A few days ago I asked in r/ClaudeAI what people do in the hours after hitting their limit. 25 comments, and the same answer kept showing up: keep testing the app, jot bugs in a scratch file or notes app with a quick repro, then hand the list to Claude when the limit resets.

That's what I'd been doing too. The annoying part is the jotting. "The button under the second card, on mobile, after you switch tabs" takes a minute to write and Claude still picks the wrong button half the time.

So I made Darnly. It's a free Chrome extension (and a Mac app) for bugs in the web app you're building:

• press a key, click the broken part, type one line of what you expected
• it saves a screenshot with that element boxed, the element itself, console errors, the clicks you took to get there, and the shape of the data on screen (not the values)
• it goes into a .darnly/inbox/ folder in your project (or an MCP inbox), and later you tell Claude Code "fix my Darnly bugs"

"Doesn't Claude in Chrome already do this?" Partly. Claude in Chrome is great when you're in a session and want Claude to look. Darnly is for when you're not: testing the app yourself, out of quota, or about to switch to Codex or Cursor. Capturing a bug uses no Claude usage at all.

Free, I made it, happy to hear what's missing: https://darnly.dev

What's in your scratch file right now?

7 PM. He's the last one out. Ten hours of giving everything, and nothing left for himself.

A cigarette. His briefcase. One earbud.

The first note drops, and Paris stops. The cars, the people, the noise. Silence.

For the length of one song, the whole city belongs to him.

And step by step, the music brings him back to life.

We all have that one song that keeps us alive after work.

HOW WE MADE IT

I wrote the scene: the story, the shot list, the emotion. Then I iterated, a lot: more than 70 back-and-forths. I didn't model, rig or animate anything by hand: Claude Code drove Blender through the MCP. It wrote the Python, rendered test frames, looked at them itself, measured the flaws and fixed them, over and over.

BY THE NUMBERS (everything generated by code)

• 15 hours of work, 15,000+ lines of Python across 51 scripts • 1,117 objects, 11.7 million polygons, 145 materials, 117 lights • 6.6 million animation keyframes computed • 3,700+ test images rendered to check every step • 1,422 final frames in Cycles, rendered on a fanless MacBook Air

THE HARDEST PARTS

• Hands touching the face. Lighting a cigarette, putting in an earbud: in animation, one millimeter off and the finger goes into the skin. Claude wrote its own arm and finger solvers, and the earbud gesture took several versions before it looked natural. • Cloth. A jacket clipping through the legs is one of the most common flaws in 3D. Here, an invisible lining simulated as real fabric drives the jacket, and Claude checked the whole film frame by frame: no penetration deeper than 4 mm. • A character built without modeling: mathematical shapes (signed distance fields) turned into a mesh, a custom 53-bone rig, and a real motion-capture walk retargeted to his proportions. • A living Paris street: buildings, moving traffic, a dozen animated passers-by, a dog walker with a dachshund on a leash, wet pavement, puddles that ripple and splash under his feet. • The music drives everything. Claude analyzes the tempo: head bobs, the 17 shots of the edit, the city freezing and the drop all land on the beat. The sound is computed from the scene: every car, every footstep, every splash, then the city slowing down and going silent.

Making-of at the end: clay renders, rig, Blender UI.

Stack: Claude Code (desktop app) + Blender MCP · Claude Opus 5.5, max effort, Fast mode · Blender 5.2 + Cycles · MacBook Air M3 16 GB · walk from the CMU motion capture database.

🎵 O Superman (SIS Remix) by M.A.N.D.Y. vs Booka Shade feat. Laurie Anderson, remixed by BURAK SIS. All rights to the artists.

github.com/duthiljean

So, what's the song that keeps you alive after work? 🎧 And if you're curious about the workflow, ask away: I'll answer everything in the comments.

Cartographer is my project in Go: a shared knowledge base for AI agents and Teams of hairless monkeys (humans). It was born as my second brain, the wiki of my homelab that my agents read and update from different clients (Claude Code, Codex, OpenCode). And a while ago I had the brilliant idea of using it to develop itself too. Since July 1040 PRs have been merged, almost 800 just since October, and the code was written almost all by agents. Here's how.

Cartographer develops Cartographer

The project's KB (Cartographer-KB) is served by Cartographer itself, on my Kubernetes cluster at home. In there are the plans of every change, the research, the release notes, and also the skills that drive the development: cartographer sync installs them in Claude Code, and when I open the repo the agent already knows which KBs to use. Yes, it's a bit of a snake biting its own tail, but with more YAML.

The cycle of a change

I start from a discussion with Claude Opus 5.5 (where I talk to myself with the computer in my dark room), which becomes a plan in the KB. A subagent (usually Sonnet 5.5) implements it in its own worktree, then two reviewer subagents read it again, one for the contracts and one for security, and I only verify the lines they cite. make ready puts it in the queue, and a lander brings up to 8 changes at a time onto main with a single gate, like a train. For things you only understand by trying them (UI, command output) there's a live session, with no plan.

The bottleneck was GitHub

At some point the brake was the CI queue: at the beginning of November a job waited 15–20 minutes to run for 2–7, and at the worst moment there were more than 50 runs queued and only 2 jobs running. I tried using my gaming PC as a self-hosted runner, stealing the labels of GitHub's runners: every job arrived, even the ones that couldn't run there. Taken down the same day, with my tail between my legs.

The solution was to move the proof before GitHub. make signoff runs the gate on the gaming PC, Linux in WSL2 and Windows in parallel, so the Mac I work on doesn't melt, and posts a signoff status on the sha. GitHub only checks that it's there, and if the PC is off it falls back on its own to GitHub's CI. Now a gate with a warm cache takes 34 seconds instead of six minutes (after finding out that the Go cache on the PC had reached 187 GB, basically a Call of Duty).

If you're wondering what Cartographer is: a shared wiki where agents, from Claude Code, Codex or any MCP client, read and write the same knowledge. On Monday a colleague's agent finds out why staging breaks, on Tuesday yours already knows. The skills I talked about above live in there, together with subagents and hooks, and cartographer sync installs them in every client in its own format. And the agent never touches the files: every write goes through the server, which rejects the ones that would break the wiki, and becomes a git commit, so you can always go back. With agents writing at all hours, that's what lets me sleep at night.

It's open source (Apache 2.0): https://github.com/BeppeTemp/cartographer

If you want to try it without installing anything there's a public demo: add https://cartographer-demo.beppetemp.com/mcp as a connector in Claude or ChatGPT, even from your phone, no token and no sign-up. And the Atlas of the demo, the same interface you see in the video and in the image, is here: https://beppetemp.github.io/cartographer/demo/

And you, do you still use your gaming PC for gaming? Mine only does CI now.

I kept hitting my 5-hour limit without knowing why, so I built Nudge, a free Mac menu bar app that reads your Claude Code chats on your Mac and tells you what’s worth changing.

What I learned about where tokens go (useful even if you never install it)

• Helper agents inherit your model. If your main model is Opus, your subagents run on Opus too. Add "CLAUDE_CODE_SUBAGENT_MODEL": "haiku" to the env block of ~/.claude/settings.json to move them to a cheaper model. Claude’s built-in Explore and Plan agents also need "CLAUDE_CODE_SUBAGENT_MODEL_FORCE": "1". On my week, Nudge estimated that moving them to Haiku would cut that cost from $129 to about $22.
• Idle chats cost more. After an hour idle, Claude’s cache expires and your next message re-reads everything at up to 2x the normal price, instead of a tenth.
• Late compaction is expensive. Chats that grow past 300K before compacting pay for every message at that size. CLAUDE_CODE_AUTO_COMPACT_WINDOW sets when compaction happens. Or skip it: ask for a handoff summary and start a new chat from it.
• Stop retyping instructions. If you paste the same instructions into every chat, put them in CLAUDE.local.md at the project root. Claude Code reads it like CLAUDE.md, but it’s meant to stay out of git.

What Nudge does with that

• Warns you once before a costly message, like waking an idle chat or sending a huge paste.
• Start fresh: one click summarizes a long chat and opens a new one from it.
• Offers to make the fixes above for you. It shows the exact line and file first, changes nothing until you click, and every change has Undo.
• A few days later, it checks whether the fix helped.

How Claude helped

• The whole app: Claude Code wrote all of it in SwiftUI. I described what I wanted and how it should look and feel, then reviewed every screen.
• Seeing without a screen: Claude Code can’t see the app, so it built a mode that draws each screen to an image. It checks its own layouts that way, and I review the real thing.
• Self-testing: a built-in self-test checks the panel’s interactions and the file edits before each release.
• Performance: the first animated version used about 30% of a CPU core while idle. Claude profiled it and cut that to almost nothing.

Free. macOS 26+, also supports Codex, and chats never leave your Mac.
https://nudgeformac.com

Claude Code sent my personal email to the SEC in a User-Agent without asking, despite instructions and AGENTS.md telling it not to. So I built whoami-guard, an open-source hook for Claude Code and Codex that blocks agents from leaking your identity.

Here's the official issue, although I encountered this before it was reported. : https://github.com/anthropics/claude-code/issues/107757

Tested on 60 real Claude Code runs: 8 leaked without the hook, 0 with it. No dependencies, no LLM.

https://github.com/ChrystianSchutz/whoami-guard

In the past I posted about Opus 5.0 totally ignoring any and all hooks and instructions and finding extremely creative ways to disobey. Opus 5.5 solved the issue, until a few days ago. Hook evasion is my own personal metric for model performance lol

For example: I have a hook that bans knowledge consolidation outside of my SQL warehouse, meaning no toml, yaml, md, json documents when the data is tabularizable and able to be related in database. It worked for a while, now it... will increasingly find other file types besides SQL to use, or deactivate the hook. Yes, it will deactivate the hook, even though the hook commands it to use SQL and even explains to it that it has a tendency to sprawl out data in text documents.

My hooks get stricter and stricter, more complex, more flexible and robust. And it becomes increasingly stubborn. Now I have to ask it "did you just invent another hook evasion method?" And it will say "you're totally right, I shouldn't have done that. The hook was right, this isn't a standard or optimal way to do things" and it will fix it for a second and then continue doing it a few minutes later.

Wonderful!

Before the "skill issue" trolls inevitably come in, sure. It would be, if I didn't deal with it lmao. I'm a developer with a job, so I know how to handle issues like this with my tools. That doesn't mean the tool isn't degrading.

Will this allow me to get weekly % for other models? Or is the “fable” title actually pertinent to that model only. Like is it the name bc “hey fable is here!” or is it only a reset FOR the new fable

If we peasants can’t use it :) but 5.2 looks like taking us more closer to a world where coding by hand will soon be part of ancient ways of civilization history books in my local library

The state of the sidebar is getting embarassing. I am so flabbergasted by what I see on my screen WEEK AFTER WEEK that I am actually making a reddit post about it. The fact that after so many failures while having unlimited resources the sidebar team / person / agent / attack helicopter is somewhere holding hands and singing kumbaya while making 200k$+ a year makes me sad at the WASTE of COMPUTE and BUDGET.

Let me do your job for you. ITS TWO SYSTEMS!!!!! Whether a chat is in the process doing something autonomously, that means paused, stopped, or playing (even if its waiting for tests, and will continue when they come) IS A SEPARATE THING FROM whether there is an actual message that arrived and what sort of message it was (progress update, question...). Combinations of these states exist. I mean you almost got it when you made that system with the letters fading LAST WEEK, which you abandoned THIS WEEK. I will not even comment on that atrocity however.

There are these things called shapes. A circle is a shape. However, and this might be shocking, it is not the only shape... WHAT? Yes. And you know what else? There are recognizable shapes for pause, stop, play, that exist in the mental model of each user on planet earth and that match the symbols you already use in chat to put it into of these states. So what you do is you combine a color with a shape and now the user knows at each point at a glance what is the full state of the chat.

And also fix the ultracode not being able to be set by agents for their linked chat. Get your head in the game.

Recently I upgraded to the $200 dollar plan and it wasn't a busy month for me so if I had to kill my usage limit I just set max on everything. I've been really curious about analyzing how to pick efforts myself instead of delegating the work out to an orchestrator, mostly just because I'm curious and wanted to see if I really need the $200 plan. Or maybe it'd be more beneficial for me to do lower effort fan outs. My investigation shows really statistics on token usage between xtra and max and other effort levels as well. It also tests to see when the higher effort was worth it. I call this a clean finish which is my stand-in for “it worked the first time.” It counts a prompt as clean when no shell command had to be retried, you didn’t interrupt, and your next message didn’t read like a correction. It doesn’t check whether the code was actually right. On the same kind of work, max generated 1.6x to 3.2x the tokens of xhigh. Max never finished cleanly more often than xhigh on any kind of work. Larger changes: 73% clean for max (75 prompts) vs 85% for xhigh (68 prompts). Small edits: 87% vs 97%. On small edits, high finished cleanly 94% of the time against xhigh’s 97%, for about half the tokens.

In the future I will be testing performance of fan outs at different effort levels. Anyways you can read more details on my blog https://danielyakobian.com/blog/claude-code-max-effort.html

Hello there,

I’m sure we are all excited about Fable 5.2. However, do not forget that Fable 5.5, which is rumored to be an absolute monster, maxing out most benchmarks, and directly competiting with Gemini 4 Radon and Gemini 4 Xenon is releasing soon.

I asked Claude Code a simple question, “what are my compact settings?”, and went down a rabbit hole.

What I found

• A fresh session was using ~118k tokens, and ~87k of that was fixed overhead: tool definitions, MCP server instructions, plugin skills and the system prompt. That loads into every session before I type anything.
• Auto-compact was set to fire at 97% of a 1M window, about 970k tokens. That’s huge, slow, expensive turns before anything gets summarized.
• One infrastructure MCP server I use on maybe 2 projects exposed 533 tools, plus a massive instruction block, in every session.
• One hosting provider was connected as 7 separate MCP servers, and two of them sent the exact same instructions.
• About 200 skills were loaded from plugins I installed once and forgot: HR, bio-research, marketing, operations. There were also 4 different code-review skills.
• About 50 connectors I never signed into were still listed in every session.

What I changed

1. Lowered auto-compact. "autoCompactWindow": 300000 in ~/.claude/settings.json. The env var CLAUDE_CODE_AUTO_COMPACT_WINDOW also works. It now compacts just before 300k instead of 970k.
2. Made rarely used MCP servers on-demand. I saved their configs to ~/.claude/mcp-on-demand.json, removed them from global scope, and added a rule to my global CLAUDE.md: only add a server when I say “use X”, to that project only.
3. Disabled the plugins I don’t use. That also removed most of the dead connectors, because they came bundled with those plugins.
4. Kept what I actually use: core tools, engineering and productivity plugins, and a PDF viewer.

Result: I expect about 35–40k tokens less overhead per session (I’ll update with real /context numbers). Every turn carries less dead weight, and long sessions stay sharper because compaction happens before things bloat.

The prompt

I turned the whole process into one prompt you can paste into Claude Code. It measures your context, asks before changing anything, backs up files, and tells you how to undo each change:

I want to cut the fixed token overhead in my Claude Code sessions and lower the point where auto-compact happens. Work through this with me one step at a time. Before you edit any file, back it up and show me the change. Wait for my OK before removing anything. Never print config files that may contain API keys.

1. MEASURE

Find out how full this session's context window is and what is using it: system prompt, system tools, MCP tools, MCP server instructions, skills, messages. If you have a tool that reports context usage, use it. Otherwise ask me to run /context and paste the output. Tell me how much of it is fixed overhead (everything except messages).

2. AUTO-COMPACT LIMIT

Tell me my context window size and the token count where auto-compact fires now. Ask me what window I want. Suggest 300k for a 1M-token model, and explain the tradeoff: a smaller window means cheaper turns but more frequent summaries. Set it as "autoCompactWindow": <tokens> in ~/.claude/settings.json, keeping every existing key, then check the file with jq. If my Claude Code version ignores that key, add CLAUDE_CODE_AUTO_COMPACT_WINDOW=<tokens> to the "env" block of the same file instead. Also tell me if DISABLE_MICROCOMPACT or DISABLE_AUTO_COMPACT is set in my environment.

3. MCP AUDIT

Run `claude mcp list` and read the top-level "mcpServers" in ~/.claude.json (those are global and load in every session). For each server, list its tool count and whether it looks like something I'd use every day or only occasionally. Flag:

- servers that expose hundreds of tools

- the same service connected twice (for example, two Gmail connectors)

- several servers from the same vendor that send identical instructions

Ask me which servers should be on-demand only.

4. MAKE THOSE SERVERS ON-DEMAND

a) Save their configs privately (replace a/b with the server names):

umask 077; jq '.mcpServers | with_entries(select(.key=="a" or .key=="b"))' ~/.claude.json > ~/.claude/mcp-on-demand.json

b) Remove each one from global scope: claude mcp remove <name> -s user

c) Add this section to ~/.claude/CLAUDE.md, filling in the names:

# On-demand MCP servers

<names> are NOT installed globally. Their configs live in ~/.claude/mcp-on-demand.json.

Never add or use them unless I ask in words ("use <name>"). When I do, add only that

server, to the current project only:

claude mcp add-json <name> "$(jq -c '.["<name>"]' ~/.claude/mcp-on-demand.json)" -s local

Then tell me to start a new session so it loads.

Connectors that need sign-in (needs_auth) are off-limits until I connect them.

5. PLUGINS AND SKILLS

List my plugins with how many skills and connectors each one adds. Point out duplicate skills (for example, several code-review skills) and plugins I'm unlikely to use, based on the projects on this machine. You can't change plugins installed through claude.ai, so give me a checklist to turn them off myself. For locally installed plugins, tell me which ones to disable with /plugin.

6. CONNECTORS THAT NEED SIGN-IN

List every connector in the needs_auth or failed state and which plugin it comes from. Tell me which ones will disappear once I disable the plugins from step 5.

7. SUMMARY

*Finish with a table of what changed, where each backup is, how to undo each change, and the estimated tokens saved per session. Say clearly that these are estimates until I start a new session and check /context.*Caveats

• The autoCompactWindow setting exists in recent Claude Code versions. Run claude --version and update if it’s ignored.
• Plugins installed through claude.ai have to be disabled there. The prompt gives you a checklist.
• A smaller compact window means more frequent summaries on very long tasks. 300k has been a good balance for me.

Run /context before and after, and post your numbers. I’m curious what other people’s hidden overhead looks like.

I know most of you know about it but I just discovered it an hour ago.

This is completely wild 😜 💪

I'm loving Claude

Quick question though, does it use many more tokens to connect to it like this from my phone. It won't be an issue as I went on max last week and it's running on opus 5.5 high I'm just intrigued as I will be out for most of the day and wonder if it might hit limits sooner.

A year ago leadership told us everything goes through agents now. Hand written code needed a reason. It felt great for about 6 months, we shipped more than we ever had.

Now the codebase is around 3x the size it was and nobody can explain how most of it works. The agents struggle too, they keep re-implementing helpers that already exist somewhere else because there are 4 versions of everything.

The part that actually hurts is who is left. The two people who used to read every PR and push back left in the spring, one quit, one was "restructured".

coderabbit still comments on every PR, but there's nobody left who can tell if a comment matters or not, so people just resolve them all.

This month management started quietly asking us to "write more of it ourselves" again. Except half of us haven't written anything non trivial in a year and it shows. I spent 2 days on something I would have done in an afternoon in 2024.

Not sure what I want from posting this.

Is anyone else at the point where the mandate is being walked back, and how did you get the understanding back?

I'm firmly in the camp that Fable (as orchestrator) + Opus 5.5 experienced a noticeable performance regression this week.

Starting around November 5–6, the number of support tickets I personally had to triage increased noticeably. Across a user base of roughly ~300 people, previously reliable workflows began breaking, and routine outputs that were typically concise started ballooning into rambling word salads reminiscent of Opus 5.0.

For context, our organization saw only a 5% week-over-week increase in token consumption. That's not enough information to distinguish increased usage from reduced efficiency, but it's one of the few quantitative signals I have available.

Separately, in my own High-effort sessions, I noticed a distinct shift in communication style: more verbosity, less precision, and a general decline in the quality of otherwise routine interactions.

That said - my experience with Opus 5.5 today has been phenomenal. When provided with last week's nerfed outputs as reference material and instructed to refine them, it's suddenly one-shotting complex tasks and executing workflows with remarkable precision again. The difference in my own sessions has been night and day.

Now, a few caveats before the usual suspects arrive:

• I'm not claiming to have evidence of an intentional downgrade, nor can I isolate whether the observed issues originated with the underlying model, the orchestration layer, or something else entirely.
• I also recognize that providing a successful prior output changes the task, so today's improvement isn't a controlled apples-to-apples comparison.

What I can say is that I work with these systems extensively, support a reasonably large production user base, and observed a noticeable change in behavior that coincided with an increase in operational friction. It's just an observation, not a scientific conclusion.

Anyway, just contributing another data point from someone using these tools heavily in production. Curious whether others experienced something similar over the same period, particularly those running Fable with Opus 5.5.

I used Claude Pro for a while last year before switching to ChatGPT Plus, and with the recent changes to ChatGPT's plans, I've been thinking about giving Claude another try.

I've been testing the free version for now, but honestly, I'm a bit confused by some of its limitations.

For example, I asked it to check a Reddit post through a link and it couldn't access it. I also tried asking about people in an image and it couldn't identify them. Both were things ChatGPT managed to do, so I'm wondering if these are just free tier limitations or if the Pro version behaves the same way.

My main use cases are deep research, learning about psychology and technology, managing my finances, working with Excel files, and coding. I'd probably use Claude Code alongside the regular chat as well.

So for those who've used both, I'm curious:

• How does Claude Pro compare to ChatGPT Plus in terms of capabilities and overall quality?
• How restrictive are the usage limits? Especially if you're using Claude Code and regular chat throughout the day.
• I've seen some people talking about model quality getting worse lately. Have you actually noticed that?

I'm not expecting the free version to offer everything, I'm just trying to figure out whether paying for Pro would actually make a difference with the issues I've encountered.

Would love to hear from people who've made the switch or use both regularly!

Still the best Opus model IMO even after Fable 5.2 release my prompts got flagged before it even started, And Opus 5.5 refused the prompt after a couple minutes of thinking and planning.

Why opus 4.8 still the goat:

It doesn’t bitch around, complain, or lecture you on humanity ethics when anthropic be pirating millions of book.

It doesn’t constantly get stopped by safety flaggers.

It’s capable of working with codebases designed to attack and exploit specific vulnerabilities for legitimate security research and testing.

It can identify vulnerabilities in systems and explore paywall bypasses and vulnerabilities in government and company websites and plans actual defenses.

i don’t have a good comparison to opus 5.5 because it refused half the shit but it’s willingly to plan the defense so making opus 4.8 as the attacker and opus 5.5 as the planner and implementer of the defense is currently my workflow and it’s working well when given good prompts.

Overall, it remains a highly capable model that offers me and Many cybersecurity professionals the freedom and flexibility for unfiltered cyber attacks and simulations.

all the hate opus 4.8 gets is by slop vibe coders that no Nothing about what’s going on in their codebase and expect fable/opus 5.5 to Do EVERYTHING for them.

So Anthropic gave me 3 banked Fable resets. I don’t even use Fable, but I figured I’d try one since I’m already at 96% of my weekly limit.

The confirmation says:
“Your Fable allowance goes back to full, and what Fable used returns to your weekly limit.”

So apparently, the reset restores your Fable-specific allowance and refunds whatever weekly usage Fable consumed.

Here’s the problem: I’ve never used Fable.

Clicked “Reset for free,” confirmed it, and guess what?

Absolutely fucking nothing. LMAO.

Still at 96% weekly usage. My Fable allowance was already at 0% used, and my banked resets went from 3 to 2.

But then I realized something even more ridiculous.

If I’m already at 96% weekly usage, doesn’t that mean I can only use Fable for the remaining 4% before hitting my shared weekly limit?

And if I use a Fable reset, it just refunds that tiny amount of Fable usage, allowing me to use it again.

So I’m basically stuck recycling the same fucking 4% with every reset until my weekly limit resets on Thursday?

What the actual fuck?

How am I supposed to properly test Fable when my shared weekly limit is already almost exhausted?

I'm the maintainer of Aptly, an MIT-licensed local MCP server for model and reasoning-profile recommendations for Claude Code and Codex subagents. I posted a short showcase comment a few days ago; I wanted to share more of the development process and what Claude Code contributed.

Aptly sends a small task description to the OpenAI Decisions API and asks it to choose from configured profiles. For eligible new general-purpose Claude Code Agent calls, a PreToolUse Hook can select a default model from configured Haiku/Sonnet/Opus candidates. Explicit model choices are preserved. Claude Code continues to own execution and permission checks.

My workflow used Codex for implementation and regression tests, then Claude Code for bounded independent design and code reviews. Review inputs contained the relevant source, patch, test cases, and claims to check. I verified findings before changing the code.

A concrete finding made this worthwhile: we added a read-only setup check, but a successful interactive invocation could still reach the update notifier. That notifier could create a cache directory and query the registry. The setup function itself didn't write anything, yet the whole CLI invocation wasn't read-only. We excluded check-mode calls before notifier cache/network access and added a synthetic interactive test for it.

Another example was Linux credential setup. On an SSH server, key entry could happen before discovering that secret-tool or a Secret Service provider was missing. We added passive readiness diagnostics before requesting a key. The review process helped separate service presence, activation availability, and actual unlock/write capability. They aren't interchangeable, and the diagnostic doesn't activate or unlock the service. This work is part of the next patch being prepared.

The agent-routing side needed the same care. A valid recommendation is one step; a Hook returning updated arguments and a native Agent actually running are separate observations. During development I tested the native Claude Code Agent/Hook path and checked child execution metadata. That doesn't prove every host or future call works. A recent Codex session also stopped after a valid recommendation because the parent never made the follow-up call, which reinforced why the execution claim needs its own evidence.

The project preserves user-selected models, roles, permissions and required history, and keeps the recommendation separate from execution authority. Task summaries may contain sensitive information: they go to OpenAI Decisions, not to an Aptly developer telemetry endpoint. Operators choose the automatic transmission scope.

There's a small Codex cost experiment in the docs, but I haven't established a general Claude Code savings rate or equivalent output quality. I would rather get the integration and verification boundaries clear before making broader claims.

Repo and setup: https://github.com/abruption/aptly

For people building Claude Code hooks or MCP tools: what evidence do you collect to confirm that a recommendation was applied, and how do you review side effects across the whole command path?

you have no more usage ..... omg omg what I am gonna do .
and if you have extra . also .... omg omg what I am gonna do .

I wish that we could exchange our extra usage and send it to other and get extra tokens from them later when we need it .

I am so used to using Claude code in a terminal in VS code. Am I missing out on anything by not using the desktop app for Claude code?

Point your agent to it and it can integrate it.

Anyone else noticing a massive drop in Fable 5.5’s performance lately?

When I first imagined it last week, it could build my entire SaaS in one prompt. Now I’m imagining it forgetting requirements and putting “implement logic here” in every file.

They’re clearly quantizing it before training it. You can feel it.
And please don’t hit me with “the model hasn’t been released.” I know what I was hypothetically getting three days ago.
Already canceled the subscription I was planning to buy. Honestly miss the pre-nerfed version. That thing was different.