set_template_column

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

With no annotations, the description carries the full burden of behavioral disclosure. It explicitly states that it writes back in place with a .bak guard, fails if the column does not exist, leaves omitted properties unchanged, and works without Power BI Desktop. This comprehensively covers the mutation, side effects, error behavior, and prerequisites.

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 three sentences: the first states the core purpose and scope, the second explains omission behavior, and the third covers error handling and write-back safeguard. Every sentence contributes distinct value with no filler or repetition.

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 mutation tool with no output schema and no annotations, this description covers the purpose, target resource, method of editing, prerequisites, side effects (in-place write with backup), error condition (column not found), and parameter behavior. It is sufficient for an agent to correctly select and invoke the tool.

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?

The input schema already provides descriptions for all 8 parameters (100% coverage). The description adds valuable cross-cutting semantics: 'Any omitted property is left unchanged', which clarifies the effect of null/default values across all optional parameters. It also enumerates the property types, reinforcing schema meaning without being redundant.

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 clearly states a specific action: 'Patch properties of an existing column in a closed .pbit template's model', listing the exact property types and the editing mechanism ('editing the DataModelSchema JSON on disk'). This distinguishes it from sibling set_* tools by emphasizing the offline template context and combined property patching.

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 description implies when to use this tool: for closed .pbit templates requiring on-disk JSON editing without Power BI Desktop. It does not explicitly name alternatives (e.g., set_column_data_type, set_summarize_by) or state when not to use it, but the context is clear enough for an agent to infer the appropriate scenario.

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