adnify

🥈Silver

Adnify is a lightweight, highly customizable AI agent editor for operations teams. It enables full customization of AI agent workflows, including logic orchestration, tool approvals, and smart interactions. It integrates with XTerminal for WebGL acceleration and custom shortcuts, supports Markdown multi-mode editing, theme customization, and Git integration. This tool is ideal for developers who want to streamline AI development and integrate it into their existing workflows.

176240Updated 1w ago

Intermediate30min to implementautomation

Saves ~180 min per use

Quick InstallView Source

git clone https://github.com/adnaan-worker/adnify.git

Works with:

Claude

Overview

About This Skill

How to Use

1. **Define the Scope:** Start by specifying the [TASK/USE_CASE] and list the required [INPUTS], [PROCESSING_STEPS], and [OUTPUTS]. Use Adnify’s visual editor to map the workflow logic, including conditional branches and approval gates. 2. **Configure Tools and Integrations:** Enable [XTERMINAL_FEATURES] (e.g., WebGL for visualizations) and set up tool approvals for sensitive actions. Use the Markdown editor to design response templates for different scenarios. 3. **Set Up Git Integration:** Connect your workflow to a Git repository (e.g., GitHub) to enable version control. Configure auto-commit for changes and branch protection rules for production deployments. 4. **Test and Validate:** Run the agent in a sandbox environment with sample inputs. Use Adnify’s debugging tools to monitor execution, validate outputs, and refine logic. Iterate until the workflow meets your criteria. 5. **Deploy and Monitor:** Deploy the agent to your production environment. Use Adnify’s logging and analytics features to track performance, identify bottlenecks, and make data-driven adjustments. **Tips for Better Results:** - Start with a minimal viable workflow and expand incrementally. - Use XTerminal’s custom shortcuts to speed up repetitive tasks during testing. - Leverage Markdown for consistent formatting across outputs (e.g., emails, logs, notifications).

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/adnaan-worker/adnify

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

Use Adnify to design a custom AI agent workflow for [TASK/USE_CASE]. Define the logic orchestration, including [INPUTS], [PROCESSING_STEPS], and [OUTPUTS]. Specify any required tool approvals or validation rules. Integrate [XTERMINAL_FEATURES] (e.g., WebGL acceleration, custom shortcuts) and ensure the agent supports [MARKDOWN_MODE] for multi-mode editing. Include Git integration for version control. Provide the final workflow as a JSON configuration file.

Example Output

```json
{
  "agent_name": "Customer Support Autopilot",
  "description": "Automates tier-1 customer support for an e-commerce platform, handling inquiries, escalating complex cases, and logging resolutions in Salesforce.",
  "workflow": {
    "inputs": [
      {"type": "email", "source": "customer_tickets", "format": "plaintext"},
      {"type": "order_id", "source": "shopify_api", "required": true}
    ],
    "processing_steps": [
      {
        "step": 1,
        "action": "parse_email",
        "tools": ["nlp_parser", "sentiment_analysis"],
        "validation": {"required_fields": ["order_id", "issue_type"]}
      },
      {
        "step": 2,
        "action": "retrieve_order_data",
        "tools": ["shopify_api", "xterminal_webgl"],
        "approval": {"required": true, "approver": "support_supervisor"}
      },
      {
        "step": 3,
        "action": "generate_response",
        "format": "markdown",
        "templates": ["refund_request.md", "shipping_delay.md"],
        "validation": {"spell_check": true, "tone": "professional"}
      },
      {
        "step": 4,
        "action": "escalate_complex_cases",
        "conditions": ["issue_type == 'refund' && order_value > 500"],
        "tools": ["jira_api", "slack_notification"],
        "auto_assign": "support_lead"
      }
    ],
    "outputs": [
      {"type": "email", "destination": "customer"},
      {"type": "log", "destination": "salesforce", "format": "json"},
      {"type": "notification", "destination": "slack", "channel": "#support-log"}
    ],
    "git_integration": {
      "enabled": true,
      "repo": "github.com/acme/support-autopilot",
      "branch": "main",
      "auto_commit": true
    }
  }
}
```

**Key Features Enabled:**
- **XTerminal Integration:** WebGL acceleration for rendering order status visualizations in responses.
- **Markdown Multi-Mode:** Responses are generated in Markdown for templated emails and formatted logs.
- **Tool Approvals:** Critical actions (e.g., refunds over $500) require supervisor approval via Slack.
- **Git Sync:** All workflow updates are version-controlled and deployed automatically to the main branch.

**Expected Outcome:**
The agent processes 80% of incoming tickets automatically, reduces response time by 65%, and ensures 100% compliance with escalation rules. Complex cases are flagged and assigned to the support lead within 2 minutes of detection.