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set_annotation

Set custom name/value annotations on Power BI model objects like tables, columns, measures, and partitions. Preserve metadata through serialization for tooling like Tabular Editor.

Instructions

Set a name/value annotation on any model object: objectType = model | table | column | measure | hierarchy | partition. Pass the object's table for column/measure/hierarchy/partition. Replaces a same-named annotation. Annotations are free-form metadata that survive serialization (used by tooling like Tabular Editor).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesannotation name
tableNothe object's table (required for column/measure/hierarchy/partition)
valueYesannotation value
sessionIdYes
objectNameYesthe object's name (the model name for objectType=model)
objectTypeYesmodel | table | column | measure | hierarchy | partition
Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses that the tool replaces same-named annotations and that annotations survive serialization, which are meaningful behavioral traits. However, it does not mention permissions, side effects beyond replacement, or return/error behavior. The description adds useful context but misses some aspects expected for a write operation.

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 four concise sentences that front-load the core purpose. It avoids fluff and every sentence adds value (purpose, table guidance, replacement behavior, serialization context). It's slightly redundant with the schema's objectType list, but that's acceptable for a readable description.

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

Completeness4/5

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

The tool has no output schema or annotations, but the description covers the essential aspects: what the tool does, which object types are supported, the table requirement, replacement behavior, and persistence. It doesn't discuss return values or errors, but for a straightforward 'set' operation this seems adequately complete for tool selection and invocation.

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

Parameters3/5

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

Schema description coverage is 83%, so the baseline is 3. The schema already describes objectType allowed values, objectName usage, and table requirement. The description reinforces the table requirement and adds conceptual context (free-form metadata), but it doesn't significantly clarify parameter semantics beyond what the schema already provides.

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 opens with a specific verb 'Set' and identifies the resource as a 'name/value annotation' on any model object, listing supported object types. It clearly distinguishes from sibling tools like set_extended_property or set_display_folder by emphasizing annotations as free-form metadata and naming object types (model, table, column, measure, hierarchy, partition).

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

Usage Guidelines4/5

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

The description provides clear context by specifying when to use the tool (for annotations on various object types) and how to handle the table parameter for column/measure/hierarchy/partition. It also notes that annotations are used by tooling like Tabular Editor. It doesn't explicitly name alternatives or state when not to use it, so it stops short of a 5.

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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