#llm/tool-calling

Anthropic say that Cowork can only access files you grant it access to—it looks to me like they’re mounting those files into a containerized environment, which should mean we can trust Cowork not to be able to access anything outside of that sandbox.

Update: It’s more than just a filesystem sandbox—I had Claude Code reverse engineer the Claude app and it found out that Claude uses VZVirtualMachine—the Apple Virtualization Framework—and downloads and boots a custom Linux root filesystem.

I recently learned that the summarization applied by the WebFetch function in Claude Code and now in Cowork is partly intended as a prompt injection protection layer via this tweet from Claude Code creator Boris Cherny:

Summarization is one thing we do to reduce prompt injection risk. Are you running into specific issues with it?

Subscribe [On agents using CLI tools in place of REST APIs] To save on context window, yes, but moreso to improve accuracy and success rate when multiple tool calls are involved, particularly when calls must be correctly chained e.g. for pagination, rate-limit backoff, and recognizing authentication failures.

Other major factor: which models can wield the skill? Using the CLI lowers the bar so cheap, fast models (gpt-5-nano, haiku-4.5) can reliably succeed. Using the raw APl is something only the costly "strong" models (gpt-5.2, opus-4.5) can manage, and it squeezes a ton of thinking/reasoning out of them, which means multiple turns/iterations, which means accumulating a ton of context, which means burning loads of expensive tokens. For one-off API requests and ad hoc usage driven by a developer, this is reasonable and even helpful, but for an autonomous agent doing repetitive work, it's a disaster.

We introduce the Berkeley Function Calling Leaderboard (BFCL), the first comprehensive and executable function call evaluation dedicated to assessing Large Language Models' (LLMs) ability to invoke functions. Unlike previous evaluations, BFCL accounts for various forms of function calls, diverse scenarios, and executability.