agentpool system prompt

--- sync: agent: doc_sync_agent dependencies: - src/agentpool_config/system_prompts.py title: System Prompts description: System prompt configuration and library icon: material/text-box --- ## Overview AgentPool's prompt library allows defining reusable system prompts that can be shared across agents. Prompts are defined in the `prompts` section of your configuration and can be referenced by name. System prompts define agent behavior, personality, and methodology. You can configure prompts using: - **Static prompts**: Inline text content - **File prompts**: Load from external files with Jinja2 templating - **Library prompts**: Reference shared prompts from the library - **Function prompts**: Dynamically generate prompts using Python functions ## Basic Structure ```yaml --8<-- "docs/configuration/prompts_example.yml" ``` ## Prompt Categories System prompts can be categorized by their purpose: - **Role**: Define WHO the agent is (e.g., "expert developer", "data scientist") - **Methodology**: Define HOW the agent works (e.g., "step-by-step", "analytical") - **Tone**: Define communication STYLE (e.g., "professional", "friendly") - **Format**: Define output STRUCTURE (e.g., "markdown", "structured") ## Configuration Reference /// mknodes {{ "agentpool_config.system_prompts.PromptConfig" | union_to_markdown(display_mode="yaml", header_style="pymdownx") }} /// ## Complete Example ```yaml prompts: system_prompt: # Role definitions technical_expert: category: role content: | You are a technical expert specializing in: - Software development best practices - System architecture and design - Code review and quality assurance # Methodology definitions systematic: category: methodology content: | Follow this systematic approach: 1. Understand requirements fully 2. Break down complex problems 3. Apply best practices consistently 4. Validate results thoroughly # Tone definitions professional: category: tone content: | Maintain professional communication: - Use formal, precise language - Be respectful and constructive - Provide clear explanations agents: senior_dev: model: gpt-4 system_prompt: - "Specialize in Python and TypeScript development." - type: library reference: technical_expert - type: library reference: systematic - type: library reference: professional - type: file path: "prompts/coding_style.j2" ``` ## Organization Best Practices ### File Structure Keep prompts organized in separate files: ```yaml # prompts/roles.yml prompts: system_prompt: technical_expert: category: role content: ... # prompts/styles.yml prompts: system_prompt: professional: category: tone content: ... # agents.yml INHERIT: - prompts/roles.yml - prompts/styles.yml agents: my_agent: system_prompt: - type: library reference: technical_expert - type: library reference: professional ```