execute_service_query

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

With no annotations, the description must carry the burden of behavioral disclosure. It does add valuable context: the HTTP method (POST), endpoint, authentication requirements (AAD token, env var fallback), and token non-echoing. However, it does not disclose return format, error behavior, or whether the query is read-only, which are relevant for a REST execution tool.

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 two sentences, starts with the action verb, and packs essential constraints (published dataset, REST, no Desktop, token handling) with no filler. Every phrase adds value, making it highly concise while preserving clarity.

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?

The description covers purpose, execution environment, and authentication, which is substantial. However, it lacks any mention of what the query returns, pagination, or error handling, which would be expected given there is no output schema to clarify results. It is adequate for a simple execution tool but not fully complete.

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% so all parameters are already documented. The description adds meaning beyond the schema, especially for accessToken: it specifies the required AAD scopes, mentions the DAXOPS_PBI_TOKEN fallback, and notes the token is never echoed. This enriches the parameter semantics beyond the basic schema descriptions.

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 verb 'Run a DAX query' with a specific resource: 'PUBLISHED dataset over REST'. It explicitly contrasts with local execution ('no Desktop, no live model session'), which distinguishes it from sibling tools like run_dax or eval_dax_offline. The purpose is unambiguous and specific.

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 when to use the tool by noting it runs against a PUBLISHED dataset over REST and is not for Desktop or live sessions. However, it does not explicitly name alternatives or state 'use this when you need X instead of Y'. This leaves the usage context inferred rather than explicitly excluded.

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