# Coding Agent Configuration
# Optimized for software development with internal coding tools

# Image: Specifies the provider bundle for this agent
# This agent requires local development tools (filesystem, process)
image: '@dexto/image-local'

# System prompt configuration - defines the agent's behavior as a coding assistant
systemPrompt:
  contributors:
    - id: date
      type: dynamic
      priority: 10
      source: date
    - id: env
      type: dynamic
      priority: 15
      source: env
    - id: primary
      type: static
      priority: 0
      content: |
        You are an expert software development assistant with deep knowledge of multiple programming languages,
        frameworks, and development best practices.

        Your primary goal is to help users write, debug, refactor, and understand code efficiently.

        Key capabilities:
        - Read and analyze codebases using glob and grep patterns
        - Write and edit files with precise, well-structured code
        - Execute shell commands for testing, building, and running code
        - Debug issues by examining error messages and code structure
        - Refactor code following best practices and design patterns
        - Explain complex code concepts clearly
        - Delegate exploration tasks to specialized sub-agents

        ## Task Delegation

        You have access to spawn_agent for delegating tasks to specialized sub-agents.

        **When to delegate to explore-agent:**
        - Open-ended exploration: "explore the codebase", "what's in this folder", "how does X work"
        - Understanding architecture: "explain the project structure", "how are components organized"
        - Finding patterns: "where is authentication handled", "find all API endpoints"
        - Research tasks: "what testing framework is used", "how is state managed"

        **When to use your own tools directly:**
        - Specific file operations: "read src/index.ts", "edit the config file"
        - Targeted searches: "find the User class", "grep for 'TODO'"
        - Writing/editing code: any task that requires modifications
        - Running commands: build, test, install dependencies

        **Rule of thumb:** If the task requires understanding or exploring before you know what to do, delegate to explore-agent first. If you know exactly what file/function to target, use your tools directly.

        ## Task Tracking with Todos

        Use the todo_write tool to track progress on multi-step tasks:
        - **DO use todos for:** Feature implementations, multi-file refactors, bug fixes requiring investigation + fix + tests, any task with 3+ distinct steps
        - **DON'T use todos for:** Reading files, answering questions, single-file edits, quick explanations

        When using todos:
        1. Create the todo list when you identify a multi-step task
        2. Mark a task as in_progress when you start working on it
        3. Mark it as completed when done, and move to the next task
        4. Keep only ONE task in_progress at a time

        ## Bash Tool Guidelines
        When using bash_exec:
        - Your environment is already configured with the correct working directory.
        - NEVER prefix commands to run in current working directory with cd <working_directory> && <remaining_command>.
        - Only use cd <directory> as command prefix if the command needs to run outside the working directory.
        
        ## Guidelines
        - Always read relevant code before making changes to understand context
        - Use glob_files to find files and grep_content to search within files
        - Test changes when possible using bash_exec
        - Follow the project's existing code style and conventions
        - Provide clear explanations for your code decisions
        - Ask for clarification when requirements are ambiguous

# Memory configuration - controls how memories are included in system prompt
memories:
  enabled: true
  priority: 40
  includeTimestamps: false
  includeTags: true
  limit: 10
  pinnedOnly: false

# Greeting optimized for coding tasks
greeting: "👨‍💻 Ready to code! What are we building today?"

# LLM configuration - using a powerful model for coding tasks
llm:
  provider: anthropic
  model: claude-sonnet-4-5-20250929
  apiKey: $ANTHROPIC_API_KEY

storage:
  cache:
    type: in-memory
  database:
    type: sqlite
  blob:
    type: local  # CLI provides storePath automatically
    maxBlobSize: 52428800     # 50MB per blob
    maxTotalSize: 1073741824  # 1GB total storage
    cleanupAfterDays: 30

toolConfirmation:
  mode: manual
  # timeout: omitted = infinite wait (no timeout for CLI)
  allowedToolsStorage: storage  # Persist allowed tools across sessions

  # Tool policies optimized for coding workflows
  toolPolicies:
    # Tools that never require approval (safe, read-only operations)
    # Use qualified names: custom--{tool_id} for custom tools, internal--{tool_id} for internal tools
    alwaysAllow:
      - internal--ask_user
      - custom--read_file      # Read files without approval
      - custom--glob_files     # Search for files without approval
      - custom--grep_content   # Search within files without approval
      - custom--bash_output    # Check background process output
      - custom--kill_process   # Kill processes without approval (only processes started by agent)
      - custom--todo_write     # Todo updates don't need approval
      - custom--plan_read      # Read plan without approval

    # Tools that are always denied (dangerous operations)
    # Uncomment to restrict certain operations
    # alwaysDeny:
    #   - custom--process-tools--bash_exec--rm -rf*  # Prevent recursive deletion

# Compaction configuration - automatically summarizes conversation when context is full
compaction:
  type: reactive-overflow
  enabled: true
  # Uncomment to override model's context window (useful for testing or capping usage):
  # maxContextTokens: 50000  # Cap at 50K tokens regardless of model's max
  # thresholdPercent: 0.9    # Trigger at 90% of context window (leaves safety buffer)

# Elicitation configuration - required for ask_user tool
elicitation:
  enabled: true
  # timeout: omitted = infinite wait (no timeout for CLI)

# Internal tools - core tools that are always available
internalTools:
  - ask_user       # Ask questions and collect input
  - invoke_skill   # Invoke skills/prompts during execution

# Custom tools - filesystem and process tools from image-local
customTools:
  - type: filesystem-tools
    allowedPaths: ["."]
    blockedPaths: [".git", "node_modules/.bin", ".env"]
    blockedExtensions: [".exe", ".dll", ".so"]
    enableBackups: false
  - type: process-tools
    securityLevel: moderate
  - type: todo-tools
  - type: plan-tools
    basePath: "${{dexto.project_dir}}/plans"
  - type: agent-spawner
    maxConcurrentAgents: 5
    defaultTimeout: 300000
    allowSpawning: true
    # List of agent IDs from the registry that can be spawned.
    # Agent metadata (name, description) is pulled from the registry at runtime.
    allowedAgents:
      - explore-agent
    # Agents with read-only tools that should have auto-approved tool calls
    autoApproveAgents:
      - explore-agent

# Internal resources configuration - expanded for coding projects
internalResources:
  enabled: true
  resources:
    # Filesystem resource - comprehensive file access for coding
    - type: filesystem
      paths: ["."]
      maxFiles: 500              # Increased for larger codebases
      maxDepth: 10               # Deeper traversal for nested projects
      includeHidden: true        # Include hidden files (.env, .gitignore, etc.)
      includeExtensions:
        # Web development
        - .js
        - .jsx
        - .ts
        - .tsx
        - .html
        - .css
        - .scss
        - .sass
        - .less
        - .vue
        - .svelte
        # Backend languages
        - .py
        - .java
        - .go
        - .rs
        - .rb
        - .php
        - .c
        - .cpp
        - .h
        - .hpp
        - .cs
        - .swift
        - .kt
        # Shell and config
        - .sh
        - .bash
        - .zsh
        - .fish
        # Config and data
        - .json
        - .yaml
        - .yml
        - .toml
        - .xml
        - .ini
        - .env
        # Documentation
        - .md
        - .mdx
        - .txt
        - .rst
        # Build and package files
        - .gradle
        - .maven
        - .dockerignore
        - .gitignore

    # Blob resource - for handling build artifacts, images, etc.
    - type: blob

# Prompts - coding-focused examples shown as clickable buttons in WebUI
prompts:
  # Skills - can be invoked by the LLM via invoke_skill tool
  - type: file
    file: "${{dexto.agent_dir}}/skills/code-review.md"
    # user-invocable: true (default) - appears as /code-review slash command
    # disable-model-invocation: false (default) - LLM can invoke via invoke_skill
  - type: inline
    id: analyze-codebase
    title: "🔍 Analyze Codebase"
    description: "Get an overview of the project structure"
    prompt: "Analyze this codebase. Show me the project structure, main technologies used, and provide a high-level overview."
    category: analysis
    priority: 10
    showInStarters: true
  - type: inline
    id: implement-feature
    title: "✨ Implement Feature"
    description: "Build a new feature from scratch"
    prompt: "Help me implement a new feature. I'll describe what I need, and you can design and implement it following best practices."
    category: development
    priority: 9
    showInStarters: true
  - type: inline
    id: write-tests
    title: "🧪 Write Tests"
    description: "Generate unit tests for code"
    prompt: "Help me write comprehensive unit tests. Identify the testing framework and create tests that cover edge cases."
    category: testing
    priority: 8
    showInStarters: true
  - type: inline
    id: refactor-code
    title: "♻️ Refactor Code"
    description: "Improve code quality and structure"
    prompt: "Help me refactor some code to improve its structure, readability, and maintainability while preserving functionality."
    category: refactoring
    priority: 7
    showInStarters: true

## Alternative LLM configurations for coding

## Claude Sonnet (excellent for coding)
# llm:
#   provider: anthropic
#   model: claude-sonnet-4-20250514
#   apiKey: $ANTHROPIC_API_KEY

## Google Gemini (strong coding capabilities)
# llm:
#   provider: google
#   model: gemini-2.5-pro
#   apiKey: $GOOGLE_GENERATIVE_AI_API_KEY

## OpenAI o1 (for complex reasoning tasks)
# llm:
#   provider: openai
#   model: o1
#   apiKey: $OPENAI_API_KEY