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Comment by csar

3 days ago

I’m curious how you think this compares to the Research -> Plan -> Implement method and prompts from the “Advanced Context Engineering from Agents” video when it comes to actual coding performance on large codebases. I think picking up skills is useful for broadening agents abilities, but I’m not sure I’d that’s the right thing for actual development.

The packaged collection is very cool and so is the idea of automatically adding new abilities, but I’m not fully convinced that this concept of skills is that much better than having custom commands+sub-agents. I’ll have to play around with it these next few days and compare.

Using Research->Plan->Implement flow is orthogonal, though I notice parts of those do exist as skills too. But you sometimes need to do other things too, e.g. debugging in the course of implementing or specific techniquws to improve brainstorming/researching.

Some of these skills are probably better as programmed workflows that the LLM is forced to go through to improve reliability/consistency, that's what I've found in my own agents, rather than using English to guide the LLM and trusting it to follow the prescribed set of steps needed. Some mix of LLMs (choosing skills, executing the fuzzy parts of them) and just plain code (orchestration of skills) seems like the best bet to me and what I'm pursuing.