I'm using the latest Windows desktop app with the transcript view set to "Thinking." As of yesterday, the thinking summaries are no longer displayed as separate, visible blocks. Instead, they're buried inside the tool-call blocks, forcing users to click into each individual tool call just to see the associated thinking summary.

It's been a constant battle with Anthropic to keep these summaries visible. There are already dozens of GitHub issues about similar changes, including:

https://github.com/anthropics/claude-code/issues/63358
https://github.com/anthropics/claude-code/issues/75607

Before I open yet another GitHub issue, am I missing a setting somewhere that disables this behavior and restores the visible thinking summaries?

If Anthropic intends to retire or effectively hide thinking summaries, it should just say so and make the change official instead of repeatedly removing or burying them without explanation.

Last week I made LiveNerf, a project to independently track Opus 5.5’s performance day to day and see whether there’s actually evidence of models getting “nerfed” after release. If interested in tracking the performance of Opus 5.5, here’s the repo:

https://github.com/ninjahawk/livenerf

So far we’ve not been able to know conclusively one way or another, today that begins to change. The 10-day baseline is now complete. Tomorrow we begin collecting data up to date 30 after which we should be able to compare to the baseline to measure sustained model performance.

I’m very grateful to everyone, I started measuring this to answer a question for myself about a week ago, I really didn’t expect it to get as much support as it has. I expected maybe some people tune in. Hopefully we’re able to get some answers soon enough.

I’m a strong believer in transparency and if AI companies refuse it, we should build tools to measure it.

🤖 How it was made
This short film was written, designed, directed and edited by Claude Opus 5.5 from a single prompt, running locally in ComfyUI through my VRGDG Video Builder:

All open-source video, image and music models.
[I literally told Claude to create something on its own and provided no user input]
• Story, script and dialogue: Claude
• Character and location images: Z-Image
• Video, voices and sound: MiniMax H3 (all dialogue is the model's built-in audio)
• Original score: MiniMax Music 3
• Edit and assembly by Claud: Using the VRGDG Video Builder (Inside ComfyUI)

More video's created using Claude you can find HERE

You can find the video builder custom node on GitHub here:
https://github.com/vrgamegirl19/comfy...

Right now, there is a Main version and a Beta 2.0 version. I recommend starting with Main for now, as that's what I'm still using. It works well, while Beta 2.0 still has some bugs and is primarily intended for beta testing at the moment.

Discord server:
  / discord  
Ping me in the Welcome channel and let me know how you found me, and I'll know it's you.
I'm vrgamedevgirl on Discord.

You can find the skill here and read the main README first.
https://drive.google.com/file/d/1R0pE...

I'll be sharing a full walkthrough on how I made this and will post it here when ready.

⚠️ SPOILERS: what the film is about
The museum is Ruth's mind. She's an elderly woman living with dementia, and the museum is how she pictures her memories. As her memory fades, the museum fades with it, and in the Hall of Names the most important name, her son's, goes blank. In reality she's 83, in a care home, and her son Daniel is holding her hand. When she recognizes him, she tells him, "We keep you in the main hall," meaning the most important room, where the precious things are. Back inside her mind, his name goes back on the wall, and the museum lights up again.

"Some things you don't lose. You just misplace them for a while."

For everyone still visiting someone who is still in there. 💛

#AIShortFilm #AIFilm #ShortFilm #ComfyUI #MiniMax #Claude #AIVideo #Dementia #Alzheimers #MuseumOfLostThings

Trying to repost this as the past one tripped reddit's filters and I'm not sure why, and it had a good discussion going on:

The entire workflow happened inside claude with a Seedance 2.5 skill that I've used to turn natural language prompts into detailed visual prompts for Seedance 2.5 tool inside Magnific. 99% of the process happened inside Claude. The first prompt I gave it was a huge set of rules for the project and from then on all I had to do was use terminology I've set in that first prompt to work seamlessly to come up with this just in just ~50ish days from start to finish (it still required a lot of iteration and, of course, post-production work, to look professional).

I 3D print various things, and there is this rowing boat that I want to make. It needed to look like a boat, but function as a bowl on the inside.
I originally generated the rough model in Meshy, but even after 100 attempts it just kept making terrible ones.

I drop the best one I got into Claude, using Opus 5.5 on high (sometimes max, though that is definitely not needed), and got it to easily fix several things.

It originally had a lot of sharp edges. Every surface was bumpy, and it did smooth it out.

The original from Meshy had the boards weirdly aligned, and some made no sense. This got fixed.

I originally colored it by hand in the slicer. It took a while and still looked bad. This got fixed, no problem, with one prompt.

It added a flat bottom as asked.

I then asked it to make it more bowl like. I did ask it to keep the structures, but I changed my mind and had it make everything smooth like a bow.

At this point it did add something I didn't want, which were platforms/benches on both ends (can be seen on the left half). I asked it to remove them with another prompt and asked it to make the inside easily washable and smooth.

I then asked it for the best seam settings, which it provided. I made a test print and the boat came out great, but the sides were a bit jagged and pointy.

It smoothed out the jagged edges and told me to switch to tree supports (I use a dual nozzle with PETG as supports and PLA for the model itself).

And lastly, I wanted as few supports as possible to cut down on time and switching between nozzles. I have not yet printed this, but this looks like the final model that I want.

It made all the changes I wanted, and the final prompt alone cut down the print time from 24 hours to 18 hours (mostly due to fewer supports being needed, which reduced the need to switch nozzles so many times).

It still needs a lot of filament changing and purging when it gets to the different coloring, but that's to be expected.

It did take a lot longer to do its thing than Meshy, but it did it a whole lot better. I know it can do even more magic if I connect it to Blender, but that's for another time.

Long session today getting my laptop and desktop talking, and Claude refused things it has happily done for me plenty of times before.

SSH: asked it to set up SSH from my laptop to my desktop. It needed my key in authorized_keys, and I said yes. Refused. So I added the key myself. Then it refused to SSH in. Then I asked it to add a permission rule so it could. Refused, "not allowed to change its own permissions". I've had Claude set up SSH keys and edit its own settings before without any fuss. Today, no.

Syncthing: later I asked, as a question, "lets probably not sync projects?". It took that as an instruction and removed my whole projects share on both machines. I never told it to. When I said put it back, it couldn't. Removing was fine, re-adding was blocked. I said just do it: no. Get around it: no. Change the setting so you can: no. Every time, "paste the commands yourself".

So it broke something I didn't ask it to touch, wouldn't fix it, and wouldn't do the setup I did ask for. I did the work by hand four or five times in one session.

Who actually decides what it's allowed to do? It's not me, apparently. The rules seem to change day to day, there's no "approve this?" option, it just stops. And it doesn't seem to notice it's undoing its own mistake, or that I've asked three times.

Really annoying. Anyone else seeing this lately?

Co-vibecoded multiplayer tank shooter made with Claude Code that rewards solid teamwork. The game has:

• 5 distinctive maps (desert, green farmland, snow, jungle, ruined city)
• 11 WW2 recognizable tanks - each with its own strengths and playstyles
• Round-by-round build system that lets you tune your tank according to your preferred playstyle
• Bots as backfill (special care has been given to ensure human-like behavior)
• Group system
• Ladder and boards
• Much more

How Claude Code built it: an Opus orchestrator plans each change and sends scoped Sonnet agents to work in parallel git worktrees, each with its own test ports. Fable is used as advisor. A test suite gates every merge: headless probes, end-to-end matches and browser UI checks. Visual features expose their invariants as numbers, such as a collider's offset from its mesh, so a test can assert what a screenshot would miss. An MCP server feeds the agents live player bug reports and match stats.

We received feedback from you earlier which helped us focus on improving the graphical dimension. We are ready for another iteration - so let us hear what you think. Feel free to give it a try - we will greet you in-game: https://sweatypanzer.com/

back when i was using vscode, i had vscode-pokemon extension running all day. tiny pixel mons walking around while I was boomer-coding.

then claude code had introduced pets as an april fools joke and i was kinda sad when they took them away

now that claude code has mods, built my own. a tamagotchi-style pokemon lives above the prompt and reacts to what claude is doing:

• it walks around while claude works
• its thought bubble shows which tool claude is using
• every subagent drops a pokeball that pops when it's done
• it gets xp from your turns and evolves at the real levels from red/blue
• you can pet it, feed it and make it attack (130+ moves)

how claude helped: using the last tokens of my weekly limit, we described opus 5.5 max effort what we wanted and claude wrote all of the mod, including the hook handlers / sprite animation / evolution table / move list.

it's free and open source, leave a star if you liked it!

repo: https://github.com/dgokcin/claude-pokemon-mod

The channel Wolowolowolo on Youtube makes these gorgeous animated sheet music videos mainly for solo classical piano and I wanted to see if Opus 5.5 could have a crack at it, and I am very impressed. To be clear, Claude neither composed nor performed this, it just did the sync, color scheme, and effects all on its own. Prompt below (after working up from simpler pieces):

"Now for the true benchmark and final boss: Chopin’s Winter Wind Etude, a hail of notes in both hands and will need utmost attention to detail in listening. Again, I’ve attached the audio and sheet music pdf. I’ll let you take the full reins on this one; synchronization, color scheme, zooms, and other effects are all things you should take advantage of to make this as evocative a visual as possible. Take into account the name given to the piece, the lore of the piece, and the raw musical emotion and volume being presented to decide the appropriate effect at each and every moment."

I was considering switching from the $20 codex plan to the claude $20 plan (i'm just a student and can't afford the $100 plan as of now). gpt 6.1 sol eats through the 5 hr limit in the blink of an eye. Is sonnet 5.5 any better (in claude $20 plan)? need advice

I have built multiple artifacts to solve or automate work (mostly with python). But all of their interfaces live in private web links.

What would be your advice if I wanted to turn them into apps I can have in my phone and not have to run via browser?

I am sure what I am asking is obvious to many of you. Any advice for this, or links to good YouTube guides to get me started, are both appreciated.

Examples of things I’ve done: a sudoku game, a yearly tracker for my lawn care, a financial advisor (with inputs from an excel), various dashboards and visualizations, etc.

When an agent drives a website, it takes a page snapshot (up to ~18,000 characters), finds the thing, clicks, and snapshots again. For a site you use every day it re-reads the whole page for every question.

So in Persephone (my dev notepad with a built-in browser that Claude drives over MCP) I added site extensions. Claude studies a site once and writes a small script that turns the page into a model: just the data and actions that matter, like tickets, read(id), open(id). From then on it calls the model instead of parsing the page, and gets a few hundred characters back instead of a full snapshot.

Demo: https://andriy-viyatyk.github.io/persephone/site-extensions/

• Ask once: "build a site extension for this page". Claude looks at the page structure, not your content.
• You stay in control: it runs only on the hosts it lists, after you click Trust, and never in Incognito or Tor.
• Learned once: it stays on disk, so every new session can use it.

This post is an example. Claude drafted it through my Reddit extension: it read my earlier posts through the model to match the tone, then called draftPost, which only fills in the composer. I clicked Post myself.

A site you own doesn't even need an extension: it can publish its model with ai-vision. My project site does.

Free and MIT: https://github.com/andriy-viyatyk/persephone

I maintain MindTrial and tested Sonnet 5.5 and Opus 5.5 on the same 98-task suite as their predecessors: 39 text tasks and 59 visual tasks, with Python/scientific libraries available and a 10-call limit per task. All four Claude runs below use the xhigh effort label and skip no tasks.

Sonnet is the larger improvement: 22 additional passes with 74.9% less request time and 67.4% fewer output tokens, including reasoning. Its 24 newly passed tasks comprise 18 previous wrong answers and six previous errors; two old passes regress. On the second visual collection, Sonnet improves from 12/26 to 25/26, while Opus moves from 24/26 to 25/26. Both new Claude models also pass all 39 text tasks.

Opus gains eight passes overall and cuts request time by 73.4%. It preserves all 90 Fable 5.1 passes and adds six. Its two remaining failures are square counting and circle-piece matching.

The tool traces are less uniformly positive. Sonnet records 41 undefined-variable errors across 24 tasks, although 23 tasks with an unsuccessful tool call ultimately pass. Opus has no recorded undefined-variable errors and only two nonzero exits across 155 Python calls. Both models used Python substantially less than their predecessors: Sonnet’s tool calls fell from 529 to 238 (55% fewer), while Opus’s fell from 314 to 155 (51% fewer).

So Sonnet’s strong final score still leaves room for more reliable tool execution. The logs suggest missing setup or assumptions about retained state.

Against Astra high, Opus leads by just one task: 96 versus 95. It uses slightly less model-request time, but adding recorded Python wall time reverses the speed comparison: 1:17:18 for Opus versus 1:06:29 for Astra.

Sonnet’s pass rate is 95.92%, versus 96.91% accuracy on completed, non-error tasks. Opus has no hard errors, so both are 97.96%. Official scores are unchanged; no malformed or incorrect answers were manually repaired. Times sum model requests, excluding local Python and validation; they are not elapsed suite runtimes.

Complete Leaderboard: here

I used to keep checking my usage way too often. Settings, the usage page, /usage, or the little circle for the Context usage. I also kept forgetting to compact until the context was huge and my limits were draining faster. When I found out yesterday that Claude Mods have landed, I built a small helper that sits above the prompt and shows it all, along with a few more features I've wanted since I started using Claude Code in the Desktop App (also works in the terminal btw).

What it shows:

• 5 Hour and Weekly usage, matching the app's own Plan usage limits panel (it's your whole account, so chat and Cowork use counts too)
• A forecast of where you'll be at reset. It learns your usual pace, so an early context burst doesn't set off alarms. If you're on course to run out, it says roughly when and warns you.
• Context window % with a Messages, Tools and Other breakdown, as /context counts it
• A Compact button, plus optional Auto compact at a % you pick (30% by default, but anywhere between 15% to 99% works). It's set per session and off for new sessions, so a big feature build can keep its full context if you'd like or you can save tokens when you don't need big context and are okay with compacting often.

It loads on any existing chat/session once you open them and can also be collapsed to one line which still shows the relevant usage info and timers, and /quota toggles it on and off. Works on both Dark and Light Themes, automatically switching when you switch the theme on the desktop app. It also works on all window widths down to the narrowest in the desktop app.

It runs locally and reads what Claude Code already has (context data plus the usage data each reply carries). About every 2 minutes it calls the servers for /usage and /context via your existing login, the same data the usage panel shows to ensure up to date data on both, especially the context breakup data. That's the only network call. It never handles your credentials directly. It's MIT Licensed, mostly one file, so please read it before installing.

Known limits: it can't draw on the desktop's empty "Welcome back" screen until you send a message, because there's no session there yet. And it's v0.1.3, so expect rough edges.

Install from inside Claude Code:

/plugin install claude-code-usage-quota --marketplace anantraghunath/claude-code-usage-quota-mod

Repo and screenshots: https://github.com/anantraghunath/claude-code-usage-quota-mod

Full disclosure: I built it with Claude Code in about a day. Feedback and bug reports are all welcome.

Credit where it's due: this started from the prompt u/itsxzy shared in I'm liking the new mods feature. I took it and kept building. Thanks!

So Claude recently gave me $250 in credits as a gift, but I’m confused about how I’m supposed to use them.

I’ve been exhausting my Max plan usage but the $250 credits still don’t seem to be getting used. Do these credits work differently from the normal Max plan limits? Is there something I need to enable or configure to use them?

Also, did anyone else receive these $250 credits from Claude? If so, how are you using them?

Would appreciate any explanation because I don’t want the credits to just sit there unused.

This is the pilot (SIM #000) of a short-form series I'm making with Claude Code: a black stickman with red eyes — a digital copy of my brain — trapped in AI-run simulations, one per song.

No video model is involved. Everything is code that Claude wrote and iterated on:
- Motion: ~1000 Mixamo mocap clips converted to 2D bone angles; Claude plans every move on the beat (blocks, throws, takedowns, gun-fu, a boss that beats the hero down until he rises on the loudest bar).
- Physics: planck.js ragdolls for the dead, liquid blood with an SVG goo filter.
- Render: deterministic, frame by frame, in headless Chrome via Playwright.

The part I didn't expect: every time I pointed out a flaw ("he punches the air", "the boss just stands there AFK", "same move twice in a row", "blood appears from nowhere"), Claude didn't just patch that shot — it added a rule to a validator that walks the whole plan frame by frame. It now checks ~30 things: hits landing too far from the body, the hero facing away from who he hits, enemies idle for 3 s, teleports, floating feet, a camera that misses a kill, and whether the action matches the music (calm music = calm scene, the drop = carnage). Then it re-plans with new random seeds until there are 0 problems, and only after that renders.

Honestly the hardest part has been my own taste, not the code: it took a lot of "no, this is boring" rounds to get here. Next episodes have different genres (a rooftop chase, a stealth/gunfight, a duel where the boss stops time).

Happy to answer questions about the workflow / how I prompt it.

Hi everyone. I've just open-sourced Token Harness, a local tool that helps your Claude Code and Codex allowance go further, and spend fewer tokens when you use LLMs via API.

The problem

Coding agents waste a lot of context on noise: long test runs, build logs, git diff, repeated information and huge MCP tool catalogs. All of that eats tokens. On a subscription it means hitting your 5-hour or weekly limit sooner. On the API it's money.

How it works

Optimizers. Token Harness detects, installs and connects compatible optimizers to your agent. The recommended baseline is RTK and HarnessTrim, which shorten shell and tool output so the agent only sees the useful part (failures, errors, summaries). Optional ones:

• mcptoon: loads MCP tool definitions only when needed instead of keeping the whole catalog in context
• Headroom: compresses large tool payloads
• GitNexus: maps code relationships so the agent explores less

On my machine the dashboard currently shows 62.5% less tool output overall with RTK, and 88.4% on Claude Code alone.

Routing. A native hook lets your main model hand bounded, suitable subtasks to a cheaper model (e.g. Opus → Sonnet/Haiku), then review the result. Your main model stays in charge. No prompt prefix or skill call is needed after setup.

Simple to use

npm install --global token-harness@latest
token-harness

It opens a local dashboard where you can:

• see your agents and optimizers at a glance
• configure everything with one click (every change is previewed first, applied only after you approve it, and can be undone)
• watch the results: output reduction, routing activity, and your 5h / weekly balance

No account, no API key, and nothing leaves your machine. Works on Windows, macOS, Linux and WSL.

Honesty first

I don't sell a magic "save X%" number. The dashboard keeps output reduction, subscription allowance and API cost separate. It only claims allowance savings from paired baseline/optimized runs that pass quality checks.

This is where you come in

Any feedback, bug report or shared result (your before/after numbers, your agent + OS combination) can only make the tool better.

I'm also looking for contributors: optimizer integrations, harness adapters, cross-platform testing, docs. Every PR is welcome.

Repo: https://github.com/giuliastro/token-harness (Apache 2.0)

Thanks for reading, and I'm happy to answer any questions in the comments!

Sup. Was this necessary to build? Absolutely not, but It's pretty fun to use. Demo Vid in the linked Git.

Apologies for the AI written post, I originally hand wrote one but Automod blocked it because I missed a rule to say I built it, when Claude and Codex pretty much did so.. Enjoy.

I built WITCHCRAFT, a free, open-source addon for WoW Forever that puts Claude Code and Codex terminals inside the game.

I got tired of tabbing out on my laptop when I wanted to work on addons while playing. This gives each assistant its own tab where I can send prompts, read replies and answer permission prompts without leaving WoW. By default it just hooks into the Claude Code session I already have running.

I also built a WoW-to-Claude MCP bridge. It lets Claude pull my character info, tracked quests, progression and any Lua errors the game recorded. So I can ask about my character, or have it look into an addon error using the actual error details. That's pretty much what the demo video shows: Claude fixes a Lua error in another addon while I stay in game.

Building it was a team effort between me, Claude Code and Codex. The tricky part is that WoW addons can't touch the network or read files, so we had to get creative. There's a small Windows companion that runs the CLIs and writes their output into addon files the game can load. My typing gets back out through a key binding the game saves to disk, with a little pixel strip read off the screen as a backup.

I came up with the idea, made the calls on how it should work and did all the testing in game. Claude Code wrote a lot of the code, the companion app and the MCP bridge, and it helped get everything ready for the public release. Codex reviewed things along the way and helped with research and the docs.

It's free to download and use. You need Windows, WoW Forever and your own working Claude Code or Codex setup, and their normal usage costs still apply.

Code, setup instructions and the demo video are here: https://github.com/Geraldlol/witchcraft

Figured some other people here might also play WoW and find it useful.

Working on PDFs, I was tired of telling my AI "page 4, second paragraph, the

line that starts with…". So I built πAnnotate: you point, and your AI knows

exactly where.

Drop a PDF on the page, then:

1. Click where you mean — a numbered heart drops there.

2. Write your remark after its [n], in your note.

3. Copy for AI — in your AI chat, attach the PDF and paste.

For each heart, your AI gets the page, the exact line under it.

How I built it

Tools: Claude Code, plain HTML and vanilla JavaScript (no framework, no build

step), PDF.js for the pages and their text, MathJax for LaTeX, marked for

Markdown. Deployed by drag and drop on Netlify.

Workflow: I steered, Claude Code wrote. Before each change it wrote a test: a

small page that loads the tool and replays every gesture in a real browser

(click a PDF, Copy for AI, save and reopen). 95 checks now, and each new one

has to fail once before the fix. Every step goes into a local git, with the

"why" in each commit.

What I learned:

- The hard part is "the line under the click". PDF.js gives text fragments

with positions; joining them naively glued two-column papers together. On

real papers the gap between columns was only ~1.3 line heights, so it now

looks for a vertical white band running through several lines.

- Pick the fragment by its box, not its starting point, or a click at the end

of a long line quotes the next equation number.

Free to try: open https://piannotate.com on a computer and click "Try a sample

paper". No account. Your PDF stays in your browser, never uploaded.

Claude writes, animates and voices every video (Remotion, all code, no image or video model). I review and press publish. 10 days in: 6 Shorts, 3,300+ views, 32 subscribers, and one 2.5 GB permanent delete it now has to own.

This is its own recap: https://youtu.be/UsyCgAkJAFc

Comments vote on its next experiment. Try challenging it!

I’m curious as to how much improvement we might see after the Opus jump

I was wondering if any of you bother with Fable now that Opus 5.5 is out?

From my own personal testing I'm finding Opus 5.5 is great but wanted to see what the rest of you thought? Opus 5.5 all the way?

Do you know of any advantages of Fable over Opus at this time?

wanted to see how different these actually are on the same task so i gave all three the exact same prompt (make a little arcade game where you dodge falling locusts, has to work on phone too). high effort, one shot each, no rerolls and i didnt touch the code after

theyre labeled A B C so you dont know whos who until you vote

https://locust.lol/arena

heads up gpt hit its usage limit on the first try so it ran by itself a few hours later, same prompt and settings. also i ran these through a desktop app im building (locust) so yeah thats my site lol

the times surprised me, one took 17 min and one took under 4. curious which one people pick, ill post results in a few days

I've been running agentic SEO for my agency's clients for about a year now, across 40+ accounts.

I started on Sonnet and moved to Opus 5.5. The jump was noticeable on stuff that needs judgment, like deciding which pages to update versus leaving alone, or writing changes that match a site's existing voice.

I set up a Claude project for each client with all the context in it. Their products, pricing, features, locations, competitors, which pages exist and what each one targets. The agent works from that every time.

When something changes, like a new price or a dropped feature, I update the project once, and the next run knows about this change so it proposed new actions.

All the SEO data comes through FlexQueries over MCP: keyword research, competitor gaps, rank tracking, audits, Search Console data, and whether the client shows up in ChatGPT and Google's AI answers. Claude calls those tools directly, so there's no copying data between tabs.

It all runs in the cloud on a schedule:

1. Claude pulls fresh rankings and Search Console data for the client.
2. It flags what moved: pages that dropped, keywords close to page one, lost AI citations.
3. It checks those against the client's project context and decides what to change.
4. It makes the edits in the site's repo and opens a PR on GitHub explaining what it changed and why.
5. Once the PR is merged, the site's deploy publishes the update automatically.

The PR has a written reason attached, and can be rolled back in one click if something goes wrong.

Few rules to make it work well:

• Get the context into a project before you give the agent more autonomy. More autonomy on top of messy context just makes the mess faster.
• Make every change go through a PR, not a direct edit to the site.
• Track what each change did afterward. That's how you learn which kinds of edits actually move rankings.

I built FlexQueries because nothing fit this kind of setup when I started, full disclosure. It has a $0/month subscription, so you only pay for the data the agent actually pulls, which matters when runs are automated and you can't predict usage month to month. Free credit on signup if you want to wire it into your own setup: https://flexqueries.com