Agent skills, originally introduced by Anthropic in 2025, provide specialized knowledge to guide models on preferred task implementations. Although frontier models can deduce package behaviors by inspecting assembly metadata and cached documentation, this trial-and-error approach drains token budgets. Packaging skills solves this inefficiency by delivering clear, just-in-time usage guidance alongside the relevant binaries. These instructions follow the official agentskills.io SKILL.md format, using Markdown combined with YAML front matter as demonstrated in the markout package.
Key points
Bundling skills into packages ensures guidance arrives alongside binaries to match the ex…: Bundling skills into packages ensures guidance arrives alongside binaries to match the exact package version in use.
Delivering predefined instructions allows artificial intelligence agents to concentrate c…: Delivering predefined instructions allows artificial intelligence agents to concentrate computational resources directly on core business challenges.
Implementations like the markout package demonstrate how library maintainers can provide…: Implementations like the markout package demonstrate how library maintainers can provide version-tailored guidance for immediate application programming interface use.
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Agent skills were introduced by Anthropic in 2025 and have quickly become commonplace for AI-driven development. dotnet/skills and Impeccable skills are good examples. Agent skills are typically distributed via git repos. We’ve been working on skill delivery via NuGet packages and found that the approach can be effective. The common thread is that repos and packages are units of development that can be used as distribution vehicles for skills.
Skills solve two main problems: fill in gaps in model knowledge and can prescribe “our way” of approaching a task. New NuGet packages will always be ahead of model training and can benefit from just-in-time skill delivery.
Here’s a quick demo using the markout package, whch contains a set of skills:
We’ve done a lot of experimentation. We’ve found that agents (as a baseline behavior) are capable of finding content in the NuGet cache to learn about a package. This includes reading README.md
files and even writing throwaway programs that reflect over…
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