run_readiness_diagnostic

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

No annotations are present, so the description carries the full burden, and it does: free, no API key or account, DOES call the dxpert.ai API, requires connectivity, and is rate limited. It also warns the verdict is only as good as the intake and that the 'scope' field must be reported as a preliminary self-reported screening, not an audit.

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?

Front-loaded with verb, resource, and the input/output pairing, and every sentence carries non-redundant information. It is dense and the sentences run long, which slightly taxes readability, but 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?

For a single-parameter tool with no output schema, the description covers connectivity, rate limits, auth (none), what comes back, and how to frame the result to the user. Nothing an agent needs to call it correctly is missing.

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 100% and the nested intake object is fully documented, so the baseline is 3. The description earns above baseline by telling the agent to ask the user for missing values rather than guess them and by warning that the result quality depends on honest intake answers, adding actionable semantics the schema cannot express.

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?

Precise verb+resource (runs the dxpert.ai industrial AI-readiness diagnostic), with the input stated (a 16-answer self-reported intake) and the output characterized (ten axes 0-5, maturity stage, foundation gaps, confidence). It also explicitly contrasts itself with 'the two validators,' letting an agent separate it from its siblings.

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?

Gives concrete triggering conditions ('how ready a plant or site is for AI/analytics, what is blocking them, or where to start') plus a precondition (you can supply honest answers to the intake). It distinguishes itself from the validators by noting it calls the network while they do not, but does not name those alternatives explicitly, so it stops short of a full 5.

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