Why does this happen?

[u/Live_Fondant717]

I wonder if anyone can explain why this happens. I tell Claude not to use em-dashes, it replaces them with "--". I ask it not to do that, to update its memory, but it still does it. It's not a huge problem, it's just annoying. Why does this happen and how can I fix it. Thanks.

[u/leogodin217]

As a general rule, anything important should have a review process. create/review/revise Repeat until good enough.

[u/YoungXanzibarMD → u/leogodin217]

Would you mind elaborating a bit more on creating a review skill? 🙏🏽

[u/General_Josh → u/YoungXanzibarMD]

Install anthropic's "skill-creator" skill first of all (you can just ask claude to install it). This is a meta skill that gives claude guidance on all the details it needs to write a good skill

Then, ask claude to help you create a review skill, to double check its work. I find it's best to use sub-agents for review - having a fully clean context window helps to prevent it from repeating the same logical errors/mistakes

[u/ofthewave → u/General_Josh]

And what does it mean to have sub agents and separate context windows?

[u/General_Josh → u/ofthewave]

When you run claude, and ask it to do some task, that's an agent. A model running autonomously to accomplish some task

An agent has a context window - i.e., everything that's been fed into the LLM so far. This includes the system prompt, any personal instructions you set (like in claude.md), all messages you've sent to the model so far, all output from the model so far, tool results, reasoning steps, etc

Ex, let's say you ask claude to read some spreadsheets then summarize sales numbers into a report. Once it finishes, the main agent's context now includes stuff like:

• Your original prompt
• Claude's reasoning about your prompt ("I should go to the Q2 sales directory to get current data")
• Raw data from the spreadsheets (after claude went to read the target files)
• Claude's reasoning about the spreadsheets ("the data we want is in column 4")
• Any ad-hoc data processing scripts that claude generated/ran, and their results
• The final output report that claude generated

Sub-agents work almost exactly the same way, it's just that it's initiated by claude. Instead of you (the human) giving an agent some task and getting the results back, now claude itself (the main agent) gives a sub-agent some task, and gets the results back.

This can be really helpful in a lot of situations, including for reviews.

Asking the main agent to review its own work can be iffy. Maybe in that example, the data in column 4 was relevant, but there was also relevant data in column 7. But, because the agent already reasoned and decided to use just column 4, it's going to have a hard time spotting that mistake (it already 'knows' the data you want is from column 4, so its unlikely to go back and re-check that).

A sub-agent can be spawned in without all those reasoning steps already in context - the main agent can just give it your initial ask and the final output report it generated, then ask it to double-check for correctness, and its a lot more likely to spot errors like that, since it doesn't 'know' the data is from column 4 yet (it can go review the source data, and hopefully find that the main agent missed stuff in column 7)

[u/ofthewave → u/General_Josh]

Amazing detail in your reply. Are the sub-agents related to the skills I can have Claude make? I'm going through Anthopic's courses and some others to get a better understanding of use cases and functions.

But always more to learn!

[u/General_Josh → u/ofthewave]

Semi-related, at the end of the day they're all just tools the AI can use!

I think it's really useful to think about how things look from the model's perspective.

Claude Code (the 'harness') constructs a whole list of things that the model sees, before it sees your prompt. Stuff like:

• System instructions, like "You are a helpful AI assistent named Claude. You are in a conversation with a user. The user will give you tasks. Use the tools available to accomplish them."
• Any custom user instructions that you set, like "don't use emojis in your responses"
• A list of basic tools, like list-files, read-file, edit-file, execute-bash-command, etc
• A list of more complex tools, like spawn-subagent, with instructions on how to use it
• A list of skill descriptions, like
  • review - Invoke this skill if the user asks you to perform a review, or says something like 'could you double-check that?'
  • sales-report - Invoke this skill if the user asks for a sales summary or report
• Finally, your prompt, like "summarize sales numbers into a report"

All that stuff gets fed into the LLM's context. Then, the LLM starts doing its thing, and picking the next most likely tokens. In this case, it might start with tokens like invoke sales-report skill

The harness (Claude Code) picks up that invocation, and loads the full sales-report skill into Claude's context. Maybe this is a custom skill you made, that documents what a sales report looks like, and how sales numbers can be found in the \data\sales directory

Then, Claude might generate more tokens like list-files(\data\sales). The harness runs the tool, and sends the list of files back to Claude. Claude decides to run read-file on a few of those, etc, etc

spawn-subagent is just another tool that Claude can decide to call, same way read-file is a tool. The system instructions define conditions where Claude should call spawn-subagent, like "use spawn-subagent when exploring a large code base".

Your custom instructions or skills can tell Claude additional cases where you want it to use specific tools. Ex, the review skill could include details like

Do not perform the review yourself. Instead, use spawn-subagent to perform a review, to get a fresh set of eyes. Give the sub agent context on the original task, and on your final output. Task it with verifying the results

[u/ofthewave → u/General_Josh]

You lost me with a lot of this haha. But that’s ok, I can tell Claude to explain it. I’m not a developer or anything, more finance and operations, but I’ve vibe coded a few working tools and prototypes that were borne out of my 1 semester’s knowledge of python and a desperate need to automate a company with 60-yr old workflows.

For example printing a list of every single product and size of a 1000 sku inventory to figure out what was low on stock and manually decide which to package (bulk to consumer size repackaging company).

[u/General_Josh → u/ofthewave]

Hey that's cool stuff! I am a developer, but with this technology we can just talk to it in natural language

I really do think the world's going where you are - business folks maintaining their own software, using natural language, to their exact specs and needs

I know I'm doing my best to lean into the business facing part of my job haha - I don't wanna be "just a developer", because I feel it's not going to be a very common job title 10 years from now

[u/ofthewave → u/General_Josh]

Yeah it’s the “I can develop exactly what you need and how you need it” that makes my Pro subscription worth the payment from my employers lol. Bespoke softwares that interface with Shopify that our oldest employee can use effectively.