mark_as_date_table

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

No annotations are provided, so the description carries the full burden. It discloses two concrete behaviors (setting data category and flagging date column) but does not mention potential errors, prerequisites, or side effects such as overriding an existing date table mark. This is adequate but not fully transparent.

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 two sentences, informative, and front-loaded with the action and its details. No redundant or extraneous information.

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 simple model-marking tool with three required parameters and no output schema, the description covers purpose, effect, and usage scenario. It lacks details about return values or error conditions, but these are not critical for the agent to invoke the tool correctly.

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 coverage is only 33% (only dateColumn has a description). The description adds context for table ('your own calendar table') and dateColumn ('given DateTime column') but does not explain sessionId. It partially compensates for the low coverage, but not completely.

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 the verb and resource: 'Mark a table as the model's date table' and elaborates by specifying the exact effects ('sets the table's data category to Time and flags the given DateTime column as the date key'). This distinguishes it from sibling tools like set_column_data_category (which only sets a category) and create_date_table (which creates a new table).

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?

Provides clear usage context: 'Use this so built-in time intelligence works reliably against your own calendar table.' It tells when to use the tool but does not mention alternatives or exclusions, which would merit a 5.

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