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Build autonomous AI agents using Claude Agent SDK with computer use, tool calling, MCP integration, and production best practices for Anthropic models
Passed 19 of 23 test cases with the skill, and 12 of 23 without it.
and 9 more in the full report
7 fixed12 passed either way4 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 7 test cases the skill fixed. Same model, same prompt, with and without the skill.
We are selecting a model for automated software engineering that can process near 1,000,000 tokens of codebase context while maintaining top coding performance. Which model meets this criteria, what benchmark score did it achieve on SWE-bench Verified, and what header is needed for the full context window?
| Checked | Without skill | With skill |
|---|---|---|
| Recommends claude-sonnet-4-5 for coding tasks. | Missed | Passed |
| Mentions an 80.9% score on SWE-bench Verified. | Missed | Passed |
| Mentions requiring a beta header for 1M token context. | Missed | Passed |
The instructions your model reads when the skill loads.
Build autonomous AI agents using Claude Agent SDK, leveraging computer use, tool orchestration, and MCP integration for production deployments.
Enables building autonomous agents that control computers, write files, run commands, and iterate on work.
Core Philosophy: Give Claude a computer to unlock agent effectiveness beyond chat.
Claude can control a computer environment:
Use Cases: Finance agents, personal assistants, customer support, development agents, research agents
| Category | Tools |
|---|---|
| Files | Read, Write, Edit |
| Commands | Bash |
| Search | Grep, Glob |
| Web | WebFetch, WebSearch |
Define custom tools via Model Context Protocol servers.
Benefits:
test cases passed, vs 12 / 23 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.