AI 资讯
Designing Production-Grade OpenClaw Skills: Schemas, Tool Calling, and Dynamic Dispatch
Original Article published on ZeroLabs . Designing Production-Grade OpenClaw Skills: Schemas, Tool Calling, and Dynamic Dispatch Key Takeaway: A deep engineering walkthrough on creating modular, reusable skills for OpenClaw agents with strict JSON schemas, fallback execution paths, and error telemetry. Structured verification, strict boundaries, and deterministic tooling prevent production failure. Implemented directly across the ZeroLabs and OpenClaw platform architecture. Image credit: labs.zeroshot.studio Why this matters: Engineering reliable systems requires moving past unstructured prompts into hardened execution contracts. Contents What is an OpenClaw skill? How do you structure the SKILL.md specification? How do you implement reliable Python tool scripts? What is dynamic dispatch and context management? FAQ What is an OpenClaw skill? In OpenClaw, a skill is a self-contained directory containing instructions, configuration schemas, and executable scripts. Instead of writing monolithic prompts that describe every possible task, skills allow agents to discover, load, and execute specialized capabilities on demand. flowchart TD A[User Request] --> B[OpenClaw Router Agent] B -->|Matches Capability| C[Load skill: domain-seo-audit] C --> D[Read SKILL.md Frontmatter & Rules] D --> E[Execute Scoped Python Script / Tool] E --> F[Return Formatted Output to Context] How do you structure the SKILL.md specification? Every skill must reside in its own subdirectory under skills/<skill-name>/ with a root SKILL.md file: --- name : domain-seo-audit description : " Scans a target URL for Core Web Vitals, OpenGraph tags, and indexability issues." version : 1.0.0 parameters : type : object properties : url : type : string format : uri description : " The full target URL to audit (including https://)." check_mobile : type : boolean default : true description : " Whether to emulate mobile viewport checks." required : - url --- # Domain SEO Audit Skill ## Overview Use this skill whe
AI 资讯
Taming Vibe-Coded Technical Debt: Automated Test Harnesses for AI-Generated Repos
Original Article published on ZeroLabs . Taming Vibe-Coded Technical Debt: Automated Test Harnesses for AI-Generated Repos Key Takeaway: A pragmatic strategy for refactoring AI-generated codebases, eliminating dead boilerplate, and establishing regression test harnesses before shipping to production. Structured verification, strict boundaries, and deterministic tooling prevent production failure. Implemented directly across the ZeroLabs and OpenClaw platform architecture. Image credit: labs.zeroshot.studio Why this matters: Engineering reliable systems requires moving past unstructured prompts into hardened execution contracts. Contents What causes vibe-coded technical debt? How do you build a safety test harness? What is the 4-step refactoring loop for AI code? How do you clean dead dependencies and boilerplate? FAQ What causes vibe-coded technical debt? AI coding models are optimized to satisfy the user's immediate prompt. When asked to add a feature, models often take the path of least resistance: Copy-Pasting Logic : Duplicating utility functions across multiple files rather than importing shared modules. Swallowing Errors : Wrapping fragile database or network calls in broad try/except: pass blocks. Dependency Sprawl : Installing heavy npm packages or Python libraries for trivial single-line operations. flowchart TD A[Vibe Coded Prototype] --> B[Generate Smoke & Contract Tests] B --> C[Run Static Analysis & Linters] C --> D[Identify Duplication & Dead Imports] D --> E[Scoped AI Refactor on Single Module] E --> F[Run Test Suite] F -->|Pass| G[Commit Refactor] F -->|Fail| E How do you build a safety test harness? Before asking an AI agent to clean up or refactor an existing repository, you must write automated smoke tests that verify critical user journeys. If you don't have tests, ask the agent to write tests before modifying any implementation code: # tests/test_smoke_endpoints.py import pytest import httpx BASE_URL = ' http://localhost:3000 ' def test_homepage
AI 资讯
Context Engineering with Claude Code: The Spec-First Pipeline for Production Codebases
Original Article published on ZeroLabs . Context Engineering with Claude Code: The Spec-First Pipeline for Production Codebases Key Takeaway: How to structure markdown specification files, linting contracts, and context boundaries to eliminate hallucinated refactors when coding with Claude Code and modern CLI agents. Structured verification, strict boundaries, and deterministic tooling prevent production failure. Implemented directly across the ZeroLabs and OpenClaw platform architecture. Image credit: labs.zeroshot.studio Why this matters: Engineering reliable systems requires moving past unstructured prompts into hardened execution contracts. Contents What is the problem with unstructured conversational prompting? How does the Spec-First Pipeline work? What belongs in a production feature spec? How do you enforce automated verification loops? FAQ What is the problem with unstructured conversational prompting? When developers ask CLI coding agents to 'Fix the user profile page' or 'Refactor our database queries' , the model must guess which files to edit, what interfaces to preserve, and how to verify correctness. This ambiguity leads to three common failure modes: Collateral Damage : The agent modifies unrelated utility functions, introducing silent regressions across the codebase. Context Saturation : The agent reads dozens of unnecessary files, exhausting its context window and forgetting the primary objective. Premature Completion : The agent claims a task is complete without running linters, compilers, or test suites. flowchart TD A[Feature Request / Bug] --> B[Draft SPEC.md in Repo] B --> C[Review Interface & Target Files] C --> D[Feed Spec to Claude Code / CLI Agent] D --> E[Agent Edits Code in Target Files] E --> F[Run Deterministic Test Suite] F -->|Tests Fail| E F -->|Tests Pass| G[Commit & Open PR] How does the Spec-First Pipeline work? The Spec-First Pipeline replaces open-ended chatting with a deterministic three-stage workflow: Stage Artifact Action O
AI 资讯
Google’s revived nuclear power plant gets $1.9B loan from US government
Google said it would bring an Iowa nuclear power plant back from the dead. Now, the plant's owner is getting a $1.9B loan from the U.S. Energy Department.
科技前沿
Nintendo is releasing a 40th anniversary Legend of Zelda Switch 2 on October 29
No, the Zelda anniversary edition Switch 2 doesn't come with a copy of Ocarina of Time.
AI 资讯
Pusheen’s first game is coming to Apple Arcade
Pusheen is getting her first game, and it will appear exclusively on Apple Arcade. Launching October 1st, Pusheen's Place lets you collect and care for more than 100 Pusheens as you play minigames and decorate rooms for Pusheenicorn, Pancake Pusheen, and other variations of the cartoon cat. In the mix of minigames, you'll "sort color […]
AI 资讯
Chrome is now shipping updates every 2 weeks as AI changes the security landscape
Google is speeding up Chrome’s release schedule to ship security patches and new features faster.
AI 资讯
JBL’s soundbar with detachable rear speakers is over $300 off
A lot of people are split between getting a nice all-in-one soundbar or spending more for an option that includes rear satellites for immersive surround sound. JBL’s Bar 700 Mark 2 system is one of the most unique options available, shipping with two modular speakers that charge when docked to the soundbar. When detached, the […]
创业投融资
The Switch 2 remake of The Legend of Zelda: Ocarina of Time arrives November 5
We're heading back to Link's original 3D adventure ahead of next year's live action Zelda movie.
科技前沿
Steam Deck vs. Switch 2 — which gaming handheld is more powerful?
The Switch 2 is newer and more affordable than the Steam Deck, but Valve's console still has serious power to draw on.
创业投融资
Nintendo’s Ocarina of Time remake launches in November
Link's next adventure now has a release date. During a Legend of Zelda stream for the franchise's 40th anniversary, Nintendo announced that the upcoming Ocarina of Time remake for the Switch 2 is launching on November 5th. The release date makes Ocarina of Time one of just a few big-budget titles launching in the same […]
AI 资讯
Mistral raises €3B as sovereign AI becomes big business
The French AI lab has raised €3 billion at a €21 billion valuation in a Series D round led by Samsung, Scaleup Europe and PSG Equity.
安全
A hacker stole $340M in a crypto heist, then returned most of it
The latest heist is one of the largest thefts of cryptocurrency to date.
AI 资讯
Nuclear startup Bluecore Energy raises $50M seed round, just two months after launch
Bluecore Energy announced Tuesday an oversubscribed $50 million seed round — just months after raising a $10 million pre-seed and coming out of stealth.
AI 资讯
A word with a woman who’s trying to pull off a crossbody phone strap
Oh, this thing? It's just a crossbody strap. It's a fun and youthful way to carry your phone. It's all the rage with Europeans and young people. I love it, and I definitely don't feel weird and self-conscious using it. Plus, it's great to have a $700 investment dangling near your waist while you walk […]
开发者
What is considered good speed for home internet and how can you test it?
The speed of your downloads, uploads and ping are affected by several variables. Let's measure your internet speed and see if we can improve it.
科技前沿
Richard Kelly on Donnie Darko at 25: ‘It’s a Miracle That Any Movie Gets Made’
The director discusses his debut novel, staying true to an artistic vision, and the absurd line of dialogue from Donnie Darko he believes will find its way into his obituary.
AI 资讯
Presentation: Platform Engineering in the Age of AI
The panelists explain how platform teams adapt to support AI-assisted engineering, highlighting which capabilities belong in the platform. They discuss trade-offs between standardization and developer autonomy, while sharing strategies to manage AI tooling, security guardrails, and shifting workflows. By Stéphane Di Cesare, Davide de Paolis, Stephen Cihak, Camila Macedo, Renato Losio
AI 资讯
HashiCorp Packer 1.16 Adds Native SLSA Provenance Generation and Verification for Machine Images
HashiCorp has released Packer v1.16.0, adding native support for generating, signing, and verifying SLSA provenance attestations for every image the tool builds. The release provides teams with a secure, tamper-proof record of how a machine image was made. It does this without needing extra supply-chain tools. By Claudio Masolo
AI 资讯
Google’s Atlas of the human genome could pave the way for new treatments
Google DeepMind has unveiled an AI tool that its scientists claim could help unravel the mysteries of the human genome and transform our understanding of biology, accelerating scientific research and ultimately paving the way for new treatments for diseases. The platform, called AlphaGenome Atlas, contains a "predictive map of every possible DNA letter change in […]