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Emergence DeepSeek TUI Multi-Agent Programming Assistant

Development Updated 2026.08.30

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About this skill

Problem

In multi-agent workflows, handing a complex coding task directly to a model often fails in two ways: the model lacks file context and guesses at interfaces, or it explores the repository and runs commands in interactive mode while the caller lacks clear boundaries. If the difference between deepseek exec and deepseek run is not made explicit, teams may treat headless mode as tool execution or interactive mode as plain text completion.

How It Works

This skill separates the two modes into different delegation strategies:
- deepseek exec: headless mode. It produces text output only, cannot access the file system, and cannot truly execute tools. It is suited for cases where the host agent has already read the relevant files and provided interfaces, types, and insertion points.
- deepseek run: interactive mode. It can use tools such as list_files, read_file, write_file, terminal, and grep, making it suitable for autonomous workspace exploration, file editing, and build commands.

The key steps are: have the host read the relevant code first, build a compact prompt, verify the returned snippet, apply it with a targeted patch, and finish with compilation or type checking.

Boundaries

Tool-call text in exec output is model reasoning, not actual execution. Use run for cross-file refactoring or unknown dependency investigation. Use exec for tightly controlled small changes, keep prompts around 10KB, and avoid asking for full-file rewrites in one call.

Use Cases

  • After the host agent reads target file interfaces, call deepseek exec to generate JSX snippets and apply them with patch
  • Use deepseek run in a local workspace to read project files, search code, and run build commands to locate compile errors
  • For precise insertions in a skill page, prepare CommandBlock interfaces, examples, and insertion points before calling exec
  • When the model returns full-file rewrites or hallucinated interfaces, extract only verified snippets and cross-check before applying

Best For

  • Engineers maintaining OpenClaw or Hermes workflows who need controlled code generation for host agents
  • Frontend engineers iterating on components who want model-generated JSX snippets that can be patched
  • Full-stack engineers prototyping with TUI terminals who want autonomous file reads, command execution, and build fixes
  • Architects defining multi-agent delegation rules who need clear boundaries between headless exec and interactive run