transform_get_optim_field

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

With no annotations provided, the description carries the full burden of behavioral disclosure, and it does so unusually well. It reveals that 'Algorithm' and 'Error' are write-only, that GTFV rejects them, that the tool returns readable=false with an explanation instead of throwing, and that indexed fields and options read reliably. This goes well beyond a generic 'read' statement.

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 front-loaded with the core purpose, then uses compact sentences to cover caveats and usage guidance. Every clause earns its place, and the structure moves naturally from 'what it does' to 'what to watch out for' to 'when not to rely on it.' No filler or redundant restatement.

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 two-parameter read tool with no output schema and no annotations, the description covers the essential edge cases and limitations thoroughly. The only minor gap is that it does not explicitly describe the normal successful return shape beyond the mention of readable=false, though 'read a value' makes the common case reasonably inferable.

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 100%, so the baseline is 3. The description adds value by giving concrete field name examples like Target[0] and Name[0], and by calling out 'Algorithm' and 'Error' as invalid readable field names. This enriches the field_name semantics beyond the schema's brief example.

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 opens with a specific verb and object: 'Read an Optimize Transform's table field value.' It also explicitly identifies itself as the counterpart to transform_set_optim_field, immediately clarifying the operation's scope and distinguishing it from the setter and other getter 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?

The description states when this tool is appropriate and gives concrete alternatives: track the value returned by transform_set_optim_field when you set it, and open the GUI to inspect transforms configured elsewhere. It could more explicitly compare against sibling getters like transform_get_fields or transform_get_data, but the context is clear enough.

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