get_datastructure_variable

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

readOnlyHint=true already covers the safety profile, but the description goes further and discloses the returned field set (core, data type, description, var-set in refs) plus the case-insensitive auto-matching behavior against mixed-case API spellings like SITEGRy/APHASEw. That is real behavioral context an agent would not get from annotations, though the token-saving 'raw' behavior is only described in the schema.

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?

Two short blocks, front-loaded with the return-field summary, then the casing caveat, then a compact example. The case-insensitivity point is repeated in both the description and the schema property, which is minor redundancy rather than bloat.

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?

A read-only single-record lookup with full schema coverage and no output schema needs to say what it returns and how to form the call; the description does both via the field list and the example. The main remaining gap is not routing the agent away from similarly named siblings.

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 100%, so all five parameters are already documented with descriptions and the standard enum. The description's case-insensitivity note and worked example add marginal value but largely restate what the schema already says for 'variable' and 'datastructure'. Baseline 3 is appropriate when the schema does the heavy lifting.

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+resource: fetch the details of one variable inside an analysis data structure, and enumerates what comes back (core, data type, description, var-set membership via refs). The singular 'single variable' implicitly contrasts with the plural listing sibling, but no sibling is named explicitly.

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?

Usage is only implied: the example shows a concrete call shape (standard='adamig', version='latest', datastructure='ADSL', variable='AGE'), which helps an agent pattern-match. There is no explicit statement of when to prefer this over get_variable, get_datastructure_variables, or get_dataset_variables, and the 'call get_datastructures first if unsure' advice lives in the schema, not the description.

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