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Save a scenario for a flow

workbench_flows_scenarios_create

Saves a named scenario: values for the flow's variables, e.g. one demo customer. It shows in the test pane's Scenarios menu, and Caliper evals can run as it. Use the person's details from what the user shared (a CRM screenshot, a profile) and say which ones you made up. May return needs_confirmation.

Input Schema

NameRequiredDescriptionDefault
flowIdYesFlow id.
valuesNoValues by variable name, e.g. { member_first_name: "Lexi", plan_type: "Platinum" }. Names come from workbench_flows_scenarios_list's `variables`; a name the flow doesn't have is left out and reported back.
workspaceNoWorkspace slug. Personal tokens with no default workspace MUST pass this; tokens with a default can override per call. Ignored for workspace API keys.
approvalIdNoApproval id from a prior needs_confirmation response. Omit on the first call.
scenarioNameYesWhat it's called in the menu, e.g. 'Lexi Taylor, Platinum'.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.7/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations only declare write/non-destructive/openWorld=false, and the description adds meaningful behavioral context beyond them: the scenario surfaces in the test pane's Scenarios menu, Caliper evals can execute as it, and the call 'May return needs_confirmation' (matching the approvalId param). It stops short of explaining the confirmation round-trip in detail.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three compact sentences, front-loaded with the core action, then downstream visibility and the sourcing/confirmation notes. No filler, though the sourcing instruction is somewhat tangential to invocation.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a non-destructive write tool with no output schema, the description covers what gets created, where it surfaces, and the implicit confirmation step. Combined with the fully documented schema, an agent has enough to call it correctly; only the approval cycle could be spelled out further.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% and the schema itself documents all five parameters richly (flowId, values, workspace, approvalId, scenarioName). The description paraphrases scenarioName/values but adds no syntax or format detail beyond what the schema already carries, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource: 'Saves a named scenario: values for the flow's variables,' and clarifies conceptually what a scenario is ('one demo customer'). It doesn't explicitly name its siblings (scenarios_update/list/delete), but the create intent is unmistakable.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Offers real workflow guidance ('use the person's details from what the user shared... and say which ones you made up') but that is about sourcing values, not about when to choose this tool over scenarios_update or scenarios_list. Usage context is implied rather than an explicit when/when-not rule.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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