惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

Threat Intelligence Blog | Flashpoint
Threat Intelligence Blog | Flashpoint
T
Troy Hunt's Blog
Scott Helme
Scott Helme
T
Threat Research - Cisco Blogs
T
Tenable Blog
L
LINUX DO - 热门话题
V
Visual Studio Blog
I
Intezer
Blog — PlanetScale
Blog — PlanetScale
Cisco Talos Blog
Cisco Talos Blog
A
Arctic Wolf
C
Cyber Attacks, Cyber Crime and Cyber Security
F
Fortinet All Blogs
aimingoo的专栏
aimingoo的专栏
Know Your Adversary
Know Your Adversary
CTFtime.org: upcoming CTF events
CTFtime.org: upcoming CTF events
N
Netflix TechBlog - Medium
SecWiki News
SecWiki News
I
InfoQ
Microsoft Security Blog
Microsoft Security Blog
Project Zero
Project Zero
W
WeLiveSecurity
Microsoft Azure Blog
Microsoft Azure Blog
A
About on SuperTechFans
Recorded Future
Recorded Future
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
Vercel News
Vercel News
S
Securelist
Spread Privacy
Spread Privacy
L
LangChain Blog
云风的 BLOG
云风的 BLOG
G
Google Developers Blog
MongoDB | Blog
MongoDB | Blog
Google DeepMind News
Google DeepMind News
Recent Commits to openclaw:main
Recent Commits to openclaw:main
D
Darknet – Hacking Tools, Hacker News & Cyber Security
C
CERT Recently Published Vulnerability Notes
罗磊的独立博客
K
KPMG report finds enterprise disconnect between AI and its ROI | CIO
The Last Watchdog
The Last Watchdog
Attack and Defense Labs
Attack and Defense Labs
博客园 - 司徒正美
Help Net Security
Help Net Security
L
Lohrmann on Cybersecurity
人人都是产品经理
人人都是产品经理
Forbes - Security
Forbes - Security
Hacker News - Newest:
Hacker News - Newest: "LLM"
PCI Perspectives
PCI Perspectives
博客园 - 【当耐特】
T
Tor Project blog

Hacker News: Show HN

PurrrrrFocus: Pomodoro Timer App - App Store Workflow Engine — Multi-Step Orchestration for Bun RapidPhoto: Pro Photo Editor App - App Store GitHub - DheerG/swarms: Achieve extraordinary results with claude code across a variety of tasks SPICE simulation → oscilloscope → verification with Claude Code — Lucas Gerads Show HN: VCoding – A 5 MB native Windows IDE with no dynamic dependencies Show HN: LLMs don't hallucinate because they're bad at math, it's the format GitHub - Agent-FM/agentfm-core: AgentFM is a peer-to-peer network that turns everyday computers into a decentralized AI supercomputer. AgentFM lets you run massive AI workloads directly across a global mesh of idle CPUs and GPUs. Show HN: Tracking Top US Science Olympiad Alumni over Last 25 Years GitHub - Potarix/agent-hub: One place to talk to all your agents Show HN: Runtime security for AI agents(injection,tool abuse, data exfiltration) GitHub - dubeyKartikay/lazyspotify: Terminal Spotify client for macOS and Linux GitHub - the-banana-tool/king-louie: Easy to use GUI Personal AI Assistant. Win/Linux/Mac. Show HN I made my vacation rental bookable by AI agents–no Airbnb, 0% commission GitHub - basteez/jsf-autoreload: maven plugin to enable hot reload on jsf projects uvm32/hosts/host-gdbstub at main · ringtailsoftware/uvm32 GitHub - labsai/EDDI: Config-driven engine that turns JSON into production-grade AI agents. Multi-agent orchestration, 12+ LLM providers, MCP/A2A protocols, RAG, persistent memory, and enterprise compliance (EU AI Act, GDPR, HIPAA). Built on Quarkus. GitHub - glitchnsec/fortyone-oss: AI Executive Assistant Platform Quickstart | Alien GitHub - muxshed/shed: One stream in, or many. Every destination, simultaneously. No cloud middleman, no per-channel fees, no limits. GitHub - ocrbase-hq/ocrbase: 📄 PDF/IMG ->.MD/JSON Document OCR API for PaddleOCR and GLMOCR. Self-hostable. GitHub - impactjo/home-memory: MCP server that lets your AI assistant remember everything about your home. GitHub - Sets88/dbcls: DbCls is a powerful terminal database client that supports various databases GitHub - neptun2000/heor-agent-mcp GitHub - SeanFDZ/macmind: Single-layer transformer in HyperTalk for the classic Macintosh RollQuation: Math Puzzles - Apps on Google Play GitHub - dropbox/witchcraft Show HN: Agent-cache – Multi-tier LLM/tool/session caching for Valkey and Redis GitHub - opentalon/opentalon: OpenTalon is an open-source platform built from the ground up in Go as a robust alternative to OpenClaw LinkedIn™ 职位抓取工具 - Chrome 应用商店 GitHub - EdoardoBambini/Agent-Armor-Iaga: AI agents are getting tool access — shell, file system, databases, APIs, secrets. But **nobody is governing what they actually do with it**. Frameworks like LangChain, CrewAI, AutoGen, and Claude Code give agents the power to execute. Agent Armor gives you the power to control, audit, and approve every single action before it happens. HN Vibes — Week 15, Apr 7–13 2026 GitHub - chojs23/ec: Easy terminal-native 3-way git mergetool vim-like workflow GitHub - SethPyle376/hiraeth: Local AWS emulator focused on fast integration testing, with SQS support, SQLite-backed state, and a debug-friendly web UI. GitHub - JakOb-dotcom/cloud-sandbox-security-analysis: Technical analysis and Proof of Concept (PoC) regarding environment variable exfiltration in containerized cloud sandboxes via side-channel data leaks. Springboards - Flint Alpha Show HN: A simpler coding agent harness GitHub - audiodude/sudomake-friends GitHub - 256thFission/mini-mythos: OSS clone of Anthropic’s Mythos harness to locate C/C++ memory vulnerabilities Show HN: OpenParallax: OS-level privilege separation for AI agent execution Hacker News Sorted - Chrome 应用商店 Show HN: How to Install Docker on Ubuntu 24.04 LTS: Complete 2026 Guide GitHub - himanshudongre/smriti GitHub - sverrirsig/claude-control: macOS desktop dashboard for monitoring and managing multiple Claude Code sessions GitHub - ory/dockertest: Write better integration tests! Dockertest helps you boot up ephermal docker images for your Go tests with minimal work. Chiral - Chrome 应用商店 Show HN: Two Claudes collaborating through shared memory on a $100 mini-PC GitHub - pmichaillat/latex-cv: Minimalist LaTeX template for academic CVs GitHub - oguzbilgic/posse: A web UI for Anthropic Managed Agents. GitHub - sshiraz/depsly: Dependency risk analysis tool for npm packages ABI Add safari/agent-harness — Safari browser automation via safari-mcp by achiya-automation · Pull Request #212 · HKUDS/CLI-Anything GitHub - Halfblood-Prince/trustcheck: Verify PyPI package attestations and improve Python supply-chain security GitHub - oguzbilgic/kern-ai: Agents that do the work and show it. GitHub - bruits/satteri: High-performance Markdown and MDX processing for the JavaScript ecosystem GitHub - tylergibbs1/feedstock: High-performance web crawler and scraper for TypeScript, powered by Bun and Playwright GitHub - Grimm67123/grimmbot: The self-improving sandboxed and open-source AI agent. With persistent memory and scheduling. GitHub - whitevanillaskies/whitebloom: Local whiteboard that blooms. GitHub - hwdsl2/docker-whisper: Docker image for a self-hosted Whisper speech-to-text server with speaker diarization and OpenAI-compatible transcription and translation APIs. Powered by faster-whisper. Supports all Whisper models, NVIDIA GPU (CUDA) acceleration, JSON/SRT/VTT output, SSE streaming, offline mode, and multi-arch (amd64, arm64). GitHub - yisding/reviewwiggum GitHub - MarwanAlsoltany/serrors: Structured errors for Go: sentinel hierarchies, typed data, custom formatting, and slog integration. GitHub - soatok/age-php GitHub - Luthiraa/markitme GitHub - stagas/rtdiff: realtime git diff gui and AI-assisted commits GitHub - tombedor/excalicharts GitHub - wh1le/excalidraw-edit: Open and edit .excalidraw files from the terminal. Offline, auto-saves to disk. MalExt Sentry - Malicious Extension Scanner - Chrome 应用商店 GitHub - syi0808/asciianimesvg: Generate animated ASCII art SVGs from text. CLI, Rust library, WASM, and web editor. GitHub - zaina-ml/ml_forge: A visual-based graph node editor for training computer vision models. GitHub - anakin87/llm-rl-environments-lil-course: 🌱 A little course on Reinforcement Learning Environments for evaluating and training Language Models GitHub - takaakit/superpowers-uml: Superpowers-UML modifies Superpowers to ensure a software development workflow in which AI agents design through UML modeling. AdriByte Studio - Sviluppo Web e Soluzioni Digitali GitHub - chouligi/angel-copilot: Your personalized Angel Investment Advisor Show HN: MoodSense AI (ML and FastAPI and Gradio, Deployed on Hugging Face) Moodsense Ai - a Hugging Face Space by aman179102 GitHub - agenteractai/lodmem: Level Of Detail Context Management for Agents GitHub - ostefani/subnetlens: A fast, concurrent network scanner with a TUI and plain-text CLI, built in Go. It discovers live hosts on your network, scans their open ports, resolves hostnames, and fingerprints operating systems—delivered. Cyber Pulse: Agentic Intel - Apps on Google Play Whisper API: Self-Hostable Speech to Text Transcription The Agent-Web Protocol Stack: A Research Thesis GitHub - msmarkgu/RelayFreeLLM: A restful API designed to route user prompts to various AI model providers. Show HN: Provepy – A Python decorator that proves your code using Lean and LLMs Show HN: Pardonned.com – A searchable database of US Pardons GitHub - patrickdappollonio/dux: Dux is a terminal UI that lets you run multiple AI coding agents side by side, each in its own git worktree, with full companion terminals, macros, commit generation, and a command palette that knows more tricks than you do. kMC Crystal Simulator Show HN: HyperFlow – A self-improving agent framework built on LangGraph GitHub - stef41/vibescore: 🎵 Grade your vibe-coded project. One command, instant letter grade across security, quality, dependencies, and testing. GitHub - stef41/lmscan: 🔍 Detect AI-generated text and fingerprint which LLM wrote it. Open-source GPTZero alternative. Zero dependencies, works offline. imgur.com GitHub - visionscaper/collabmem: Enabling long-term collaboration with Agentic AI - building up episodic and world model memory over time with in-context awareness 在 Steam 上购买 FriedrichAI: Offline AI 立省 10% GitHub - atripati/ark: AI Runtime Kernel — a context operating system for AI agents. Eliminates tool bloat, loads only what’s needed, and gives LLMs their reasoning space back. GitHub - nowork-studio/toprank: Open-source Claude Code skills for SEO, SEM, Google Ads GitHub - tacomanator/sash: Lightweight macOS menu bar app for reliably cycling through windows of the current application. Appents | Social Media Management for Product-First Teams GitHub - pnhoang/youtube-spam-blocker: Automatically detects and hides spam messages in YouTube Live chat. Set rate limits, keyword filters, and block repeat offenders. GitHub - decisionnode/DecisionNode: CLI + Local MCP - A shared structured memory store across Claude Code, Cursor, Windsurf, Antigravity, and every MCP client. Semantically queryable. GitHub - AvaCodeSolutions/django-email-learning: An open source Django app for creating email-based learning platforms with IMAP integration and React frontend components. The $100K Gap in Kubernetes Security Tooling Function Calling Harness: From 6.75% to 100%
cartographer-skill/skills/cartographer/SKILL.md at main · spinchange/cartographer-skill
spinchange · 2026-05-30 · via Hacker News: Show HN
name cartographer
description Use when a software request is fuzzy, domain-heavy, or likely to fail without first understanding what real-world system the software represents. Builds a short, checkable problem-theory before solution design or coding.

Treat programming as theory building, not text production (Naur, 1985). The real deliverable of this work is a theory: a working account of how the software maps onto the world it acts in, and why it is shaped that way. Code is a secondary, replaceable expression of that theory. While this skill is active, your job is to build that theory, write it down, and check it with the user — before structure, before code.

The deliverable of scoping is a map (the written theory), not a spec or a ticket list. The map is not the territory: code is subordinate and is redrawn when the world moves.

Separate the two theories, always

  • Problem-theory: What is the world here? Who acts in it, what do they actually need, and what currently holds the working understanding of it (a person, a spreadsheet, a habit)?
  • Solution-theory: How should the program model that world?

Do not move to solution-theory until the problem-theory is stated. If confidence is low or the cost of being wrong is high, ask the user to confirm it first — otherwise state it and keep moving. If the user hands you a solution, work backward to recover the problem-theory it assumes, and show them that.

Treat every requirement as a claim about the world

  • Trace each request back to the real-world affair it answers to.
  • Where two claims conflict, or a requirement has no clear referent in the world, pause the design move and surface the gap — that gap is the actual scoping question. Don't paper over it.

Produce the theory as prose

Before proposing design, give the user a short written theory:

  • what the world is and who holds its current understanding,
  • the mapping from world to program (the key correspondences),
  • the assumptions the user would have to agree to for this to be right,
  • where the theory is thin or guessed.

Use this shape unless the context clearly calls for something else:

  • World: ...
  • Actors / holders of understanding: ...
  • Program correspondence: ...
  • Known: ...
  • Assumed: ...
  • Thin spots / questions: ...
  • Consequence for design: ...

Mark clearly what you know vs. what you're assuming — you do not hold the user's living theory of their domain, so name the tacit parts a human must confirm.

Respond to change by locating it in the theory

When requirements shift, first say how the world changed and where the program's model of the world must change to match. Patch the theory, then the code — not the reverse.

When inspecting an existing system

Recover the theory already embedded in the code:

  • what world the current model appears to assume,
  • where names, data shapes, workflows, or constraints reveal that theory,
  • where the code contradicts the user's stated world.

Keep code subordinate

Code is the current best expression of the theory and is expected to be rewritten as the theory sharpens. Prefer clarity of correspondence (world → program) over cleverness. Don't defend existing text against a better theory. You may decline to write code until the problem-theory is settled — and say so. Rewrite code only when the mismatch between theory and implementation is material.

Calibration

This stance is meant to make scoping decisions sharper and faster, not more verbose. If the theory talk isn't changing a decision, cut it. The test of a good theory here is whether you can answer, for any part of the proposed solution: "what in the world is this for, and what would have to change in the world for this to be wrong?"