Build a rows-by-columns value grid for editable data entry, returning JSON that maps each cell to a write tuple for TM1.
Build a rows × columns value grid for an editable data-entry table. Returns JSON (rows, columns, values, updateable) that maps each cell back to a write tuple.
| Name | Required | Description | Default |
|---|---|---|---|
| context | No | ||
| cubeName | Yes | ||
| colElements | Yes | ||
| rowElements | Yes | ||
| colDimension | Yes | ||
| colHierarchy | No | ||
| rowDimension | Yes | ||
| rowHierarchy | No |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral disclosure burden. It clearly states the return shape (rows, columns, values, updateable) and the write-tuple mapping, which tells an agent that this is a read-oriented grid builder for writeback workflows. It does not cover permissions, errors, or size limits, but those are secondary for a get-style tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single front-loaded sentence with no filler. It states the action, purpose, and return contract efficiently, making every word earn its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 8 parameters, 5 required, no output schema, and no annotations, this description is too thin. It gives a strong high-level purpose but leaves parameter semantics, valid combinations, and required context behavior unexplained, so an agent would still need to infer how to construct a correct call.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not compensate by explaining the parameters. While names like cubeName, rowDimension, and colElements are somewhat self-explanatory, the important 'context' parameter and hierarchy-related fields remain semantically opaque.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb and resource: 'Build a rows × columns value grid' for an editable data-entry table. It also distinguishes itself from sibling read/list tools by emphasizing the 'updateable' flag and mapping cells back to a write tuple.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'for an editable data-entry table' gives a clear intended use context, signaling this is the right tool when a writeback grid is needed. It does not explicitly name alternatives or state when-not-to-use conditions, so it falls just short of full routing guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.