Yiyun_dan1

2/
/The strongest aspect of /loop is not "timing".
But these 4 steps:
Execute
See the result
Auto-fix
Re-execute
Until the task is complete.
If your workflow for a task is originally:
"Run -> Check errors -> Fix -> Run again"
Then it’s very suitable to delegate to /loop.

3/ It is best suited for two types of tasks:
Tasks that are repetitive but easy to forget
Such as checking PRs, running tests, synchronizing documentation
Tasks that require repeated trial and error
Such as fixing bugs, adding tests, large-scale refactoring, technical migration
Essentially, /loop handles "circulation."

6/
I think the 4 most practical scenarios are:
Automatically monitoring PR status
Running tests on a schedule and attempting to fix issues
Syncing code changes to documentation
Performing refactoring/migration that requires multiple rounds of validation
Especially for the 4th category, the user experience improvement is very noticeable.

7/ But /loop is not mindless opening.
It is best suited for tasks with "clear completion criteria," such as:
All tests passing
0 lint errors
PR status checks completed
Documentation synchronized
The more vague the goal, the easier it is to spin wheels and burn tokens.

One sentence:
/loop is not a "timer".
It’s more like an automatic execution loop in Claude Code.
If something essentially requires:
Execute -> Verify -> Correct -> Re-execute
Then don’t keep an eye on it manually, just use /loop.

In a VPN case involving more than 3 million yuan, the parties were arrested on charges of "providing tools for intrusion and illegal control of computer information systems."
The lawyer argued that VPNs are essentially encrypted transmission tools, designed to bypass interception, and do not have malicious functions such as intrusion or control of computer information systems. Therefore, even if there is illegality, it does not necessarily constitute a crime.
In the end, the prosecution accepted the relevant opinions, the public security authorities withdrew the case, and the case was dism

Recently, many people have been asking why their personal Anthropic accounts get banned.
I’ve summarized the common situations, which mainly fall into these categories:
Obvious illegal or violations of rules
This goes without saying; almost all AI companies handle this, and Anthropic is no exception.
Various proxy or sharing behaviors
Especially multi-account usage, polling calls, reselling, relay stations, carpooling—these are essentially high-risk behaviors.
Registering or accessing from unsupported regions
If the registration environment, login environment, or usage region is outside the of

Microsoft has turned multi-Agent orchestration into a framework, with comprehensive engineering capabilities and extension interfaces. It's ideal for teams looking to systematically build Agents to focus on.

This project turns web crawling, cleaning, and structured extraction into a complete set of AI-era data infrastructure—students working on Agents and RAG should definitely focus on it.

Google's open-source TimesFM has turned time series forecasting into a foundation model. Anyone working on quantification, operational forecasting, or demand prediction should take a look.