Anthropic is handing its Agent Skills standard, a folder-based format for teaching AI agents specific tasks, to the Agentic AI Foundation under the Linux Foundation. The goal is to keep the standard open and vendor-neutral, with a roadmap covering versioned releases and a formal proposal process.

• Over 70 agent platforms, including ChatGPT, Cursor, GitHub Copilot, and VS Code, have integrated Agent Skills since the standard was published in December 2025.
• Adoption is large: about 1 million skills published and nearly 280 million installed.
• The standard is donated along with its name, logo, GitHub organization, and agentskills.io domain, and anyone can use or contribute to it without joining the foundation.

A roundup of recent Anthropic posts on Twitter/X covering customizable Claude Code mods, the Opus 5.5 model with usage limit boosts, and the 2026-07-28 MCP spec release that makes the protocol stateless. The thread itself is a collection of tweets, so this is a digest rather than a single argument.

• Claude Code can now be modded through plugins, with examples like Token Weather (context window forecast) and Blast Radius (flags risky shell commands before they run).
• Opus 5.5 is reported as roughly 30% faster and 40% cheaper per task than Opus 5, becoming the default for paid plans, with 5-hour session limits raised 20% and a one-time usage reset available until Oct 22.
• MCP 2026-07-28 makes the protocol stateless, so remote servers can run on serverless or edge infrastructure and scale horizontally, and adds formal extensions like MCP Apps, Tasks, and Enterprise Managed Auth.

Paper2Agent automatically transforms static research papers into interactive AI agents that users can query in natural language, eliminating the need to manually install code, configure environments, or parse technical documentation. The system wraps a paper's methods, code, and data as an MCP (Model Context Protocol) server that connects to LLMs like Claude, letting researchers apply the paper's techniques to new problems without programming expertise.

• Paper2Agent solves a real friction point: even well-documented computational methods require substantial setup work (installing dependencies, understanding APIs, configuring parameters), which blocks adoption by researchers without strong technical skills. The system lets users ask questions like "interpret this variant's effect on chromatin accessibility" instead of wrestling with repository setup.
• The framework validates reproducibility by testing each tool against the original paper's reported results and figures, then locks those tools to prevent LLM hallucination and ensure consistent outputs. Every tool includes a code reference back to the original paper for transparency.
• Demonstrated agents successfully reproduced results from AlphaGenome (genomic variant interpretation), Scanpy (single-cell analysis), and TISSUE (spatial transcriptomics), then performed novel analyses like collaborating across multiple agents to prioritize a causal gene for psoriasis.

The article argues that the Model Context Protocol (MCP) offers a more effective way to connect large language models (LLMs) to services compared to Skills. While Skills can help with knowledge transfer, they create unnecessary complications, especially when they require command line interfaces (CLIs). The author advocates for using MCP to streamline service integration and improve user experience.

• MCP abstracts away implementation details (no local installs, auth is simpler, updates happen seamlessly), while Skills often push that complexity onto the user
• Skills requiring CLI execution break down for LLMs like ChatGPT that can't run command-line tools
• Skills introduce deployment headaches, secret management issues, and context bloat that MCP avoids
• Skills should be reserved for knowledge transfer, while MCP should handle actual service/API execution

Anthropic is launching Labs, a new team dedicated to developing experimental products that leverage the evolving capabilities of their AI model, Claude. With key leadership joining from Instagram and a focus on scaling successful innovations, Labs aims to explore and implement cutting-edge AI solutions while ensuring responsible growth.

• Anthropic launched a Labs team to incubate experimental products, led by Instagram co-founder Mike Krieger alongside Ben Mann, with Ami Vora heading Product
• Claude Code went from research preview to a billion-dollar product in six months
• MCP has surpassed 100 million monthly downloads and become the industry standard for AI-tool integration
• Anthropic also rolled out Claude for Healthcare, offering HIPAA-compliant infrastructure and integrations with Medidata and ClinicalTrials.gov