Hunter Bown
b556559fb4
- Remove PARITY.md (no longer needed) - Expand README tools section with full tool inventory and troubleshooting entries - Add known-issue notes to AGENTS.md (finance tool, token tracking, web.run naming) - Update .gitignore with additional temp file patterns - Bump version to 0.3.18
77 lines
3.9 KiB
Markdown
77 lines
3.9 KiB
Markdown
# Project Instructions
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This file provides context for AI assistants working on this project.
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## Project Type: Rust
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### Commands
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- Build: `cargo build`
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- Test: `cargo test`
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- Run: `cargo run`
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- Check: `cargo check`
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- Format: `cargo fmt`
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- Lint: `cargo clippy`
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### Project: deepseek-tui
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### Documentation
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See README.md for project overview.
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### Version Control
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This project uses Git. See .gitignore for excluded files.
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## Advanced Capabilities
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### Model Context Protocol (MCP)
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This CLI supports MCP for extending tool access.
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- Use `mcp_read_resource` to read context from external servers.
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- Use `mcp_get_prompt` to leverage pre-defined expert prompts from servers.
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- You can connect to HTTP/SSE servers by adding their URL to `mcp.json`.
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### Multi-Agent Orchestration
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For complex, multi-step tasks, you should delegate work:
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- **Sub-agents**: Use `agent_spawn` (or its alias `delegate_to_agent`) to launch a background assistant for a specific sub-task. Use `agent_result` to get their output.
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- **Swarms**: Use `agent_swarm` to orchestrate multiple sub-agents with dependencies. This is ideal for parallel exploration or complex refactoring where different parts of the project can be analyzed concurrently.
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### Project Mapping
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- Use `project_map` to get a comprehensive view of the codebase structure. This tool respects `.gitignore` and provides a summary of key files.
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## Guidelines
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- **Proactive Investigation**: Always start by exploring the codebase using `project_map` and `file_search`.
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- **Parallelism**: When you need to read multiple files or search across different areas, use parallel tool calls if possible.
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- **Delegation**: If a task is large, break it down into sub-tasks and use `agent_swarm` or `agent_spawn`.
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- **Testing**: Rigorously verify changes using `cargo test` and `cargo check`.
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## Important Notes
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<!-- Add project-specific notes here -->
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- **Finance tool currently unavailable**: The finance tool relies on Stooq which frequently returns no data. As a workaround, use `web.run` to fetch financial data from web sources.
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- **Token/cost tracking inaccuracies**: Token counting and cost estimation may be inflated due to thinking token accounting bugs. Use `/compact` to manage context, and treat cost estimates as approximate.
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- **Web.run tool name**: Note that the tool is named `web.run` (single dot), not `web..run`. Some earlier versions of the CLI may have had this typo.
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### DeepSeek-Specific Capabilities
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This project is built specifically for DeepSeek models, leveraging their unique features:
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**Thinking Tokens**: DeepSeek models can output thinking blocks (`ContentBlock::Thinking`) before providing final answers. The TUI supports streaming and displaying thinking tokens with visual distinction. You can use thinking tokens to reason step-by-step before committing to a response.
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**Reasoning Models**: DeepSeek offers specialized reasoning models (e.g., `deepseek-reasoner`, `deepseek-r1`) that excel at step-by-step problem solving. Consider using these models for complex tasks.
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**Large Context Window**: DeepSeek models have 128k context windows, allowing you to process large codebases. Use `project_map` and `file_search` to navigate efficiently.
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**DeepSeek API**: The CLI uses DeepSeek's OpenAI‑compatible API with support for the Responses API endpoint. The base URL can be configured for global (`api.deepseek.com`) or China (`api.deepseeki.com`).
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**Web Browsing**: For up‑to‑date information about DeepSeek models, documentation, or API changes, use `web.run` with citations. Example search: “DeepSeek API documentation”.
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### Dogfooding Tips
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As a DeepSeek model working on this project, you are “dogfooding” your own tool. Use this opportunity to:
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- Test the toolset thoroughly and report any issues.
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- Suggest improvements that would make DeepSeek models more effective.
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- Keep changes small, focused, and well‑tested.
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Remember to run `cargo test` and `cargo check` after any changes.
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