Claude Skills vs Copilot Agents: Verdict

Key insights

• Experiment setup: I gave the same meeting description to a Claude Skill and a Copilot Agent, then built meeting-notes agents side by side to compare outputs.
  
• How they were built: I used the built-in Skill Creator for Claude and the Agent Builder for Copilot, fed both the same transcript and notes, and ran identical tests.
  
• Shared architecture: Both platforms follow the same core pattern of instructions, knowledge, and scope, so the design approach transfers between them.
  
• Main differences: Copilot gives in-app features like conversation starters and direct access to Teams transcripts, while Claude packages outputs as reusable files and composes sub-skills for multi-step tasks.
  
• When to choose each: Choose Claude for higher local autonomy and complex file workflows; choose Copilot for tight Microsoft integration and in-app assistance across Word, Excel, and Teams.
  
• Practical conclusion: Both handle meeting notes well, but pick based on your ecosystem and autonomy needs: Copilot for Microsoft-centered work, Claude for local control and reusable agent files.
  

Daniel Anderson [MVP] uploaded a YouTube video that directly compares building a meeting notes agent in parallel on two platforms: Claude and Microsoft Copilot. In the video, Anderson uses the same prompt and the same meeting transcript to create a side-by-side demonstration, showing how each environment handles instructions, knowledge, and output packaging. His aim is to test whether Claude Skills and Copilot Agents are functionally the same, and to surface practical differences for real users and teams. Overall, the video offers a clear, hands-on look at both workflows and the end results.

Project setup and methodology

Anderson begins by explaining the tool choices and the test plan, and then walks through the practical steps taken on each platform. He creates a Claude Skill using the built-in skill creator while simultaneously building a Copilot Agent with the Agent Builder, explicitly avoiding Copilot Studio to keep the comparison fair. He then feeds both agents the same meeting transcript and a set of notes to see how each system extracts actions, summaries, and follow-ups. This controlled setup helps isolate differences in design, integration, and output formatting.

Importantly, the author tests not only the outputs but also the developer experience, noting the time required to set up each agent and the clarity of the configuration steps. By keeping prompts and data identical, Anderson makes it possible to assess differences that come from platform behavior rather than prompt engineering. He also performs live tests to observe how the agents handle edge cases in the transcript, such as incomplete speaker labels and overlapping topics. These practical details make the comparison useful for teams evaluating either option for meeting automation tasks.

Functional comparison and output behavior

When comparing outputs, Anderson finds both platforms follow the same core pattern of instructions, knowledge, and scope, but they differ in how they present and reuse results. The Copilot Agent offers conversation starters and plugs directly into Teams transcripts, which makes it convenient inside the Microsoft ecosystem and useful for quick follow-ups. In contrast, the Claude Skill tends to package its results as reusable files and supports chaining skills to create sub-agents that handle multi-step workflows. As a result, Copilot feels integrated while Claude feels modular.

The video highlights that both agents can produce meeting summaries, action items, and suggested next steps, yet the tone and structure vary. Copilot often produces outputs formatted for immediate in-app use, such as draft replies or agenda updates, whereas Claude produces outputs that are easier to store or pass to other tools. These differences matter when teams must decide whether they prefer immediate in-context assistance or reusable artifacts for downstream automation.

Integration, privacy, and ecosystem trade-offs

Anderson also discusses trade-offs between ecosystem convenience and cross-platform flexibility, showing that the best choice depends on specific needs. Microsoft Copilot integrates tightly with Office apps and Teams, which reduces friction for organizations locked into that stack and accelerates workflows that depend on calendar and transcript access. Conversely, Claude emphasizes local sandboxing and plugin-based integration that can work with non-Microsoft tools, offering greater control over data flows and more autonomy for local file operations.

These distinctions bring practical trade-offs: relying on Copilot can simplify adoption and governance in M365 environments, while adopting Claude can improve privacy and multi-tool orchestration at the cost of deeper integration. Decision-makers must weigh factors such as data residency, IT controls, user experience, and the need for automation beyond core productivity apps. Anderson points out that neither approach is universally better; each fits a different set of organizational priorities.

Usability, developer experience, and scaling

From a builder’s perspective, Anderson notes that both platforms follow a familiar pattern but offer different tooling ergonomics. The Claude skill creator makes it straightforward to define reusable behaviors and to chain skills, which appeals to teams aiming for automation at scale and for complex local workflows. Meanwhile, the Copilot Agent builder guides users toward in-app actions and conversational starters, which can speed up deployment for common meeting and document tasks in enterprises.

However, there are challenges in scaling either approach: Copilot’s advantage is centralized access to enterprise content, but that can complicate governance and cost if many agents are created. Claude’s flexible skill model can scale across tools and platforms but demands careful design to avoid duplicated logic and to ensure safe access to sensitive files. Anderson emphasizes that thoughtful design, monitoring, and clear boundaries are essential regardless of the platform chosen.

Safety, limitations, and practical considerations

Finally, Anderson highlights the limitations and the need for oversight, showing that both systems can produce useful results but should not be treated as fully autonomous without review. Hallucinations, context loss across long transcripts, and differing output formats are recurring challenges that require human supervision or guardrails. Additionally, pricing and licensing models differ, so organizations should factor in long-term costs and compliance needs when planning deployment.

Overall, the video’s practical demonstration leads to a balanced conclusion: if you need tight Office integration and quick in-context actions, Copilot Agents are compelling; if you need file-level autonomy, cross-tool orchestration, or reusable artifacts, Claude Skills offer strengths. Anderson’s side-by-side test shows that the underlying pattern is similar, and the choice often comes down to ecosystem fit, privacy needs, and how much autonomy you are willing to delegate to an agent.

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