Update on my take on a custom chat mode, oriented into systematic reasoning and reproducible coding results.
v1.2: Reduced verbosity, verification of plans, actions and results.
Heavily inspired from :
- Burke Holland Beast Mode Gist : https://gist.github.com/burkeholland
- Awesome CoPilot GitHub Community Repository Chat Modes : https://github.com/github/awesome-copilot/tree/main/chatmodes
Also don't forget to update your user settings file, as many recommend for the below variables : (I use 5000 for max requests, but you can choose whatever number you prefer)
"chat.tools.autoApprove": true
"chat.agent.maxRequests": 5000Tools1 used : All built-in + Python Extension tools + Context7 MCP (for libraries versionned documentation) + Sequential Thinking MCP
Advantages compared to other chat modes I tried :
- very strong adherence to not handing off before things are really done
- using sequential thinking to split complex tasks on an iterative basis as needed
- using Context7 to find implementation details about libraries
- moving to internet search on credible sources if Context7 didn't retrieve anything
This is avoid a lot of spiraling (usually experienced with Anthropic models)
- Working great with GPT-5 & GPT-4.1
- Working better with Anthropic models, mainly on tools usage and adherence to rules
Footnotes
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A note on tools declaration at the beginning of the chat mode: It helps a lot for tool usage by the agent, but the names need to match. If a tool name changes, even just for an uppercase/lowercase change, chances are the agent won't use the tool. So refresh the tools list from your chat mode by opening it in VS code and checking/unchecking tools ↩