get_all

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

No annotations are provided, so the description must carry the behavioral burden. It describes the data categories returned but doesn't disclose size/volume implications of fetching everything at once, response format, or whether this is a heavier/longer operation than granular reads. For an aggregate read tool, it adds reasonable value but doesn't fully disclose behavioral traits beyond listing return contents.

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?

One tight sentence that front-loads the purpose ('Get all PLC data at once') and enumerates the covered categories. Zero wasted words, perfect for a zero-parameter bulk retrieval tool.

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?

This is a simple zero-parameter tool with no output schema. For an aggregate getter, the description enumerates the categories of data returned, which is sufficient. It doesn't hurt that the siblings clarify the decomposition; describing return contents for a no-input bulk tool is reasonably complete even without specifying response formatting.

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 has 0 parameters and 100% schema coverage (empty properties), so the schema provides no parameter meaning. The description compensates by describing what data is returned. With no params to document, the baseline is 4, and the description fulfills this by enumerating the data domains it retrieves.

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 states it gets 'all PLC data at once' and enumerates the categories (sensors, alarms, status, setpoints, outputs). This clearly differentiates it as the bulk fetcher versus the more specific sibling tools like read_sensor or get_alarms. It doesn't name a specific sibling but the phrase 'at once' distinguishes its aggregate scope.

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 implies this is the when-you-want-everything tool, referring to 'all PLC data at once,' which contrasts implicitly with the granular sibling tools. However, it doesn't explicitly state when NOT to use it or suggest alternatives (e.g., 'use read_sensor for a single sensor'). The usage guidance is implied through the 'at once' framing rather than stated.

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