Anthropic Claude API

Anthropic Claude API AI

Anthropic Claude API AI

Anthropic Claude API AI

Anthropic Claude API AI

Anthropic Claude API AI

Anthropic Claude API AI

Anthropic Claude API AI

Anthropic Claude API AI

Anthropic Claude API AI

Anthropic Claude API AI

open sourced our skills package so Claude Code can post to 10 social platforms (MIT)

we maintain Pub͏lora, a social media scheduler, and a while back I wanted Claude Code to be able to drive it the same way I drive it from a browser. ended up building two things: publora/skills, open source MIT package on github with 10 platform skills (LinkedIn, Threads, Telegram, Instagram, TikTok, Bluesky, X, YouTube, Facebook, Mastodon). install with npx skills add publora/skills. each skill wraps the publora API for one platform: post, schedule, analytics where available. MCP server so Claude Code or any MCP-compatible client can use publora as a tool. needs a bearer token. queue posts and pull analytics happens through the agent. fr͏ee tier: 15 posts/month. pa͏id tiers $2.99/mo (pro) or $9.99/mo (premium) if you outgrow that. X/Twitter posting is only on paid tiers because their API has costs. publora.com for the main app. repo: github.com/publora/skills. submitted by /u/Krixim [link] [comments]

Subscription alternative for occasional users? (small business)

We're a small business with 10 employees. Since we only use Claude very occasionally it makes no sense to pay for a monthly subscription for all users. E.g once or twice a month, we need to make a report, and would like to use Claude Excel plugin, etc. I thought about just making one account, and sharing the user and pass amongst the employees, but this is not a good solution since they sometimes will enter personal data. From what I understand, Anthropic don't offer a payment model where multiple users have access and only pay for the use, instead of a fixed monthly fee? Confusing, it seems that API account is similar to what I want, but it doesn't support plugins or chat? submitted by /u/cryptogeezuzz [link] [comments]

the dashboard rebranding is live. "business intelligence for tradesmen." claude built 60% of the new analytics features.

the pivot: invoicing tool → business intelligence platform for tradesmen. the dashboard that started as an accident is now the product. new features built with claude code in the last 2 months: expense tracking: input expenses. dashboard shows profit margins per job. 8 hours to build. revenue forecasting: 3-month projection based on historical invoicing patterns. 12 hours. customer concentration: alerts when one customer exceeds 30% of revenue. 4 hours. all 3 features were claude-assisted. the architecture, the API endpoints, and the initial UI. i refined and deployed. the dashboard now functions as a simple ai report generator for tradesmen. revenue trends, expense tracking, profit margins, customer health. the data that used to require a quarterly accountant visit is on their phone. 185 of 270 customers use the dashboard daily. the rebranding from "invoicing" to "business intelligence" reflects what customers actually use. the custom claude style for technical documentation ensures release notes are consistent. the style for customer communications ensures the rebranding messaging is warm and clear. for founders with "accidental features": if your customers use it more than your core product, its not accidental anymore. its the product. submitted by /u/Ok-Salary-6309 [link] [comments]

API Cache not working or Claude Console Dashboard UI bug?

Hey there, I'm not sure if my system was using cache or if I was burning tokens needlessly? How can I confirm I have things set up correctly and it's only UI bugs? My Claude Dashboard and dashboard logs are not consistent (can one download the full log?) Using Rider and Continue.dev name : Local Config version : 1.0.0 schema : v1 models : - name : Claude Sonnet 4.6 provider : anthropic model : claude-sonnet-4-6 apiKey : ${{ secrets.ANTHROPIC_API_KEY }} roles : - chat - edit - apply defaultCompletionOptions : promptCaching : true requestOptions : timeout : 200000 thinking : type : "adaptive" effort : "low" https://preview.redd.it/h40ho3ui7n4h1.png?width=392&format=png&auto=webp&s=262fc188714299962923fbff961bab6814c3c45c https://preview.redd.it/g1l5uahj7n4h1.png?width=1096&format=png&auto=webp&s=08960e0f51b6628f9bb15863e463862cd844a0de https://preview.redd.it/5gtstt1k7n4h1.png?width=423&format=png&auto=webp&s=9fcb62379045259cd6ebc99c541b6bb90100e5a2 submitted by /u/SavingClippy [link] [comments]

Why have 126,000,000 tokens been used in 7 hours when I haven't sent a single message?

(This is not me complaining about limits, this is a bug where usage is being spent from literally nowhere, of which is clearly obvious) between 3am (when my weekly started) and now, 10:06am, my weekly has been used 21% and my session has been used 100%. I haven't even been awake to send a single message. I am only logged into my on my phone and computer, and neither have been accessed by anyone new. There has been no new chat appearing in recent chats, nor any new messages appearing in any existing chats. I do not have any currently running API codes that I use, I don't use claude code, nor am I connected to any external platforms like connectors or plugins. Is this a known bug? Support bot hasn't provided anything helpful. Thanks in advice for any help. submitted by /u/SamwiseMay [link] [comments]

I used Claude Code to build a free Pokémon personality profiler from scratch in one session

Hey r/ClaudeAI, I built NotRandom (notrandom.vercel.app) a free web app where you type your favorite Pokémon and get a psychographic profile based on your choice. The premise: your favorite Pokémon is not random. It reveals something real about you. What it does: Fetches the Pokémon's types and Pokédex lore from PokéAPI Classifies it into one of 10 archetypes (The Sovereign, The Rebel, The Shadow Operator, The Jester...) Generates a Core Identity, Shadow Side, a unique nickname ("The Calculated Vanishing" for Greninja), and a one-liner "The Line" designed to feel uncomfortably accurate Lets you download a 1080x1080 shareable image card How Claude Code specifically built this: Everything was written by Claude Code in a single session. Here's what it actually did: Full architecture I described the concept, Claude Code planned the stack (React + Vite + Tailwind + Vercel serverless) and the complete file structure before writing a single line All React components from scratch LandingPage, LoadingScreen, ProfileCard, ShareCard, state machine in App.tsx The archetype system designed and coded the mapping of all 18 Pokémon types to 10 personality archetypes with color palettes per type The Claude Haiku prompt engineered to return a structured JSON with the right tone (intelligent, slightly poetic, never cringe) Solved a real architectural problem — the Anthropic API blocks direct browser calls (CORS). Claude Code diagnosed it, then created a Vercel serverless /api/profile route to proxy the call server-side Debugged the share card the downloaded image was black. Claude Code identified two causes: position: fixed breaks html-to-image's canvas renderer, and Google Fonts fail silently during capture. Fixed with skipFonts: true + sprite conversion to base64 before capture Full deployment Vercel config, environment variables, 30s timeout for cold starts I described what I wanted, Claude Code wrote the code, I tested, reported what broke, it fixed. Classic loop. https://preview.redd.it/i62hsrbd0n4h1.png?width=1080&format=png&auto=webp&s=aa31a839f094fa5760e401e8f336b01efbb49179 Free to use: https://notrandom.vercel.app no login, just type any Pokémon name in English (all 1025 are supported). submitted by /u/dyloum84 [link] [comments]

PSA: "deep research" in Claude Code is *not* the same as in the desktop/web app.

Learnt this one the hard way. Previously I've used deep research to build helpful reports on whatever topics, e.g. API docs that I want CC to build an interface for. Fired up a deep research session from Claude Code - it launched 199 agents and burnt ~50 million tokens over 30 mins! Now I'm timed out, oof. Turns out this is a new(?) thing? Maybe? A "dynamic workflow", say the docs. The docs also mention that these workflows are "limited" to 1,000 agents per run. Lol. Lmao, even. submitted by /u/marky125 [link] [comments]

trying to see if Mythos claims are verified or not

The claims about Mythos Preview (Anthropic's unreleased Claude model) are substantially verified from multiple independent sources, though the exact CVE numbers and commit hashes for the FFmpeg vulnerability are still being disclosed through coordinated security processes. Key Verified Facts 1. OpenBSD 27-year-old vulnerability ✅ Verified What: A bug in OpenBSD's TCP SACK (Selective Acknowledgment) handling introduced around 1998[forum.devtalk] Impact: Allows an attacker to remotely crash any OpenBSD machine just by connecting to it via TCP[linkedin] Details: OpenBSD tracks SACK state as a singly linked list of holes; the vulnerability is subtle and survived 27 years of expert review[reddit] Patch: Available at openbsd/pub/Openpatches/.8/025ack.patch[reddit] 2. FFmpeg 16-year-old vulnerability ✅ Verified What: A bug in FFmpeg's H.264 decoder where a 32-bit slice counter is stored in a 16-bit lookup table, initialized to 65535[secureworld] Impact: A specially crafted frame with exactly 65,536 slices causes counter collision triggering out-of-bounds write[secureworld] Origin: Type mismatch dates to FFmpeg's 2003 H.264 commit; exploitable code path introduced in 2010 refactor[secureworld] Testing evasion: The code path was hit by automated testing tools 5 million times without flagging the bug[linkedin] Patch status: Three FFmpeg vulnerabilities found by Mythos were patched in FFmpeg 8.1[secureworld] 3. Linux kernel vulnerability chain ✅ Verified What: Mythos autonomously found and chained multiple Linux kernel vulnerabilities for privilege escalation[reddit] Impact: Escalation from ordinary user to complete root control of the machine[linkedin] Cost: Under $2,000 in tokens to create the exploit chain[linkedin] Status: Anthropic is funding the Linux Foundation to fix these vulnerabilities[linkedin] Supporting Evidence Source Type Key Confirmation Anthropic's risk report Official PDF Technical assessment of Mythos Preview released April 7, 2026 [anthropic] AI Security Institute evaluation Independent Confirmed 73% success on expert-level cyber CTF tasks [aisi.gov] Debian security tracker Official CVE-2026-40962 fixed in FFmpeg 8.1 [security-tracker.debian] Reddit/OpenBSD forum Community Patch discussion and technical details [reddit] Why This Matters This is considered "possibly the most frightening cybersecurity news in decades" because: AI found bugs that survived decades of expert audits and relentless fuzzing[agent-wars] Mythos found thousands of zero-days versus Opus 4.6's ~500[reddit] The model achieved 181 working exploits in Firefox benchmark testing[agent-wars] Access is gated/restricted due to dual-use risk[docs.aws.amazon] The FFmpeg commit should indeed be public given it's open source, and the patch is in FFmpeg 8.1. The exact commit hash is being handled through coordinated disclosure, but the vulnerability details are confirmed by multiple independent security researchers.The claims about Mythos Preview (Anthropic's unreleased Claude model) are substantially verified from multiple independent sources, though the exact CVE numbers and commit hashes for the FFmpeg vulnerability are still being disclosed through coordinated security processes.Key Verified Facts1. OpenBSD 27-year-old vulnerability ✅ VerifiedWhat: A bug in OpenBSD's TCP SACK (Selective Acknowledgment) handling introduced around 1998[forum.devtalk] Impact: Allows an attacker to remotely crash any OpenBSD machine just by connecting to it via TCP[linkedin] Details: OpenBSD tracks SACK state as a singly linked list of holes; the vulnerability is subtle and survived 27 years of expert review[reddit] Patch: Available at openbsd/pub/Openpatches/.8/025ack.patch[reddit]2. FFmpeg 16-year-old vulnerability ✅ VerifiedWhat: A bug in FFmpeg's H.264 decoder where a 32-bit slice counter is stored in a 16-bit lookup table, initialized to 65535[secureworld] Impact: A specially crafted frame with exactly 65,536 slices causes counter collision triggering out-of-bounds write[secureworld] Origin: Type mismatch dates to FFmpeg's 2003 H.264 commit; exploitable code path introduced in 2010 refactor[secureworld] Testing evasion: The code path was hit by automated testing tools 5 million times without flagging the bug[linkedin] Patch status: Three FFmpeg vulnerabilities found by Mythos were patched in FFmpeg 8.1[secureworld]3. Linux kernel vulnerability chain ✅ VerifiedWhat: Mythos autonomously found and chained multiple Linux kernel vulnerabilities for privilege escalation[reddit] Impact: Escalation from ordinary user to complete root control of the machine[linkedin] Cost: Under $2,000 in tokens to create the exploit chain[linkedin] Status: Anthropic is funding the Linux Foundation to fix these vulnerabilities[linkedin]Supporting EvidenceSource Type Key Confirmation Anthropic's risk report Official PDF Technical assessment of Mythos Preview released April 7, 2026 [anthropic] AI

How long does it take for Anthropic to approve Claude Code community plugin?

Submitted through my Claude Console and it has been in "submitted and pending review" for over 10 days, wonder what I shall do next other than waiting... https://preview.redd.it/4z3a6ylowl4h1.png?width=546&format=png&auto=webp&s=e606c8f59fbcefea35b42f399e1dc7ef9480e7dd submitted by /u/darren_eng [link] [comments]

Open-source tool to redact secrets from your clipboard before you paste them somewhere you'll regret (like claude)

Pasting an API key, password, or credit card into the wrong window or AI chat happens faster than you can undo it, and I've done it. So I built secret-stripper, a tiny Rust CLI that gives you a hotkey to scrub your clipboard on the spot. Highlight, press, paste, and what comes out is [REDACTED] instead of the real thing. Detects over 800 patterns across more than 40 categories 100% free, MIT-licensed, fully local. Claude Code helped along the way with polishing the TUI, general code review, cleanup passes on the detector modules, and generating the entire test suite (corpus fixtures, unit tests, and integration tests). The core design, the one-shot architecture, and the pattern catalog are mine. submitted by /u/kalix127 [link] [comments]

Differences Between Opus 4.7 and Opus 4.8 on MineBench

Some Notes: Average Inference Time: 24.8 min (1,487seconds) Total Cost (for 15 builds): $41.52 Much cheaper than Opus 4.7 was, despite having the same API pricing The CoT / thinking times have clearly been streamlined (similar to what OpenAI has been doing with their latest releases) which lowers overall cost, but despite that, the output seems better than Opus 4.7, so that's good This is, in my opinion, one of the first Claude models in a long time that actually feels like a genuinely impressive release; its builds are actually of similar quality to GPT 5.5, though a bit more inconsistent During generation, the model had to retry 5 builds due to either hallucinations with the given block palette (it used blocks which were not available) or malformed outputs That's pretty on par with the Claude models, though the adaptive thinking seems to work better this time around (in previous attempts the model would spend all of it's output tokens for CoT and not have enough left over to finish its actual JSON output) In my opinion, Opus 4.8 is a clear improvement over Opus 4.7 (or maybe it's what Opus 4.7 was supposed to be originally 🤷‍♂️) Feel free to see all the other updates on the GitHub release (thanks for the suggestion!) If you enjoy these posts please feel free to help fund the benchmark Benchmark: https://minebench.ai/ Git Repository: https://github.com/Ammaar-Alam/minebench Previous Posts: Comparing GPT 5.4 and GPT 5.5 Comparing Kimi K2.5 and Kimi K2.6 Comparing Opus 4.6 and Opus 4.7 Comparing GPT 5.4 and GPT 5.4-Pro Comparing GPT 5.2 and GPT 5.4 Comparing GPT 5.2 and GPT 5.3-Codex Comparing Opus 4.5 and 4.6, also answered some questions about the benchmark Comparing Opus 4.6 and GPT-5.2 Pro Comparing Gemini 3.0 and Gemini 3.1 Extra Information (if you're confused): Essentially it's a benchmark that tests how well a model can create a 3D Minecraft like structure. So the models are given a palette of blocks (think of them like legos) and a prompt of what to build, so like the first prompt you see in the post was a fighter jet. Then the models had to build a fighter jet by returning a JSON in which they gave the coordinate of each block/lego (x, y, z). It's interesting to see which model is able to create a better 3D representation of the given prompt. The smarter models tend to design much more detailed and intricate builds. The repository readme might provide might help give a better understanding. (Disclaimer: This is a public benchmark I created, so technically self-promotion :) submitted by /u/ENT_Alam [link] [comments]

Max Subscription vs $100 API based

I’ve been using Claude Code on a pay-as-you-go basis because the API costs can add up quickly. Lately, though, I’ve been using it a lot more than expected and just realized I’ve spent around $100 this month alone. At this point, I’m wondering if it makes more sense to just get the $100/month subscription since I’ll probably continue using it heavily. For those who’ve made the switch, was it worth it? Any downsides I should be aware of? submitted by /u/dzaffren [link] [comments]

I had Claude Opus 4.8 build me a custom 'operating system' for my business while I was at the vet

I've been trying to cut down the number of tabs I open every morning to run my content business. YouTube analytics in one place, competitor channels in another, a notes doc for trending stuff, skills I keep re-running by hand. So I tried something. I opened a blank folder, gave Claude a rough plan, and told it to build me a single dashboard that pulls all of it into one place. First I used plan mode to map it out. It asked me a bunch of clarifying questions (what to track, web dashboard vs morning briefing, which APIs I had). Then I dropped in my design system files so it would match my brand. Then I switched to Opus 4.8, turned on the new Ultra Code mode, and told it to execute the plan. Then I left to take my dog to the vet. Came back and it had built the whole thing. One panel for trends and drops in my space, one for competitor videos and their top comments, one for my YouTube stats, one for active projects, and a launchpad to run my most-used skills. The part that actually surprised me is how Ultra Code works. There is an orchestrator that spawns sub-agents to do the work, and then a second layer of sub-agents whose only job is to check the first layer's work. That verification layer is why it can run that long without me sitting there approving everything. First pass was not perfect. Everything had the same visual weight and the skills opened a separate terminal window. One more round of feedback (bento layout, embedded terminal, Apify for the LinkedIn and IG data it could not reach) and it was genuinely usable. Honest caveat: this is the most expensive way to run Claude right now. Ultra Code plus Opus 4.8 burns a lot of tokens. For a one-off deep build it felt worth it, but I would not leave it running on autopilot for small stuff. Anyone else messing with the multi-agent verification setup yet? Curious if the self-checking layer holds up on bigger codebases. submitted by /u/Drogoff1489 [link] [comments]

How do you handle runaway API costs across multiple OpenAI agents? I built something to solve this

Hey, I'm a CS student and I've been building LedgerAI, a cost tracking and budget enforcement layer for LLM agents. The problem it solves: You're running 3+ agents in production. One goes rogue overnight. You wake up to a $400 bill with no idea which agent caused it and no way to have stopped it. What makes LedgerAI different: Most tools log costs after the call. LedgerAI enforces limits before it. The SDK hits a budget check endpoint before every LLM request, and if the agent is over its daily or monthly limit, the call is blocked. Hard stop, not a soft warning. What it tracks per call: Agent name, model, provider (Anthropic + OpenAI supported) Input/output tokens + exact cost in USD Daily and monthly spend rollups per agent Completely free and open source right now. Pip install or hit the API directly with cURL. Would love feedback from anyone running multi-agent systems, especially what alerting/enforcement features would actually be useful in prod! submitted by /u/IndianCurry06 [link] [comments]

What actually is "Prompt Engineering"?

I've been thinking about this lately because I feel like people use the term "prompt engineering" to describe two very different things. On one end, you have what most people are familiar with: A person opens ChatGPT, Claude, Gemini, etc., and writes a carefully structured prompt. They define a role, provide context, establish goals, set constraints, maybe include examples, and iterate until they get the output they want. Most people seem to call this prompt engineering. But on the other end, when I'm building AI systems, prompt engineering looks completely different. The prompt isn't really a prompt anymore. It's much more of a dynamic pipeline. Variables are injected from databases, user input, APIs, previous conversations, tools, memory systems, retrieval systems, business rules, and workflow state. Decision trees determine which instructions are included and which are excluded. Prompts become assembled in real time based on context. In some cases, the "prompt" is really just an orchestration layer made up of dozens of smaller prompts, conditionals, guardrails, routing decisions, and context windows. At that point, are we still talking about prompt engineering? Or are we actually talking about system design, context engineering, workflow engineering, orchestration, or something else entirely? Personally, I see prompt engineering as a spectrum: Level 1: Writing a better prompt. Level 2: Designing reusable prompt templates. Level 3: Building dynamic prompts with variables and context injection. Level 4: Engineering entire prompt-driven systems with routing, memory, tools, retrieval, and decision logic. Curious where others draw the line. When you hear "prompt engineering," are you thinking about writing prompts, building workflows, designing agent systems, or all of the above? Has the term become too broad to be useful? submitted by /u/Early-Matter-8123 [link] [comments]