get_table_row_count

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

No annotations are provided, so the description carries the full behavioral burden, yet it only implies that the count reflects loaded (not source) data. It says nothing about whether a live connection is required, whether the value is cached, or whether the table must exist in the current model.

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?

One sentence, front-loaded with the verb, with no filler. It is appropriately sized for a simple read tool, though it leaves no room for the guidance that is missing elsewhere.

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?

An output schema exists, so return-value detail is not required, but with zero annotations and two entirely undocumented parameters, the definition leaves an agent unable to confidently supply 'instance'. The 'currently loaded' nuance needs more grounding for a Power BI/Tabular context.

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 neither 'instance' nor 'table' has a documented format, casing rule, or example. The description does not compensate at all — it never mentions the instance parameter, which is the more ambiguous of the two.

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 states a specific verb and resource ('Get the number of rows ... in a table') with a useful scoping qualifier, 'currently loaded', which signals an in-memory model context. It does not, however, distinguish itself from nearby siblings such as profile_table or get_model_summary, which could also report row counts.

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?

There is no guidance on when to use this instead of profile_table, list_tables, or get_model_summary, nor any stated prerequisite (e.g. model must be open/connected). The agent must infer the choice purely from the name.

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