cmw_get_errors

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

With no annotations, the description carries the full burden. It discloses that reading the queue clears it, which is a crucial behavioral side effect. It also explains the underlying reason for the tool's existence (silent write failures). This is highly transparent.

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 three sentences, each adding essential information: what it does, why it's needed, and a key side effect. It is front-loaded with the primary action and contains 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?

For a simple two-parameter tool with no output schema, the description explains the tool's purpose, its necessity, and its clearing side effect. This is complete for an agent to understand when and how to invoke it, especially given the rich sibling context.

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 0% and the description does not explain the 'host' and 'port' parameters. While they may be self-explanatory in a network instrument context, the description adds no meaning beyond the schema's bare parameter names. For a low-coverage schema, the description should compensate but does not.

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 tool drains the instrument's SCPI error queue and reports rejected settings. This is specific and distinguishes it from sibling tools by focusing solely on error retrieval and its role in detecting silent failures.

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?

It explicitly explains when to use this tool: after write commands that return no response, as the only way to learn if a setting was rejected. This provides clear context and implies it is the go-to tool for error feedback, with no ambiguity about alternatives.

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