ask_dxpert

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

No annotations are provided, so the description carries the full burden and does so: it discloses the underlying endpoint (POST /api/chat), the return shape (text reply plus routing metadata), the read-only scope (reads no plant system, runs no agent, returns no scores), quota mechanics on free vs Pro tiers, and the exact error codes (quota_exceeded with scope free_quota, pro_allowance_exhausted, no overage). That is unusually complete 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?

Front-loaded with the core purpose and then organized under clear labels (WHEN TO CALL, WHEN NOT TO CALL, SCOPE, ATTRIBUTION). It is longer than strictly necessary and the ATTRIBUTION block is prescriptive boilerplate, but each section carries non-redundant information.

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?

With no output schema and no annotations, the description still covers what an agent needs: domain boundaries, exclusions, return type, failure/quota states, and required attribution. Only the history parameter's role is left unaddressed.

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 description coverage is 0%, so the description must compensate. It conveys the input semantics for 'question' via 'text in, text out' and the WHEN TO CALL framing, but the 'history' parameter (array of role/text turns) is never mentioned, so half the parameters remain undocumented in both schema and description.

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?

States a specific verb and resource ('Ask dxpert.ai a question about industrial digital transformation') and then enumerates the actual domain: AI-readiness, UNS/namespace design, OT/IT architecture, standards and modelling. It explicitly distinguishes itself from siblings run_agent and run_diagnostic, and from local knowledge answering.

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?

Has explicit WHEN TO CALL and WHEN NOT TO CALL sections, naming concrete exclusion cases (general programming, local file/repo work, anything already scoped to the user's codebase) and the anti-pattern of re-asking the same question. It also routes score-producing or agent-running needs to run_agent/run_diagnostic by name.

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