dashai_server_info

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

The description goes beyond the readOnly/idempotent annotations by detailing the exact response shape, including reachability, queue state, dataset/run counts, and API compatibility status. It also discloses the failure string format ('Error: <what happened and what to do>'), so the agent knows what to expect on both success and failure.

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, followed by a concise use-case directive and then well-structured Args/Returns sections. The return schema is detailed but necessary because it documents a complex JSON payload, so every section earns its place.

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 read-only health-check tool, the description is complete: it explains when to call it, what it checks, what the output contains, what the compatibility field means, and what failure messages look like. The rich output schema and annotations cover the remaining structured details.

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 no meaningful parameters: the input schema defines a NoArgs object and the description explicitly states 'no parameters.' With effectively zero parameters, the baseline is 4, and the description's confirmation removes any ambiguity.

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 opens with a specific verb and resource: 'Checks that dashAI is running and summarizes what is loaded.' It also distinguishes this tool from sibling data-operations tools by framing it as the backend health diagnostic, and explicitly separates 'dashAI is down' from 'that id does not exist'.

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 guidance is explicit and actionable: 'Call this FIRST when something fails or when you do not know whether the backend is up.' It also tells the agent what diagnostic distinction the tool provides, which directly informs decision-making about which problem is being debugged.

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