automation sop workflow builder

    1

    Transforms manual business processes into technical SOPs and structured automation blueprints.

    $5

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    Claude CodeClaude CodeCursorCursorCodex CLICodex CLIMuseMuseDotsDots+21 more

    automation sop workflow builder

    Example session with this skill installed

    I need to automate our customer refund process. Currently, support gets an email, checks the Stripe transaction, asks the manager for approval in Slack, then triggers the refund in Stripe.

    • Read your context and instructions
    • Compiled the automation sop workflow

    I have analyzed the customer refund process and mapped out both the operational SOP and the technical automation requirements.

    Customer Refund Process: SOP & Automation Blueprint

    Section A — Operational SOP

    StepActorActionDecision/Control
    1.0Support AgentReceive refund request via emailVerify order ID exists in DB
    2.0Support AgentLocate transaction in StripeControl: Match email to Stripe customer ID
    3.0ManagerReview refund request in SlackApproval: Required for amounts >$50
    4.0Support AgentExecute refund in Stripe dashboardControl: Input reason code
    5.0SystemSend confirmation email to customerAutomatic trigger

    Section B — Automation Blueprint

    Automation Scope
    • Step 1.0 & 2.0: Automated via Email Parser + Stripe Search.
    • Step 3.0: Semi-automated via Slack Block Kit for approval.
    • Step 4.0 & 5.0: Automated via Stripe API + SendGrid.
    Field Mappings
    • Source: Email Body -> Regex: Order ID: (\d+) -> Target: Stripe charge_id
    • Source: Manager Input -> Type: Boolean -> Target: Workflow Condition isApproved
    Error Handling & Fallbacks

    Stripe API Timeout: Retry 3 times (exponential backoff). On final failure, move to "Manual Intervention" queue in Zendesk.

    • Transaction Not Found: Post alert to #support-triage Slack channel with raw email attached.
    Phased Rollout Plan
    • Phase 1: Automate search and Slack notification. Manager still clicks refund in Stripe.
      • Success Criteria: Slack notification arrives within 30s of email.
      • Rollback: Disable webhook trigger in Email Parser.
    • Phase 2: Full API integration for refund execution.
    Validation Results
    • Ownership: PASS (Support/Manager assigned)
    • Recoverability: PASS (Zendesk fallback queue defined)
    • Clarity: PASS (Step-by-step logic mapped)
    • Operational Readiness: GAP (Monitoring dashboard for failed Stripe calls needs setup)

    Next steps

    1. Confirm if specific Stripe metadata fields (e.g., reason codes) need to be mapped.
    2. Define the exact Slack channel ID for manager approvals.
    3. Review the Zendesk fallback queue setup for failed automations.

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

    About this skill

    The problem

    Manual processes often live only as tribal knowledge, leading to inconsistent execution and scaling bottlenecks. Developers tasked with automating these workflows frequently lack the structured documentation needed to build reliable integrations without constant back-and-forth.

    What it does

    • Extracts actors, inputs, and decision logic from raw process descriptions or transcripts.
    • Identifies specific steps suitable for automation versus those requiring human judgment.
    • Generates detailed field mappings and data transformation rules for API integrations.
    • Defines error handling protocols, retry policies, and manual fallback queues for every automated step.
    • Produces a phased implementation roadmap with test cases and rollback plans.

    Why this beats prompting it yourself

    Generic prompts often miss the "boring" but critical details like ownership, exception handling, and data validation. This skill follows a rigorous 10-step verification procedure that forces the agent to audit for operational readiness and recoverability before delivering the plan.

    Use cases

    • Documenting a complex lead routing process for a sales operations team.
    • Mapping a legacy invoice approval workflow before migrating to a new ERP.
    • Creating technical specs for a Zapier or Make.com automation project.
    • Auditing tribal knowledge processes for single points of failure.

    Known limitations

    This skill produces documentation and architectural blueprints, not executable code or direct API configurations. It requires a clear description of the current tools in use to be effective.

    Does not generate executable code or configuration files. Effectiveness depends on the detail provided regarding current tools and manual steps.

    How to use

    1. 1

      Connect your agent to the Agensi MCP

      Copy the prompt and paste it into Claude, ChatGPT, Cursor or any agent that supports MCP. It sets up the connection for you. Manual setup

    2. 2

      Sign in to Agensi

      Your agent shows a sign-in link. Sign in and click Allow.

    3. 3

      Ask for what you need

      Your agent loads this skill and uses it on your task. It always asks before any payment.

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    Listed1 month ago

    What's inside

    Frequently Asked Questions

    This skill transforms raw process descriptions or meeting transcripts into structured technical blueprints, identifying specific automation triggers, data mappings, and error-handling protocols that generic prompts often overlook.

    You will receive a specialized AI agent workflow designed for major LLM platforms; it includes the logic to generate phased implementation roadmaps, test cases, and technical field mappings.

    While it defines the logic for tools like Zapier, Make.com, or custom APIs, the skill produces documentation and architectural specs rather than direct code or live integration files.

    Yes, the skill is designed to work with any business process, provided you can list the software tools currently in use and the basic steps performed by your team.

    Setup is instantaneous upon purchase; simply import the skill into your preferred AI agent environment and start by providing a description of the manual process you wish to document.

    The skill is built to be LLM-agnostic, though it performs best on high-reasoning models (like GPT-4 or Claude 3) that can handle the complex 10-step verification procedure required for technical accuracy.

    New in Workflow Automation