measure

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

No annotations are provided, so the description carries the full transparency burden. It discloses side effects (registers the item on the scope, may populate results panel, enables disabled channels), prerequisites (live acquisition for DHO), the invalid sentinel 9.9E37, and measurement semantics. This is strong behavioral disclosure.

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 packs side effects, prerequisites, invalid values, and item semantics into three dense but purposeful sentences. Every sentence adds non-obvious information; there is 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?

In the absence of annotations and an output schema, this description covers what the tool returns, how its side effects behave, what preconditions exist, which values are invalid, and how key measurement items differ. That is sufficient for an agent to invoke the tool correctly.

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 schema gives item examples but little semantic depth; the description compensates by explaining VAMP, VPP, VRMS, PVRMS, and ACRMS meanings. Channel is adequately handled by the enum. It adds real value beyond the schema, though it does not describe every possible item.

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 action ('Read a built-in measurement as text') and the resource ('a built-in measurement'), and mentions get_capabilities for item discovery. It does not explicitly contrast with sibling measure_between, so differentiation is slightly weaker than ideal.

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 provides actionable context: get_capabilities lists valid items, and DHO may need live acquisition before measurement. It lacks an explicit 'when not to use' statement or direct mention of alternatives like measure_between, but the usage context is reasonably clear.

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