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run_scenario_11707

Trigger and interact with automation workflows by processing an array of text collections. Designed for integrating Make scenarios with AI systems to enhance task automation.

Instructions

Scenario Inputs: Array of Collections

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
arrayNo

Implementation Reference

  • Dynamic handler for all 'run_scenario_<ID>' tools, including 'run_scenario_11707'. Extracts scenario ID from tool name and executes the scenario via make.scenarios.run, returning outputs as JSON or error.
    server.setRequestHandler(CallToolRequestSchema, async request => {
        if (/^run_scenario_\d+$/.test(request.params.name)) {
            try {
                const output = (
                    await make.scenarios.run(parseInt(request.params.name.substring(13)), request.params.arguments)
                ).outputs;
    
                return {
                    content: [
                        {
                            type: 'text',
                            text: output ? JSON.stringify(output, null, 2) : 'Scenario executed successfully.',
                        },
                    ],
                };
            } catch (err: unknown) {
                return {
                    isError: true,
                    content: [
                        {
                            type: 'text',
                            text: String(err),
                        },
                    ],
                };
            }
        }
        throw new Error(`Unknown tool: ${request.params.name}`);
    });
  • src/index.ts:37-57 (registration)
    Dynamic registration of 'run_scenario_<ID>' tools via ListToolsRequestHandler. Filters on-demand scenarios, generates tool name 'run_scenario_11707' for ID 11707, description, and inputSchema.
    server.setRequestHandler(ListToolsRequestSchema, async () => {
        const scenarios = await make.scenarios.list(teamId);
        return {
            tools: await Promise.all(
                scenarios
                    .filter(scenario => scenario.scheduling.type === 'on-demand')
                    .map(async scenario => {
                        const inputs = (await make.scenarios.interface(scenario.id)).input;
                        return {
                            name: `run_scenario_${scenario.id}`,
                            description: scenario.name + (scenario.description ? ` (${scenario.description})` : ''),
                            inputSchema: remap({
                                name: 'wrapper',
                                type: 'collection',
                                spec: inputs,
                            }),
                        };
                    }),
            ),
        };
    });
  • remap utility converts Make's scenario input spec (Input type) to JSON Schema object used in tool inputSchema for 'run_scenario_11707'.
    export function remap(field: Input): unknown {
        switch (field.type) {
            case 'collection':
                const required: string[] = [];
                const properties: unknown = (Array.isArray(field.spec) ? field.spec : []).reduce((object, subField) => {
                    if (!subField.name) return object;
                    if (subField.required) required.push(subField.name);
    
                    return Object.defineProperty(object, subField.name, {
                        enumerable: true,
                        value: remap(subField),
                    });
                }, {});
    
                return {
                    type: 'object',
                    description: noEmpty(field.help),
                    properties,
                    required,
                };
            case 'array':
                return {
                    type: 'array',
                    description: noEmpty(field.help),
                    items:
                        field.spec &&
                        remap(
                            Array.isArray(field.spec)
                                ? {
                                      type: 'collection',
                                      spec: field.spec,
                                  }
                                : field.spec,
                        ),
                };
            case 'select':
                return {
                    type: 'string',
                    description: noEmpty(field.help),
                    enum: (field.options || []).map(option => option.value),
                };
            default:
                return {
                    type: PRIMITIVE_TYPE_MAP[field.type as keyof typeof PRIMITIVE_TYPE_MAP],
                    default: field.default != '' && field.default != null ? field.default : undefined,
                    description: noEmpty(field.help),
                };
        }
    }
  • Scenarios.run method: core API call to execute scenario 11707 with input arguments, returns execution outputs.
        async run(scenarioId: number, body: unknown): Promise<ScenarioRunServerResponse> {
            return await this.#fetch<ScenarioRunServerResponse>(`/scenarios/${scenarioId}/run`, {
                method: 'POST',
                body: JSON.stringify({ data: body, responsive: true }),
                headers: {
                    'content-type': 'application/json',
                },
            });
        }
    }
Behavior1/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It fails to describe any behavioral traits—such as whether it's read-only or destructive, what permissions are needed, or what the tool outputs—making it impossible for an agent to understand how the tool behaves.

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

Conciseness2/5

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

While concise with a single phrase, it's under-specified rather than efficiently structured. The description lacks essential information, making it ineffective—conciseness should not come at the cost of clarity, and this text fails to earn its place by adding value.

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

Completeness1/5

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

Given the complexity implied by 'run_scenario' and the lack of annotations, output schema, or schema descriptions, the description is completely inadequate. It doesn't explain the tool's purpose, behavior, parameters, or results, leaving critical gaps for agent invocation.

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

Parameters1/5

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

The schema description coverage is 0%, and the description only vaguely references 'Array of Collections' without explaining what 'Collections' are, what the 'text' property means, or how the array should be structured. It adds no meaningful semantics beyond the bare schema.

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

Purpose2/5

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

The description 'Scenario Inputs: Array of Collections' is vague and tautological—it restates the parameter name ('array') without specifying what the tool actually does. It mentions 'Scenario' but doesn't define what a scenario is or what action 'run' entails, failing to distinguish it from sibling tools like run_scenario_11422.

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

Usage Guidelines1/5

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

No guidance is provided on when to use this tool versus alternatives. The description offers no context, prerequisites, or exclusions, leaving the agent with no basis to choose between this and sibling tools like run_scenario_11652 or run_scenario_11704.

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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