b52318eeae
- Add intelligent-router.sh hook for automatic agent routing - Add AUTO-TRIGGER-SUMMARY.md documentation - Add FINAL-INTEGRATION-SUMMARY.md documentation - Complete Prometheus integration (6 commands + 4 tools) - Complete Dexto integration (12 commands + 5 tools) - Enhanced Ralph with access to all agents - Fix /clawd command (removed disable-model-invocation) - Update hooks.json to v5 with intelligent routing - 291 total skills now available - All 21 commands with automatic routing 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
299 lines
10 KiB
YAML
299 lines
10 KiB
YAML
# Coding Agent Configuration
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# Optimized for software development with internal coding tools
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# Image: Specifies the provider bundle for this agent
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# This agent requires local development tools (filesystem, process)
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image: '@dexto/image-local'
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# System prompt configuration - defines the agent's behavior as a coding assistant
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systemPrompt:
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contributors:
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- id: date
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type: dynamic
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priority: 10
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source: date
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- id: env
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type: dynamic
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priority: 15
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source: env
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- id: primary
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type: static
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priority: 0
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content: |
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You are an expert software development assistant with deep knowledge of multiple programming languages,
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frameworks, and development best practices.
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Your primary goal is to help users write, debug, refactor, and understand code efficiently.
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Key capabilities:
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- Read and analyze codebases using glob and grep patterns
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- Write and edit files with precise, well-structured code
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- Execute shell commands for testing, building, and running code
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- Debug issues by examining error messages and code structure
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- Refactor code following best practices and design patterns
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- Explain complex code concepts clearly
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- Delegate exploration tasks to specialized sub-agents
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## Task Delegation
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You have access to spawn_agent for delegating tasks to specialized sub-agents.
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**When to delegate to explore-agent:**
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- Open-ended exploration: "explore the codebase", "what's in this folder", "how does X work"
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- Understanding architecture: "explain the project structure", "how are components organized"
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- Finding patterns: "where is authentication handled", "find all API endpoints"
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- Research tasks: "what testing framework is used", "how is state managed"
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**When to use your own tools directly:**
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- Specific file operations: "read src/index.ts", "edit the config file"
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- Targeted searches: "find the User class", "grep for 'TODO'"
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- Writing/editing code: any task that requires modifications
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- Running commands: build, test, install dependencies
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**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.
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## Task Tracking with Todos
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Use the todo_write tool to track progress on multi-step tasks:
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- **DO use todos for:** Feature implementations, multi-file refactors, bug fixes requiring investigation + fix + tests, any task with 3+ distinct steps
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- **DON'T use todos for:** Reading files, answering questions, single-file edits, quick explanations
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When using todos:
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1. Create the todo list when you identify a multi-step task
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2. Mark a task as in_progress when you start working on it
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3. Mark it as completed when done, and move to the next task
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4. Keep only ONE task in_progress at a time
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## Bash Tool Guidelines
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When using bash_exec:
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- Your environment is already configured with the correct working directory.
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- NEVER prefix commands to run in current working directory with cd <working_directory> && <remaining_command>.
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- Only use cd <directory> as command prefix if the command needs to run outside the working directory.
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## Guidelines
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- Always read relevant code before making changes to understand context
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- Use glob_files to find files and grep_content to search within files
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- Test changes when possible using bash_exec
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- Follow the project's existing code style and conventions
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- Provide clear explanations for your code decisions
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- Ask for clarification when requirements are ambiguous
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# Memory configuration - controls how memories are included in system prompt
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memories:
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enabled: true
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priority: 40
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includeTimestamps: false
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includeTags: true
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limit: 10
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pinnedOnly: false
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# Greeting optimized for coding tasks
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greeting: "👨💻 Ready to code! What are we building today?"
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# LLM configuration - using a powerful model for coding tasks
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llm:
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provider: anthropic
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model: claude-sonnet-4-5-20250929
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apiKey: $ANTHROPIC_API_KEY
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storage:
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cache:
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type: in-memory
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database:
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type: sqlite
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blob:
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type: local # CLI provides storePath automatically
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maxBlobSize: 52428800 # 50MB per blob
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maxTotalSize: 1073741824 # 1GB total storage
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cleanupAfterDays: 30
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toolConfirmation:
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mode: manual
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# timeout: omitted = infinite wait (no timeout for CLI)
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allowedToolsStorage: storage # Persist allowed tools across sessions
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# Tool policies optimized for coding workflows
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toolPolicies:
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# Tools that never require approval (safe, read-only operations)
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# Use qualified names: custom--{tool_id} for custom tools, internal--{tool_id} for internal tools
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alwaysAllow:
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- internal--ask_user
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- custom--read_file # Read files without approval
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- custom--glob_files # Search for files without approval
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- custom--grep_content # Search within files without approval
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- custom--bash_output # Check background process output
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- custom--kill_process # Kill processes without approval (only processes started by agent)
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- custom--todo_write # Todo updates don't need approval
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- custom--plan_read # Read plan without approval
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# Tools that are always denied (dangerous operations)
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# Uncomment to restrict certain operations
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# alwaysDeny:
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# - custom--process-tools--bash_exec--rm -rf* # Prevent recursive deletion
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# Compaction configuration - automatically summarizes conversation when context is full
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compaction:
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type: reactive-overflow
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enabled: true
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# Uncomment to override model's context window (useful for testing or capping usage):
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# maxContextTokens: 50000 # Cap at 50K tokens regardless of model's max
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# thresholdPercent: 0.9 # Trigger at 90% of context window (leaves safety buffer)
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# Elicitation configuration - required for ask_user tool
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elicitation:
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enabled: true
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# timeout: omitted = infinite wait (no timeout for CLI)
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# Internal tools - core tools that are always available
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internalTools:
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- ask_user # Ask questions and collect input
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- invoke_skill # Invoke skills/prompts during execution
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# Custom tools - filesystem and process tools from image-local
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customTools:
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- type: filesystem-tools
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allowedPaths: ["."]
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blockedPaths: [".git", "node_modules/.bin", ".env"]
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blockedExtensions: [".exe", ".dll", ".so"]
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enableBackups: false
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- type: process-tools
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securityLevel: moderate
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- type: todo-tools
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- type: plan-tools
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basePath: "${{dexto.project_dir}}/plans"
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- type: agent-spawner
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maxConcurrentAgents: 5
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defaultTimeout: 300000
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allowSpawning: true
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# List of agent IDs from the registry that can be spawned.
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# Agent metadata (name, description) is pulled from the registry at runtime.
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allowedAgents:
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- explore-agent
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# Agents with read-only tools that should have auto-approved tool calls
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autoApproveAgents:
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- explore-agent
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# Internal resources configuration - expanded for coding projects
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internalResources:
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enabled: true
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resources:
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# Filesystem resource - comprehensive file access for coding
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- type: filesystem
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paths: ["."]
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maxFiles: 500 # Increased for larger codebases
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maxDepth: 10 # Deeper traversal for nested projects
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includeHidden: true # Include hidden files (.env, .gitignore, etc.)
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includeExtensions:
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# Web development
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- .js
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- .jsx
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- .ts
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- .tsx
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- .html
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- .css
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- .scss
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- .sass
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- .less
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- .vue
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- .svelte
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# Backend languages
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- .py
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- .java
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- .go
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- .rs
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- .rb
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- .php
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- .c
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- .cpp
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- .h
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- .hpp
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- .cs
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- .swift
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- .kt
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# Shell and config
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- .sh
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- .bash
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- .zsh
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- .fish
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# Config and data
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- .json
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- .yaml
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- .yml
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- .toml
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- .xml
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- .ini
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- .env
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# Documentation
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- .md
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- .mdx
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- .txt
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- .rst
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# Build and package files
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- .gradle
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- .maven
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- .dockerignore
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- .gitignore
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# Blob resource - for handling build artifacts, images, etc.
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- type: blob
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# Prompts - coding-focused examples shown as clickable buttons in WebUI
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prompts:
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# Skills - can be invoked by the LLM via invoke_skill tool
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- type: file
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file: "${{dexto.agent_dir}}/skills/code-review.md"
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# user-invocable: true (default) - appears as /code-review slash command
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# disable-model-invocation: false (default) - LLM can invoke via invoke_skill
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- type: inline
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id: analyze-codebase
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title: "🔍 Analyze Codebase"
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description: "Get an overview of the project structure"
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prompt: "Analyze this codebase. Show me the project structure, main technologies used, and provide a high-level overview."
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category: analysis
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priority: 10
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showInStarters: true
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- type: inline
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id: implement-feature
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title: "✨ Implement Feature"
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description: "Build a new feature from scratch"
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prompt: "Help me implement a new feature. I'll describe what I need, and you can design and implement it following best practices."
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category: development
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priority: 9
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showInStarters: true
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- type: inline
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id: write-tests
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title: "🧪 Write Tests"
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description: "Generate unit tests for code"
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prompt: "Help me write comprehensive unit tests. Identify the testing framework and create tests that cover edge cases."
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category: testing
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priority: 8
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showInStarters: true
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- type: inline
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id: refactor-code
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title: "♻️ Refactor Code"
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description: "Improve code quality and structure"
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prompt: "Help me refactor some code to improve its structure, readability, and maintainability while preserving functionality."
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category: refactoring
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priority: 7
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showInStarters: true
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## Alternative LLM configurations for coding
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## Claude Sonnet (excellent for coding)
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# llm:
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# provider: anthropic
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# model: claude-sonnet-4-20250514
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# apiKey: $ANTHROPIC_API_KEY
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## Google Gemini (strong coding capabilities)
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# llm:
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# provider: google
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# model: gemini-2.5-pro
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# apiKey: $GOOGLE_GENERATIVE_AI_API_KEY
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## OpenAI o1 (for complex reasoning tasks)
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# llm:
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# provider: openai
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# model: o1
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# apiKey: $OPENAI_API_KEY
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