get_table

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

readOnlyHint=true already establishes the safety profile, so the description's job is to add context. It does: all values are text in the model's present units, and for_editing returns a table_version to pass back to edit_table. It does not discuss error behavior or limits beyond the paging defaults, but with annotations covering safety this is solid.

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?

Front-loads the operation and return shape in one sentence, then a well-labeled Args list with one line per parameter. No padding 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?

With an output schema present, return values need not be explained, and the description still supplies the shape. All parameters, the key source, the units caveat, and the editing round-trip are covered — nothing needed to invoke it correctly is missing.

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%, so the description carries the full burden and does so, documenting all ten parameters. The where filter gets a concrete example ({"OutputCase": "DEAD"}), and for_editing explicitly says it returns all fields plus the table_version for edit_table.

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?

States a specific verb and resource ('Read a CSiBridge database table') and even specifies the return shape. It clarifies scope by noting it covers model definition tables and, post-analysis, result tables, and references list_tables as the source of the key, which distinguishes it from siblings.

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?

Gives clear context: the key comes from list_tables, result tables require an analysis to have been run, and for_editing selects the form edit_table expects. It stops short of explicit when-not guidance or naming edit_table as the write-side alternative, but the routing signals are strong.

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