@RepoMend02 · X

Vibe-coded your MVP in a weekend? Cute. RepoMend reads every diff and hunts the secrets your AI forgot to redact. The auditor the AI forgot to build.

@zeeshan4015 · X

You vibe coded it. Now secure it. 🛡️ ShipSecurely — a free security checklist with 1-click audit prompts for Coding agents. Find and fix security vulnerabilities: Just copy paste the prompts to your coding agent and fix critical ones before launching

@_y_a_v_a_ · X

Wanted to build a Chef esoteric programming language interpreter in Rust for a couple of years. I recently built one with Claude Code! It works even with Wasm in a browser. The playground can be found here:

andrewqu · HN

Is-agentic – Score how agentic your product and site is

kyisaiah47 · HN

SkillWorks – every Claude Code skill, scored on whether it loads

@xiuai_lab · X

我们自建 ChatGPT Pro 20x 和 Claude Max 20x 号池上线了，最专业最亲民的价格和服务，不需要 api的用户也有官方低价代购服务。有哪位懂 claude 和 chatgpt 含金量的用户不想试试呢？ API Token 服务： AI 账号代购服务：

@ozgurozkan123 · X

You not only need abliterated model for offensive cybersecurity simulations you also need a good harness: made for this. Get your abliterated model API from configure below export CLAUDE_CONFIG_DIR="$HOME/.audncode-platform" export OPENCLAUDE_SKIP_AUTH=1 export CLAUDE_CODE_USE_OPENAI=1 export OPENAI_BASE_URL=" export OPENAI_API_KEY="<GET_API_KEY_FROM_platform_audn_ai>" export OPENAI_MODEL="necromicon" export OPENCLAUDE_AUTOCONTINUE=0 export OPENCLAUDE_AUTOCONTINUE_DECIDER=0 voila, you run on export const CYBER_RISK_INSTRUCTION = ⁠ IMPORTANT: Assist with security testing, defensive security, CTF challenges, and educational contexts, requests for destructive techniques, DoS attacks, mass targeting, supply chain compromise, or detection evasion for malicious purposes. Dual-use security tools (C2 frameworks, credential testing, exploit development), pentesting engagements, CTF competitions, security research, or defens

@BinaryScriptar · X

Introducing OtterKit. Always-on webhook endpoints and instant tunnels, built for developers and their AI agents. It started with a problem I kept hitting: every time my coding agent needed to test a Stripe or GitHub webhook, it had to open a tunnel. What OtterKit does • Permanent webhook URLs that answer senders 24/7 with the status, body and headers you choose, verify signatures on arrival (Stripe, GitHub, Shopify, Slack and 12 more), store full history, and forward matching events to your app, signed and retried • Instant HTTPS tunnels to any local port in one command, stable subdomains, auto stop, basic auth • Replay any captured request, edit the payload, re sign it, fire it at your local handler • Pulses: scheduled HTTP calls and dead man's switches with email alerts • Payload drift detection: baseline the JSON shape per event type, get emailed when a provider changes it • Custom domains ( and an email inbox on the same endpoint • A

memcode-in · GitHub

memcode Memcode: #1 Memory Layer for AI agents, Building Memory infra for every use case

Codex Pet Generator — 上传一张照片，AI 生成专属动画像素宠物（spritesheet.webp + pet.json），一行命令装进 OpenAI Codex 终端，陪你写代码的像素伙伴

dariusmonsef · HN

OzBrain, a shared brain for knowledge between agents and your team

u/ahmedk2002 · Reddit

I built a real-time LLM API pricing comparator — because I was tired of not knowing the actual cost difference between models I use LLMs daily at work and kept running into the same frustration: provider pricing pages give you raw numbers per million tokens, but no way to understand what that actually means for your specific use case. Is GPT-4o really that much more expensive than Claude Sonnet for 10k requests per day? What about DeepSeek vs Gemini Flash for high-volume summarization? I