get_timebase_full

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

With no annotations, the description must carry the load; 'read back' clearly signals a non-mutating read, and it enumerates the additional query domains covered. It stops short of describing cost/round-trip or data-volume characteristics, which would matter for a 'full' variant.

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 compact sentences: the core action is front-loaded and the second sentence earns its place by giving the exact delta against the sibling. No filler.

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?

An output schema exists, so return values need not be explained, and the 0-parameter schema leaves nothing else to document. The description covers what the tool returns at the level an agent needs to select it.

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?

The tool takes zero parameters, so there is nothing to document; the schema is fully covered and no parameter ambiguity exists. Baseline of 4 for a 0-param tool is appropriate.

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 ('read back') plus resource ('complete horizontal system configuration'), and explicitly differentiates from the sibling get_timebase() by naming what it adds (reference mode/position, vernier, XY-mode). An agent can distinguish the two without opening either schema.

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 relationship to get_timebase() is spelled out, implying this is the superset to use when reference/vernier/XY data is needed. However, it does not state an explicit when-to-use vs when-not rule (e.g., prefer the lighter get_timebase() when only scale/position is required).

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