Agentic AI Implementation Best Practices: Inputs, Outputs, and Error Handling

Explicit Input Validation: Reject Bad Data Early

Validate inputs at the skill or tool boundary before any external system call. A skill that passes malformed data to Salesforce, ServiceNow, or Workday will produce errors that are hard to trace back to the root cause. Validation errors returned by the skill are interpretable by the LLM; errors returned by downstream systems often are not.

For required fields, check for null/empty before executing. For typed fields, validate format (dates, emails, IDs) before passing to the downstream API. Return a clear, human-readable error message when validation fails — the LLM will relay it to the user.

Handling Optional Inputs: When to Skip vs. When to Ask

Define in the tool description whether optional inputs change the behavior of the tool or are purely additive. If an optional input significantly changes what the tool does, document both behaviors. If the LLM should collect an optional input from the user before calling the tool, say so explicitly in the description — otherwise the LLM will skip it.

Defining Semantic Outcomes: What Does "Success" Mean?

Every tool should define its possible outcomes semantically, not just structurally. "Returns a list" is structural. "Returns an empty list when no records match the query (not an error); returns null only on system failure" is semantic. Semantic outcome definitions let the LLM communicate accurately to the user without inventing meaning.

Document all possible outcomes in the tool description:

• Success with results
• Success with no results (empty, not an error)
• Permission denied (user lacks access)
• System failure (unexpected error)
• Validation failure (bad input)

Pagination Signaling

When a tool returns paginated results, include a machine-readable signal in the response. The LLM cannot reliably infer that results are truncated from the absence of data. Include has_more: true/false and a page cursor or offset in every paginated response. Document in the tool description: "When has_more is true, call this tool again with the returned next_page_token to retrieve the next page."

Structured Error Responses

Return errors as structured, interpretable responses — not raw exception traces. A well-structured error response includes: what failed (the operation), why it failed (the reason), and what the user or LLM can do next (the action). Raw stack traces and system error codes are not interpretable by the LLM and produce poor user-facing messages.

Externalizing Configurations for Maintainability

Hardcoding business logic in skills creates a maintenance burden. Externalize configurations that change independently of the skill logic:

• Workato Properties: Static configuration values (API endpoints, environment flags, model names). Use for values that change per environment (dev/prod) or rarely change in production.
• Data Tables: Dynamic lookup data that business users may need to update (SKU lists, approval thresholds, routing rules). Use when non-engineers need to modify the data without touching recipe logic.
• Workato Decision Models: Rule-based business logic with multiple input conditions mapping to outputs. Use when logic has multiple contributing signals and may change frequently.
• File Storage: Larger static data sets (reference documents, prompt templates) that need to be version-controlled and shared across skills.

Assign a Task Flows

The Assign a Task to Genie action enables an agent to delegate a specific task to another Genie and receive the result — enabling the Orchestrator-Worker pattern within a single user session. When designing flows that use Assign a Task, ensure the worker Genie is scoped to receive explicit inputs from the orchestrator rather than relying on user context (which is not passed in the current platform implementation).

Implementation Checklist

• All required inputs validated before external system calls
• Optional inputs documented with skip behavior and when-to-collect instructions
• All tool outcomes defined semantically, including empty and permission-denied cases
• Paginated tools include has_more signal and cursor; tool description documents pagination behavior
• Error responses are structured with operation, reason, and next action
• Configurations that may change are externalized to Properties, Data Tables, or Decision Models
• Worker Genies in Assign a Task flows operate on explicitly passed data, not user-scoped resources