read_table

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

No annotations provided, so description carries full burden. It discloses read behavior (returning rows) and the optional timestamp for time-travel reads, but does not explicitly state it's read-only, idempotent, or safe. Missing details like default ordering or pagination behavior for results exceeding count.

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 concise and well-structured: a single sentence summarizing the action and output format, followed by a bulleted parameter list. No redundant information, and the most important information is front-loaded.

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?

The description covers input parameters well and mentions output format, but lacks context on error handling, permissions required, or prerequisites (e.g., table existence). With an output schema present, return values are handled, but additional behavioral context for edge cases would improve completeness.

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 fully compensates by explaining each parameter: workspace, item, qualified_name, count (with range and default), and as_of (with format and SQL option). This adds significant meaning beyond the schema types and constraints.

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 tool returns up to count rows from a table as JSON-serialisable columns and rows. The verb 'return' and resource 'table' are specific, and it differentiates from siblings like read_view (for views) and count_table_rows (count only).

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?

No explicit guidance on when to use this tool versus alternatives. While the description implies it's for reading table data, it does not state when not to use it or mention better alternatives, e.g., for large datasets or filtered reads. Given many siblings, explicit guidance would improve clarity.

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