Anthropic said on Wednesday it will release its Agent Skills technology as an open standard, a strategic bet that sharing its approach to creating AI assistants more capable will cement the corporate's position within the fast-evolving enterprise software market.
The San Francisco-based artificial intelligence company also unveiled organization-wide management tools for enterprise customers and a directory of partner-built skills from firms including Atlassian, Figma, Canva, Stripe, Notion, and Zapier.
The moves mark a big expansion of a technology Anthropic first introduced in October, transforming what began as a distinct segment developer feature into infrastructure that now appears poised to grow to be an industry standard.
"We're launching Agent Skills as an independent open standard with a specification and reference SDK available at https://agentskills.io," Mahesh Murag, a product manager at Anthropic, said in an interview with VentureBeat. "Microsoft has already adopted Agent Skills inside VS Code and GitHub; so have popular coding agents like Cursor, Goose, Amp, OpenCode, and more. We're in lively conversations with others across the ecosystem."
Contained in the technology that teaches AI assistants to do specialized work
Skills are, at their core, folders containing instructions, scripts, and resources that tell AI systems learn how to perform specific tasks consistently. Slightly than requiring users to craft elaborate prompts every time they need an AI assistant to finish a specialized task, skills package that procedural knowledge into reusable modules.
The concept addresses a fundamental limitation of enormous language models: while they possess broad general knowledge, they often lack the precise procedural expertise needed for specialised skilled work. A skill for creating PowerPoint presentations, as an illustration, might include preferred formatting conventions, slide structure guidelines, and quality standards — information the AI loads only when working on presentations.
Anthropic designed the system around what it calls "progressive disclosure." Each skill takes only a number of dozen tokens when summarized within the AI's context window, with full details loading only when the duty requires them. This architectural alternative allows organizations to deploy extensive skill libraries without overwhelming the AI's working memory.
Fortune 500 firms are already using skills in legal, finance, and accounting
The brand new enterprise management features allow administrators on Anthropic's Team and Enterprise plans to provision skills centrally, controlling which workflows can be found across their organizations while letting individual employees customize their experience.
"Enterprise customers are using skills in production across each coding workflows and business functions like legal, finance, accounting, and data science," Murag said. "The feedback has been positive because skills allow them to personalize Claude to how they really work and get to high-quality output faster."
The community response has exceeded expectations, in response to Murag: "Our skills repository already crossed 20k stars on GitHub, with tens of hundreds of community-created and shared skills."
Atlassian, Figma, Stripe, and Zapier join Anthropic's skills directory at launch
Anthropic is launching with skills from ten partners, a roster that reads like a who's who of contemporary enterprise software. The presence of Atlassian, which makes Jira and Confluence, alongside design tools Figma and Canva, payment infrastructure company Stripe, and automation platform Zapier suggests Anthropic is positioning Skills as connective tissue between Claude and the applications businesses already use.
The business arrangements with these partners deal with ecosystem development quite than immediate revenue generation.
"Partners who construct skills for the directory accomplish that to reinforce how Claude works with their platforms. It's a mutually helpful ecosystem relationship just like MCP connector partnerships," Murag explained. "There are not any revenue-sharing arrangements right now."
For vetting latest partners, Anthropic is taking a measured approach. "We began with established partners and are developing more formal criteria as we expand," Murag said. "We wish to create a invaluable supply of skills for enterprises while helping partner products shine."
Notably, Anthropic shouldn’t be charging extra for the potential. "Skills work across all Claude surfaces: Claude.ai, Claude Code, the Claude Agent SDK, and the API. They're included in Max, Pro, Team, and Enterprise plans at no additional cost. API usage follows standard API pricing," Murag said.
Why Anthropic is making a gift of its competitive advantage to OpenAI and Google
The choice to release Skills as an open standard is a calculated strategic alternative. By making skills portable across AI platforms, Anthropic is betting that ecosystem growth will profit the corporate greater than proprietary lock-in would.
The strategy appears to be working. OpenAI has quietly adopted structurally an identical architecture in each ChatGPT and its Codex CLI tool. Developer Elias Judin discovered the implementation earlier this month, finding directories containing skill files that mirror Anthropic's specification—the identical file naming conventions, the identical metadata format, the identical directory organization.
This convergence suggests the industry has found a standard answer to a vexing query: how do you make AI assistants consistently good at specialized work without expensive model fine-tuning?
The timing aligns with broader standardization efforts within the AI industry. Anthropic donated its Model Context Protocol to the Linux Foundation on December 9, and each Anthropic and OpenAI co-founded the Agentic AI Foundation alongside Block. Google, Microsoft, and Amazon Web Services joined as members. The inspiration will steward multiple open specifications, and Skills fit naturally into this standardization push.
"We've also seen how complementary skills and MCP servers are," Murag noted. "MCP provides secure connectivity to external software and data, while skills provide the procedural knowledge for using those tools effectively. Partners who've invested in strong MCP integrations were a natural place to begin."
The AI industry abandons specialized agents in favor of 1 assistant that learns every little thing
The Skills approach is a philosophical shift in how the AI industry thinks about making AI assistants more capable. The normal approach involved constructing specialized agents for various use cases — a customer support agent, a coding agent, a research agent. Skills suggest a unique model: one general-purpose agent equipped with a library of specialised capabilities.
"We used to think agents in several domains will look very different," Barry Zhang, an Anthropic researcher, said at an industry conference last month, in response to a Business Insider report. "The agent underneath is definitely more universal than we thought."
This insight has significant implications for enterprise software development. Slightly than constructing and maintaining multiple specialized AI systems, organizations can put money into creating and curating skills that encode their institutional knowledge and best practices.
Anthropic's own internal research supports this approach. A study the corporate published in early December found that its engineers used Claude in 60% of their work, achieving a 50% self-reported productivity boost—a two to threefold increase from the prior yr. Notably, 27% of Claude-assisted work consisted of tasks that will not have been done otherwise, including constructing internal tools, creating documentation, and addressing what employees called "papercuts" — small quality-of-life improvements that had been perpetually deprioritized.
Security risks and skill atrophy emerge as concerns for enterprise AI deployments
The Skills framework shouldn’t be without potential complications. As AI systems grow to be more capable through skills, questions arise about maintaining human expertise. Anthropic's internal research found that while skills enabled engineers to work across more domains—backend developers constructing user interfaces, researchers creating data visualizations—some employees fearful about skill atrophy.
"When producing output is very easy and fast, it gets harder and harder to truly take the time to learn something," one Anthropic engineer said in the corporate's internal survey.
There are also security considerations. Skills provide Claude with latest capabilities through instructions and code, which implies malicious skills could theoretically introduce vulnerabilities. Anthropic recommends installing skills only from trusted sources and thoroughly auditing those from less-trusted origins.
The open standard approach introduces governance questions as well. While Anthropic has published the specification and launched a reference SDK, the long-term stewardship of the usual stays undefined. Whether it would fall under the Agentic AI Foundation or require its own governance structure is an open query.
Anthropic's real product is probably not Claude—it would be the infrastructure everyone else builds on
The trajectory of Skills reveals something essential about Anthropic's ambitions. Two months ago, the corporate introduced a feature that looked like a developer tool. Today, that feature has grow to be a specification that Microsoft builds into VS Code, that OpenAI replicates in ChatGPT, and that enterprise software giants race to support.
The pattern echoes strategies which have reshaped the technology industry before. Firms from Red Hat to Google have discovered that open standards could be more invaluable than proprietary technology — that the corporate defining how an industry works often captures more value than the corporate attempting to own it outright.
For enterprise technology leaders evaluating AI investments, the message is easy: skills have gotten infrastructure. The expertise organizations encode into skills today will determine how effectively their AI assistants perform tomorrow, no matter which model powers them.
The competitive battles between Anthropic, OpenAI, and Google will proceed. But on the query of learn how to make AI assistants reliably good at specialized work, the industry has quietly converged on a solution — and it got here from the corporate that gave it away.
