ai automation agent builder

    1

    Turns manual, multi-step digital workflows into rigorous AI agent architectures and technical specifications.

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    Works with the AI tools you already use

    Claude CodeClaude CodeCursorCursorCodex CLICodex CLIGitHub CopilotGitHub CopilotGemini CLIGemini CLI+20 more

    ai automation agent builder

    Example session with this skill installed

    I need to automate our invoice processing. We get PDFs in a shared inbox, need to extract data, check it against our SQL database, and then flag discrepancies for the finance team.

    • Read your context and instructions
    • Compiled the ai automation agent
    • Generated the UI component

    I have analyzed your invoice processing workflow. Below is the technical specification for the AI Automation Agent.

    Invoice Processing Agent Specification

    Workflow Summary

    The agent will monitor a shared inbox for incoming PDFs, use an LLM to extract structured billing data, validate that data against existing SQL records, and either update the database or escalate to the finance team via a human checkpoint.

    Agent Architecture (Sense-Think-Act)

    PhaseAction
    SensePoll IMAP inbox every 10 minutes for unread emails with PDF attachments.
    ThinkExtract line items via LLM; Compare totals/PO numbers against invoices table.
    ActUpdate SQL record status to 'Processed' or create a Jira ticket for manual review.

    Error Handling & Controls

    ActionRetry StrategyFallback / Escalation
    PDF Extraction3 attempts (Exponential backoff)Move file to /manual_review folder.
    SQL Lookup2 attempts (Jittered)Alert admin; set agent state to 'Paused'.
    Jira Creation5 attemptsLog locally and retry on next cycle.

    Feasibility Assessment

    DimensionScoreJustification
    ReliabilityHighStructured PDF data is stable; SQL schemas provide clear validation rules.
    UsefulnessHighEliminates manual data entry for ~80% of standard invoices.
    FeasibilityMediumRequires IMAP access and SQL service account credentials.
    SafetyHighNo payments are issued automatically; agent only updates status.

    Next steps

    1. Define the specific SQL schema for the invoices and purchase_orders tables.
    2. Select the LLM model for extraction (e.g., GPT-4o or Claude 3.5 Sonnet).
    3. Set up a dedicated IMAP service account for the agent.

    ai-automation-agent-builder.tsx

    TSX · React component

    Generated

    Example file from a real run - the skill writes it into your workspace.

    Connects securely to your tools. The creator never sees your data.

    What you get

    Design robust error handling and retry logic for brittle API automations.Map human-in-the-loop checkpoints for sensitive autonomous tasks.Create a sense-think-act architecture for multi-tool LLM agents.Validate the feasibility and safety of a proposed automation idea.

    About this skill

    The problem

    Manual, repetitive digital workflows drain developer time and introduce human error. Designing an AI agent to replace these processes is difficult because most attempts lack structured error handling, state management, and clear human escalation paths.

    What it does

    • Analyzes manual workflows across six dimensions including triggers, data flow, and decision logic.
    • Architects the agent loop using a Sense-Think-Act framework for consistent behavior.
    • Maps integrations between LLM logic and external tools via APIs, CLI, or browser automation.
    • Designs critical controls for idempotency, rate limiting, and failure recovery to prevent duplicate actions.
    • Generates a full technical specification ready for implementation, including a feasibility scorecard.

    Why this beats prompting it yourself

    Generic prompts often forget the "boring" parts of automation like retry strategies, state checkpoints, and safety guardrails. This skill enforces a rigorous architectural framework that ensures your agent doesn't just work in the happy path, but fails gracefully and safely in production.

    Use cases

    • Converting a multi-step customer support triage process into an autonomous agent.
    • Automating complex ETL pipelines that require LLM-based data classification and cleaning.
    • Designing an agent to monitor system logs and execute multi-tool remediation workflows.
    • Building a human-in-the-loop approval system for AI-generated marketing operations.

    Known limitations

    This skill produces architectural specifications and design logic, not production-ready code. It is not suitable for workflows requiring real-time human judgment at every single step.

    How to install

    Works the same in every agent - Claude, Cursor, Codex, Copilot and 20+ more.

    ~30 seconds
    1. 1

      Download the ZIP

      Free skills download straight away. Paid skills unlock right after purchase.

    2. 2

      Unzip into your skills folder

      Every agent reads skills from one folder on your machine. Drop the unzipped folder in there.

    3. 3

      Ask your agent to use it

      Restart the agent if it was already running. It picks the skill up automatically - no config needed.

    Skills folder by agent

    Click the path to copy it. Create the folder if it does not exist yet.

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