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Coalesce-Software-Inc

coalesce-transform-mcp

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Create Workspace Node from Scratch

create_workspace_node_from_scratch

Create a standalone workspace node with no upstream dependencies. Use only for nodes that truly lack predecessors, after discovering the correct node type via plan_pipeline.

Instructions

Create a workspace node from scratch with NO predecessors. Only use this when the node truly has no upstream nodes — for example, a standalone utility node. If the node has ANY upstream/source nodes, use create_workspace_node_from_predecessor instead.

REQUIRED: Before calling this tool, call plan_pipeline with goal + repoPath to discover the correct nodeType. Do not guess or hardcode node types — the planner ranks all available types and returns the best match.

SPECIALIZED TYPES WARNING: Do NOT use Dynamic Tables, Incremental Load, Materialized View, or other specialized types unless the user explicitly requests that pattern (e.g., 'near-real-time refresh', 'incremental processing'). For standard batch ETL, CTE decomposition, and general transforms, use Stage or Work. The response includes nodeTypeValidation.warning if a specialized pattern was detected without matching context.

Defaults to completionLevel='configured', which REQUIRES both name and metadata.columns to be provided. If you don't have column definitions yet, set completionLevel to 'created' or 'named' instead.

AUTOMATIC CONFIG: When repoPath is provided, this tool automatically runs intelligent config completion after creation — reading the node type definition, setting node-level config defaults, and applying column-level attributes. The configCompletion result shows what was applied.

Do not use overrideSQL or override.* fields; SQL override is disallowed in this project.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
goalNoThe goal or intent for this node (e.g., 'deduplicate customer records', 'aggregate daily sales'). Used to validate that the chosen nodeType is appropriate for the task. Same value you would pass to plan_pipeline.
nameNoOptional node name to apply after creation.
configNoOptional config object to apply after creation.
changesNoOptional additional partial fields to merge after the node is created and fetched.
metadataNoOptional metadata object to apply after creation, including metadata.columns.
nodeTypeYesThe type of node to create. IMPORTANT: Call plan_pipeline first to discover and rank available node types — use the nodeType from its result. Format: 'PackageName:::ID' for package types (e.g., 'base-nodes:::Stage') or simple name ('Stage') for built-in types. Always prefer the package-prefixed format returned by plan_pipeline.
repoPathNoPath to local Coalesce repository for automatic config completion after creation.
descriptionNoOptional node description to apply after creation.
workspaceIDYesThe workspace ID
completionLevelNoHow complete the node should be before the tool returns. Defaults to configured.
storageLocationsNoOptional storageLocations array to apply after creation.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
nodeIDNo
createdNo
warningNo
nextStepsNo
validationNo
joinSuggestionsNo
configCompletionNo
nodeTypeValidationNo
configCompletionSkippedNo
Behavior4/5

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

Annotations already indicate non-readOnly and openWorld. The description adds key behavioral details: default completionLevel requiring name and columns, automatic config completion when repoPath is provided, disallowed override fields, and warning responses. This substantially enriches transparency beyond annotations.

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?

The description is relatively long but every sentence adds value. It is front-loaded with purpose and usage, uses bold and caps for warnings, and organizes information logically. Given the tool's complexity, the length is justified and it remains focused.

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

Completeness5/5

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

Given the tool's 11 parameters, nested objects, and output schema, the description covers prerequisites, edge cases, completion behaviors, automatic config, disallowed fields, and response warnings comprehensively. It leaves no significant gaps for an AI agent to infer.

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

Parameters4/5

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

Schema coverage is 100%, so baseline is 3. The description adds context about how parameters interact (completionLevel requires name and columns, nodeType should come from plan_pipeline, repoPath triggers automation) and prerequisites (goal used for validation), going beyond the schema's individual descriptions.

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

Purpose5/5

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

The description explicitly states 'Create a workspace node from scratch with NO predecessors,' clearly distinguishing it from the sibling tool create_workspace_node_from_predecessor. It provides specific examples (standalone utility node) and specifies when not to use it, making the purpose highly clear.

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

Usage Guidelines5/5

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

The description gives explicit when-to-use and when-not-to-use conditions, directly naming the alternative tool. It mandates calling plan_pipeline before this tool, warns about specialized types and completionLevel defaults, and provides concrete prerequisites, achieving full usage guidance.

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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