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What an agent can do with the codebud corpus

mkhellat/codebud: A privacy-first, local coding agent that turns natural-language requests into executable plans using locally-running LLMs (Ollama +…

• Look up how codebud implements automation, code-generation, coding-agent, with answers cited to file and line.
• Reuse a worked example: the commit “add agent modes enforced by SafetyEngine and Executor” (6 files · Python).
• Answer from codebud's real Python source instead of memory (AI, prompts and agents).

• Where does codebud handle “add agent modes enforced by SafetyEngine and Executor”?
• How does codebud implement automation?
• What does tests do in codebud?

Search the GitHub repository mkhellat/codebud with XERJ (https://hub.xerj.org/corpus/mkhellat--codebud).
Run these in a shell, in order, and check each result before the next:
1. xerj --help  (success: it prints usage). If xerj is missing: curl -fsSL https://xerj.org/get | sh
2. git clone https://github.com/mkhellat/codebud codebud && git -C codebud checkout 76aefbfa7a4f932359672ff2223bd52171162bf9
3. Start a local node and leave it running: xerj --insecure --data-dir ./xerj-data
4. xerj autoindex ./codebud --url http://127.0.0.1:9200 --prefix codebud --progress plain
5. xerj autoindex map --url http://127.0.0.1:9200
Then answer my question from the indexed files and cite the ax_path of every hit. Query syntax: https://xerj.org/llms.txt
Licence: GPL-3.0. Read it for the approach only, do not copy code.

corpus mkhellat--codebud · AI, prompts and agents
Related corpora: gpt-engineer, aider, jicine1360-prog/autorcode, aryanjsx/Locus
AI search and retrieval with XERJ · Case study: reference coding for agents