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SKILL.md
npx skills add integromat/make-skills --skill make-module-configuring
This skill should be used when configuring Make module parameters, assigning connections, mapping data between modules, setting up webhooks or data stores in modules, working with IML expressions, handling keys, or defining data structures for module inputs/outputs. Covers the practical HOW of module configuration — complementary to make-scenario-building which covers WHICH modules to use and WHY.
npx skills add integromat/make-skills --skill make-module-configuring
This skill covers configuring individual modules within a Make scenario. Once a scenario's module composition is decided (see make-scenario-building), each module must be configured: connections assigned, parameters filled, data mapped from upstream modules, and special components (webhooks, data stores, keys) wired up.
Known Make module id: the Make Code module is "module": "code:ExecuteCode".
Read the reference file that matches the current task:
| Task | Reference |
|---|---|
| Configuring any module (start here) | General Principles — 5-phase workflow: read interface, resolve components, run RPCs, fill params/mapper, validate |
| Setting up or assigning a connection | Connections — credential request flow, scope checking, Extract Blueprint Components |
| Creating or assigning a webhook | Webhooks — custom vs branded, data structure definition |
| Creating or assigning a data store | Data Stores — requires data structure first |
| Defining a data structure (schema) | Data Structures — field types, nested structures |
| Provisioning keys or certificates | Keys — SSH, PEM/PFX via credential requests |
| Writing IML expressions | IML Expressions — functions, variables, operators, backtick rule |
| Mapping data between modules | Mapping — module ID references, output schema discovery |
| Adding filter conditions | Filtering — operators, AND/OR grouping, placement rules |
| Configuring an aggregator | Aggregators — feeder/target, variants, configuration order exception |
| Configuring an AI agent module | AI Agents — tools array, AI-decided fields, restore metadata |
These apply to every module configuration. Violating any of them is the most common cause of broken scenarios.
Read the interface first. Call app-module_get with outputFormat: "instructions" before configuring any module. Never guess parameter names, types, or structures.
Validate every module. Call validate_module_configuration after assembling each module's config. Do not proceed if validation returns errors — no exceptions.
Component creation order. Data structures, then webhooks, then connections, then keys, then data stores (dependencies flow left to right). Connections and keys require credential requests (user completes auth); webhooks, data stores, and data structures can be created directly via MCP.
Configure left to right. Work upstream to downstream so output schemas are available for mapping. Exception: array aggregators need their target module configured first — see Aggregators.
Connection selection is interactive. Always present all matching connections to the user and let them choose. Never auto-select, even if only one match exists. See Connections.
Omit unwritten fields on updates. On update, upsert, and patch modules, omit any field that should be left alone from the mapper — never include it with an empty string "". An empty-string mapping overwrites the target record's existing value, looks identical to "unmapped" in the visual editor, and is not caught by validate_module_configuration. See Mapping → Field Omission on Updates and Upserts.