dotai

🥈Silver

Dotai is a context manager for AI agents, enabling integration and management of multiple agents within operations workflows. It connects to Claude and other AI tools, allowing teams to automate complex tasks and improve efficiency.

1,151830Updated 2w ago

Intermediate30min to implementautomation

Saves ~45 min per use

Quick InstallView Source

git clone https://github.com/udecode/dotai.git

Works with:

Claude

Overview

About This Skill

https://github.com/udecode/dotai

How to Use

1. **Define Your Workflow**: Identify the specific process you want to automate (e.g., lead qualification, invoice processing, bug triage). List the steps and decision points in your current manual process. 2. **Select Your Agents**: For each step in your workflow, choose the appropriate AI agent type: - *Intake Agent*: For initial data processing (e.g., parsing emails, extracting fields from documents) - *Verification Agent*: For cross-referencing data (e.g., checking CRM, validating contracts) - *Action Agent*: For taking final steps (e.g., sending notifications, updating systems) 3. **Configure Interactions**: Use dotai's context manager to define how agents pass data between each other. Set up error handling for common failure points (e.g., API timeouts, missing data). 4. **Test the Pipeline**: Run the workflow with sample inputs to verify: - Data flows correctly between agents - Error cases are handled gracefully - Outputs match your requirements 5. **Deploy and Monitor**: Connect your workflow to real systems (e.g., CRM, email, APIs) and set up monitoring to track performance. Use dotai's logging features to audit agent decisions. **Pro Tips:** - Start with a small, well-defined process before scaling - Use Claude Code for agents that need to execute code or interact with files - For complex workflows, break the process into smaller sub-workflows - Document each agent's input/output contracts to ensure compatibility

Use Cases

Generate comprehensive app design documentation to streamline development processes.

Automate the creation and updating of technology stack documentation for better project management.

Utilize the debugging framework to identify and resolve issues in code systematically.

Create and manage pull requests with detailed descriptions and automated reviews.

Setup & Installation

Quick Install

No install command available. Check the GitHub repository for manual installation instructions.

Alternative Install (Git Clone)

git clone https://github.com/udecode/dotai

Requirements

Claude Code or compatible AI agent
Works with: Claude

Quick Start Guide

Install the Skill

Copy the install command above and run it in your terminal.

Open Your AI Agent

Launch Claude Code, Cursor, or your preferred AI coding agent.

Try It Out

Use the prompt template or examples below to test the skill.

Customize

Adapt the skill to your specific use case and workflow.

Usage Examples

Prompt Template

Set up a dotai context manager workflow to automate [TASK/PROCESS]. Define the following agents: [AGENT_1_ROLE], [AGENT_2_ROLE], and [AGENT_3_ROLE]. Configure their interactions to handle [SPECIFIC_INPUTS] and produce [DESIRED_OUTPUTS]. Include error handling for [COMMON_FAILURE_POINTS].

Example Output

### Dotai Workflow Setup: Customer Support Escalation Automation

**Workflow Name:** Support Ticket Escalation Pipeline
**Trigger:** New ticket created in Zendesk with priority=high or tags=urgent

**Agent Configuration:**
1. **Intake Agent** (Claude Code):
   - Role: Analyze incoming tickets for completeness and urgency
   - Input: Raw ticket data from Zendesk API
   - Output: Structured ticket object with priority score (1-10) and required actions
   - Example Output: `{"ticket_id": "ZEN-12345", "priority": 8, "actions": ["verify customer contract", "check SLA compliance"], "assigned_agent": "support_team_lead"}`

2. **Verification Agent** (Claude Code + Python):
   - Role: Cross-reference ticket details with CRM and contract database
   - Input: Structured ticket object from Intake Agent
   - Output: Updated ticket with contract validity, SLA status, and customer history
   - Example Output: `{"ticket_id": "ZEN-12345", "contract_valid": true, "sla_breach_risk": "high", "customer_tier": "enterprise", "escalation_path": "account_manager"}`

3. **Escalation Agent** (Claude Desktop + Slack API):
   - Role: Initiate escalation protocol based on verification results
   - Input: Verified ticket object from Verification Agent
   - Output: Escalation notification to Slack channel #escalations and update ticket status
   - Example Output: `{"escalation_triggered": true, "notified_parties": ["@account_manager", "@support_director"], "ticket_status": "escalated", "timestamp": "2024-05-15T14:32:15Z"}`

**Error Handling:**
- If Verification Agent fails to access CRM: Intake Agent retries with cached contract data
- If Escalation Agent fails to notify Slack: System logs error and sends email alert to ops team
- If priority score is ambiguous: Default to manual review by senior agent

**Integration Points:**
- Zendesk API (webhook trigger)
- Salesforce CRM (contract verification)
- Slack API (notifications)
- Internal logging system (audit trail)

**Success Metrics:**
- 95% of high-priority tickets escalated within 15 minutes
- 0% data loss during agent handoffs
- 20% reduction in manual escalation work