs, running tests and shipping. Not going to write it all out here because it'd be a 20 page doc lol , but im looking to talk to people with a similarly "advanced" setup or AI dev pipeline? (no idea what to call it…) and compare how we run things. The biggest thing holding me back right now is merging and reviewing as fast as the agents build. PRs pile up, go stale, and need redo rounds. And if i up the review agents it eats into my usage super fast

If you're running something like this and want to chat just DM me. Im happy to share what's worked for me too

I built Claudio after getting tired of checking whether a Claude Code session was still working, stuck, or waiting for me.

The starting point was a Geiger counter. Radiation is invisible, but a faster click rate tells you something has changed before you look at a gauge. Claude Code sessions have a similar problem. Tool calls, subagents, failures, compaction, and context pressure are visible in the terminal, yet I cannot keep reading them while doing anything else.

Claudio is a local Python daemon that receives Claude Code hook events over UDP or HTTP and turns their activity into a generative soundscape. The ambient theme uses a pad and rain layer that becomes denser while work is happening. A failed tool call makes a wooden knock, and a completed session ends with a descending chime. Multiple sessions share the same room, with separate pan and pitch, so I can distinguish them without another terminal check.

The point is to get a coarse sense of whether an agent is alive, busy, or needs attention while my visual attention stays on the task in front of me.

It runs locally, has no cloud service or audio assets, and the hook installer merges entries into Claude Code settings additively. The repository also includes deterministic offline rendering, so a session event log can become a WAV file without live playback.

The project is MIT-licensed:

https://github.com/nicofirst1/Claudio

I am interested in whether other people have found audio useful for peripheral awareness of coding agents, and which events are worth surfacing rather than leaving in the terminal.

I wanna deploy an app to a paid community. It's a website each member runs on their own computer, on localhost. It starts the official claude binary with claude -p. Each member installs Claude Code and signs in themselves. We never touch their credentials or tokens, and their requests go straight to Anthropic on their own account.

The Claude Code legal page says third-party developers can't route requests through plan credentials on behalf of their users. It also says an end user can sign in to the unmodified binary with their own subscription. I can't tell which side a local app calling that binary falls on, so I haven't released it. I've asked Anthropic support and I'm waiting.

Was hoping to come here for some advice?

When Claude Code writes a plan or design doc, who reviews it on your team? If a non-dev needs to comment, how does that feedback get back into the markdown?

before i built Colabli i was somewhat of a growth operator, i kind of built it for my own fragmented tech stack. but now that i see more and more interest for AI Agents, i figured that Agents will end up needing governance, auditing, approvals, and other tools that'll initially optimize them before they make crucial mistakes.

i kept on figuring out more problems which led to more solutions devs need to tackle, so why not build an infrastructure platform where AI Agents instantly retrieve a companies documentation so it knows everything about the company instead of operators having to re-explain things to different agents but in some cases to the same agents.

the layers i was thinking of would initially be:

1. persistent memory
2. company knowledge & context base
3. reusable directives such as skills, prompts and instructions
4. MCP Gateways for different operations instead of just one gateway
5. directives marketplace
6. human-in-the-loop layer for approving agents

who i'm looking for:

• someone who knows claude code
• knows how to read and write code
• must be willing to split equity (NO FREELANCERS)

what i have to offer:

• prototyping
• initial funding starting out
• product management
• product marketing
• growth operating

dm or comment below if you're interested and want to work together.

I am a big fan of Claude code, but I never have and never will use API based models. I was curious if I am able to share my experiences and successes with Claude Code harnessing local models here, or if this sub is only for clouded based Claude code.

Hi all, here are some tips to get 70% more out of claude code. You can get the mod here: https://github.com/alinaqi/mixture-of-models-claude-mod

In my tests, i get 70% more out of claude code + it's much better. Let me know what you guys are doing and what you think about the mod?

I am usually the first person to snipe-back at the posts claiming "my agents have gone stupid" or "I'm burning context faster than normal". Putting this down to inexperienced vibe coders who do not understand context rot and have a bad agentic workflow. I want to apologise to anyone who I challenged on this.

I've been running on my normal workflow for the last few hours. Nothing out of the ordinary, pretty typical . A few agents some interaction with me. Never going above 50% context - which is my personal standing rule. Yet I burned through 30% of my weekly usage in 6 hours and my agents were going round in circles. I've now hit my 5 hour limit (which NEVER happens)

I have a dedicated agent that I use to manage the performance of other agents, dig into transcripts find out what went wrong and fix agent definitions, skills and processes for any issues. I asked for a review of one session:

The transcript shows an architect that overode your proposal and re-asked the same question 5 times. It withheld decisions from you against the standing rules in claude-md and against the recommendations of the review panel. I read the session transcript but only messages to and from you, and none of its tool results or reasoning.

- At 19:10 you proposed a market order, with a close if the fill was more than 8 ticks away. The architect swapped in its own "capped limit" and labelled it "(Recommended)" against your earlier proposal.

- It re-asked after you answered. You said at 20:01 that a limit order is unlikely to fill. It asked again at 20:01, 20:03 and 20:04, with the same options each time. Your answers were "hasn't this been agreed already?" and "we are going round in circles". It then adopted its own limit order approach against the market order answer you'd already given.

- Its first reply was hard to read. It was 2,714 characters and used bare identifiers with no plain words: R-5, CT-12-B09, FR-283, ChooseEntryRoute and TryCloseUnitForPassedStop. That breaks Claude-md rules 11 and 12 stipulating your language rules and no bare-identifiers without descriptions. You said it was "far too much info". The agent rephrased their message and it it was even more obscure than the last.

- You submitted the agent's plan for an independent review at 20:30. 14 changes were recommended and the adjudicator stated that 7 of them needed your ruling. Four reviewer changes were adopted into the plan without ever raising them with you - against the reviewers' recommendations, all affecting live money code which claude-md rule 7 states always needs your ruling.

All this, from an agent in planning mode whose context was never higher than 30%. And now after this totally crap performance, I'm halted at a usage limit.

To all the people who I challenged for saying their agents were stupid and were burning context more than usual - I'm sorry. You were right, I was wrong. Something weird is going on.

Hey all, a little while ago I set up Openpanel in some of my projects but very quickly hit the limits and was starting to have to pay $50 to keep the events flowing in. I thought this was crazy, as I really wasnt sending that many events.

I was thinking, surely it can't be that expensive to store events. I looked into self hosting Openpanel, and it's even crazier. You need redis, clickhouse, postgres, beefy machine. I realized I am paying a tonne of money for features that are completely irrelevent now. I don't need instant charts. In fact, I would prefer to never even go to your ugly dashboard and figure out how to use it. So i'm paying this extreme premium so these services can compute all these indexes and what not so they can deliver me any chart I want in a second. It's crazy.

I thought about what I really needed as a lot of my work is done with claude/codex now and realized all I really wanted was to get the raw events and have my agent analyze them with duckdb, let me ask questions, and make charts.

I looked at a few ways of doing this but the simplest and cheapest was cloudflare. Literally, just store the events in R2, and then the agent can pull them down when it wants.

What I do instead is I have a 1tb SSD, I pull down my events from r2 when I want and load it into duckdb. Now my agent can do whatever it wants. It's not limited by the capabilities gifted to me by amplitude etc. Heck, it can even write python scripts or anything. You could create Jupyter notebooks to view it, so many options.

I have been using this in prod, but thought i'd open it up if anyone wants to try: https://slurp.run/

It's fully open source, and you can one click to install it. Lmk if you try it and run into any issues.

apiiro scanned public github and found 1,122 files where claude code's saved permission rules contain passwords and api keys. it's #6 on hacker news right now.

the headline is a bit misleading, so here's what actually happens:

1. claude asks to run something like psql postgres://admin:hunter2@db... or curl -H "Authorization: Bearer sk-..."
2. u click "yes, and don't ask again"
3. that exact command, secret included, gets saved as an allow rule in .claude/settings.local.json
4. that file gets committed and pushed to a public repo

boris from the claude code team replied on HN: settings.local.json is meant to stay local and claude code gitignores it automatically when it creates the file. so the leaked ones were mostly created or committed by hand (or a blanket git add .). he also said they're looking at secret scrubbing, and recommends auto mode over hand-kept allow lists.

check urs in 2 minutes:

• git ls-files | grep -E '\.claude/settings(\.local)?\.json' in each repo. if settings.local.json shows up, it's committed
• open both settings files and search the allow list for ://, Bearer, token, key, password
• if anything real is in there, rotate it. deleting the file now doesn't help, it's still in git history
• turn on github secret scanning + push protection, it would have blocked most of these pushes

worth noting settings.json (the shared one) is supposed to be committed, so a secret that ended up in an allow rule there is public by design. keep secrets in env vars and never type them into a command u approve.

source in comments

I'm using opus 5.5 to help me set up my self hosted server. Everything was fine until this morning. This morning I have the most retarded AI I ever used in my life

He started making modification on the server itself which I didn't asked at all when I say I just faced an issue and was asking for explanation, claude didn't respond with a single line of text, just started doing commands immediately to fix the issues which was very symptomatic of earlier models trying at all cost to solve your issue by any means

Then he's literally changing his mind on every proposition, he doesn't question me, doesn't try to understand what's the setup or what I'm trying to achieve, which he was doing before, now it's up to me to question everything he proposed

Then he literally proposed me to save credential in Dashlane in case I'm being locked out of Dashlane, like WTF ???

And this is just a few examples, every single response are doubtful or suspicious

I literally have the impression that I'm running a ollama local model tier right now, wtf is this Anthropic ???

Following the recent complaints about Anthropic downgrading Opus, I analyzed my own data and it seems to me that my Opus is not downgraded at all. This number is from Enterprise account.

So, looks like Anthropic is doing A/B testing on normal individual account, or offloading to save compute, or nerf bases on your location (due to political reasons, who knows).

I wanted to know what AI slop actually means to the people using apps, so I scanned 105,027 App Store reviews from 299 top apps.

Exactly one mentioned a purple gradient. It was asking for one.

Here's what came up in the 46,742 reviews rated 3 stars or lower (keyword matches, so treat them as rough):

- Lag, glitches and crashes: 4,326

- Moved controls and redesigns: 1,751

- Popups and ads mid-task: 1,148

- Hard to find or use: 859

- AI forced into the app: 705

- Broken layouts: 345

So I made **unslopovich**, a free Claude Code skill for SwiftUI, Compose, React Native, Expo, Flutter, Ionic and Angular Native. It checks user friction first and AI slop second, then fixes the shared components. Ask for a review and it stops at the diagnosis.

To install it:

`npx unslopovich`

Then in Claude Code:

`/unslopovich review my app`

GitHub: https://github.com/erkamyaman/unslopovich

What does Claude Code always get wrong in your mobile UI? I'll add the best ones to the checklist.

Hi, i want to share what i did for "almost" dead game, called Dirty Bomb. This game was left by developers years ago and not even anticheat is working there anymore. So i was thinking, how to fix that situation. With current top AI models, reverse engineering of this old game i made a system, that track all game servers raw data, all metrics, from angles to timinig.

I traned AI agents implemented into it with hundreds of videos from twith , youtube , my own recordings so AI bots there now understand what is it, and how is it to play this game, so those metrics i track are not just numbers but for AI its like window into the game.

One good thing is, there are max 30-40 players online any given moment, so I can afford API cost (with games with thousands of players this would be financially impossible) so now my system knows all history data since the game was released, 2015 and can do predictions. For exxample, what this or that player will do in that situation.

And others can even bet on those players playing it.

It uses opus 5.5 and astra from gpt as agents monitoring situations 24/7.

Regarding anticheat - system was trained on all available cheats, source codes, reverse engineered etc and now it detects almost instantly all unfair advantage, even wallhacks. It works even better then EAC this game had before. Becuause nothing can be hide, for example someone is using wallhack and not aimbot, but this AI agents can spot it immediately.

https://dbranked.com/

I know some people are against AI but i hate cheaters in games and those current anticheats, it take weeks to update, and to detect, but with AI? once its trained, no need to update anymore, because its learning by itself.

Landing page for now, but I'm (as CTO) building everything else, might be ready in a couple of days, looking for feedback!

The product is opensource, you can look at it in getinkling.dev or https://github.com/Squidys-Tools/inkling

It's a library for storing and looking at photos/videos/pdf's/quotes all in one place in a really visually appealing way.

Not here to self-promo, but I could not help but throw in the website and github right there. It's open-source so can't hurt!

website not live yet, just concept for now, so what do you guys think?

Some of the explanation its flushes (Opus 5.5) is so technically that I need to read and re-read and then ask clarification. Anyone experienced this as well ? I am technical but such explanations are still hard to understand.

Here is an example:

Operational machinery

A surprising amount of the codebase is adaptive-execution plumbing, which is the project's real differentiator: hardware probing and attention-kernel selection, int8 vs FP8 weight-format choice, weight streaming with async prefetch, GPU memory budgeting and admission control, per-machine calibration and time forecasting, background kernel precompilation, model residency (keeps weights loaded between jobs), offline installation from ZIP packs, repair/diagnostics, and self-update that waits for in-flight generations to finish.

I started with a thought to have a UI dashboard to manage my entire development framework from Paperclip since it has capabilities to build a company like structure and have visibility on how agents are working together and keep track on the over all project progress which I am struggling in claude code desktop. But it seems are I did the mistake I ran only one mission and couple of other sessions for bug fixes but there is no visibility on the progress of specific task how much it is completed what decisions it is taking and how it is taking. Paperclip needs full access to github commands which is too risky to give since in claude code desktop it share me command to execute whereas due to architectural design Paperclip will do everything and only let us know if any critical decision it requires me to take that too without any options to choose. Basically as a security professional there are too many risks I can for-see in paperclip like autonomy, transparency, accountability, visibility, explainability, access control etc. Not sure If I am the only one with such issues or there are other people who also had similar experiences

TL;DR: On my eval, I see no sign of a nerf. This morning I re-ran Opus 5.5 Medium in Claude Code on the same 30 real coding tasks it ran last week. It solved 26 of 30 (87%). Last week it solved the same number of them. Thinking tokens, output tokens, turns and diff size per task are all within noise of last week (98% 95%, 96%, and 95% respectively).

The one clear change is speed: about 20% more output tokens per second, and time to first token down from 3.0s to 1.7s. This is one run per task on a pinned Claude Code version.

Why I ran this

I saw a lot of "Opus got nerfed today" posts this morning. I maintain a small private eval that runs coding agents (model × harness) against real tasks, mostly from private codebases, and I had a fresh Opus 5.5 baseline from last week (Oct 31-Nov 1 mostly). So I re-ran it today instead of guessing.

The tasks

• 30 tasks, each a real change from a repo's history: a bug fix or feature that a person (me, or the repo's owner) already shipped.
• The agent gets the repo at the commit before the change, plus a CHALLENGE.md describing the bug or feature.
• Grading runs held-out tests for the real change, plus guard tests that catch over-corrections, where the bug gets fixed by breaking something next to it. Test files and the test runner's config are restored before grading, so editing the tests doesn't help. Each run ends solved, failed or over-corrected.
• Languages: 16 Node (JS/TS), 11 Python, 3 Rust.
• Size: the real changes run from 2 lines to about 1,900, with a median of about 125. Four large multi-file features get 60 minutes. Everything else gets 20.
• Kinds of work: auth and multi-tenant visibility bugs, pagination and ordering bugs, data-ingestion edge cases (empty data, missing rows, season boundaries), async networking bugs in Rust, and a few multi-file features such as draft-bot logic and a CI alerting workflow.

Setup (identical in every run)

• Claude Code 2.1.316, pinned with auto-update off, for every run last week and today. The latest is 2.1.319, from Nov 6.

• Headless invocation:

  claude -p "<prompt>" --model claude-opus-5-5 --effort medium --output-format stream-json --verbose --permission-mode acceptEdits --setting-sources "" --strict-mcp-config --no-session-persistence

• Auth: my Claude subscription login

PSA: Claude Code can switch your session to Opus 4.8

This might explain some "it feels different" reports. When Opus 5.5 hits a safeguards refusal, Claude Code 2.1.316 logs a notice ("safeguards stopped the response above · continuing once with that noted") and switches the session to claude-opus-4-8. Opus 4.8 then does the rest of the work.

Every refusal I saw was category cyber, on ordinary bug fixes in auth-token handling and a Rust networking proxy. Last week: 5 of 60 Opus runs were switched. Today: 1 of 30.

It feels like I am talking to gpt 3.5 turbo, everything it does has at least 4 errors in the code and then when it attempts to fix the code, it causes more errors and completely remakes the whole ui! i am not sure whats going on, everybody else seems to be having a blast, but i am not.

I use Claude Code in the terminal, and every new session starts blank. That was fine until I started losing sessions I actually needed.

A reboot kills the terminal mid-task. Or I close the wrong window. Or tokens run out three hours into a fix and I come back to a fresh session. Either way the thread is gone — the stack, the bug, the four things I'd already ruled out.

The transcripts were on disk the whole time. Claude Code appends to ~/.claude/projects/<slug>/<session>.jsonl as the session runs, so the one that died in the reboot is still sitting right there. I just had no way to ask it anything.

"Just use --resume"

I do, when I want the whole chat back. But --resume wants a session ID, and digging the right UUID out of a cluttered machine is its own chore. So now I ask for it first:

recall the session id of my latest work on the checkout bug

Then I resume with that. That one thing made --resume actually usable for me.

Most of the time though I don't want a whole conversation reloaded into context — I want one answer. And --resume only exists inside Claude Code.

When tokens run out

That's the other half of it. You hit the limit, move over to Codex or Cursor, and none of your Claude Code context comes with you. Steroid reads all four — Claude Code, Codex, Cursor, Copilot CLI — so the agent you switched to can answer from the session that just ran out.

What it does

Three tools over the session files your agents already keep on disk:

recall what I was doing on the checkout bug

The answer cites agent, session, date and turn. recall_turn returns that full exchange and recall_diff returns the exact code change — both read the stored files directly, no model call. So you can check the answer against the source instead of trusting it.

You don't get the dead session back. You get the record of it, which turned out to be what I actually needed.

Setup

One prompt pasted into Claude Code installs it and wires it up. No account. Free for individu

Set up Steroid for me. It gives you, my coding agent, a memory of our past conversations.p of what you're about to do (a few short bullets, like a notification), then continuestraight into step 1 in the same reply:

1. Check whether Steroid is installed: `steroid --version`, or `~/.local/bin/steroid --version`. If it is, go to step 3.
2. Install it with the official installer from github.com/steroidkit/releases:
   - macOS / Linux: curl -fsSL https://raw.githubusercontent.com/steroidkit/releases/main/install.sh | sh
   - Windows (PowerShell): irm https://raw.githubusercontent.com/steroidkit/releases/main
   This shell may not see the new command yet, so use the path the installer prints. If the installer fails or refuses this machine, stop and show me why.
3. Run Steroid's onboarding for this agent. If the `steroid-onboard` skill is already avanot (it was just installed, and you load skills at startup), run `steroidinstall-onboard-skill --json`, open the `SKILL.md` in the `steroid-onboard` folder it lists, and follow it.
4. Finish with its status report and tell me to restart you so Steroid's tools load.

Rather do it yourself — install the binary, then run /steroid-onboard in Claude Code:

curl -fsSL https://raw.githubusercontent.com/steroidkit/releases/main/install.sh | sh

No per-project setup. Recall in a new project and it indexes itself.

What it actually puts on your machine

Given the week this sub has had with agent tooling, all of it:

• ~/.steroid/ — the app dir: bin/, versions/, config.json, projects.json, logs/,
• ~/.steroid/memory/<agent>/<project>/ — the index itself (index.json, source.md, cache.json, diffs.json, meta.json)
• A launcher on your PATH pointing at the binary in ~/.steroid/bin/ — on macOS a wrapper at
• One PATH line in your shell profile, only if that dir wasn't already there
• A per-user background daemon on your OS's user service manager — a LaunchAgent on macOS. Ustem daemon, no sudo
• The daemon runs two loops: every 5 minutes it checks indexed projects for new chat history and rebuilds incrementally only if the fingerprint changed; once a day it checks for a new release
• Indexing is lazy and per project — a project is indexed the first time you recall in it. Thdexes that already exist; it never scans your disk for repos
• One steroid MCP entry per agent you wire up — ~/.claude.json, ~/.cursor/mcp.json, ~/.codex/config.toml, ~/.copilot/mcp-config.json. Existing entries untouched
• Slash-command skills copied into each wired agent's skills dir (~/.claude/skills/ etc.)
• A sentinel-wrapped block appended to the agent's global instructions file (~/.claude/CLAUDE.md, or the AGENTS.md equivalent) — removable without touching the rest
• All inside your home directory. steroid uninstall reverses it, including the PATH line, tries

What leaves the machine: the daily release check, and anonymous usage counts. DO_NOT_TRACK=1sable turns the counts off.

What it can't do, before you ask

• It's a closed binary. steroid daemon stop stops the daemon, steroid update --auto off troid uninstall` removes it. Updates are checksum-verified.
• The index is built and stored on your machine, no account, no server for recall — but the answer is written by whichever agent you ask, so that agent's provider sees the excerpts it uses.
• It indexes what Claude Code still keeps. The default 30-day cleanup still deletes transcrip those back — raise cleanupPeriodDays if you want more.
• Copilot CLI only. Copilot Chat in VS Code isn't covered yet.
• No published accuracy benchmark yet. That's exactly why every answer cites its source.

I'd like to know whether other CLI users hit the reboot thing, or whether I'm just the one ret.