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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the description's job is to add context — and it does, via the data_source_discovery dependency chain and the constraint that fields must share a report_type in a subsequent query. Return shape is handled by the output schema, so it doesn't need to describe it, but it also says nothing about failure modes for an unknown ds_id.

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?

Three short sentences, front-loaded with the purpose, then the call precondition, then the downstream constraint. No filler and nothing repeated from the schema or annotations.

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?

A read-only discovery tool with three fully documented parameters, an output schema, and rich annotations; the description supplies the one thing structured fields cannot — the prerequisite on data_source_discovery and the report_type compatibility rule. Nothing an agent needs in order 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 description coverage is 100%: ds_id, filter (with syntax example and matched attributes), and compress are all fully documented in the schema. The description adds no parameter-level meaning beyond that, which matches the baseline-3 expectation when the schema does the heavy lifting.

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+resource: 'Discover available fields (metrics and dimensions) for a data source', which immediately separates it from data_query and data_source_discovery. It does not explicitly name an alternative tool it replaces, so it stops short of full sibling differentiation, but an agent can tell what it returns.

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 an explicit precondition: 'Only call if data_source_discovery config shows has_fields=true', which is a concrete gate that prevents wasted calls. It also warns that selected fields must share a common report_type when the source uses report types, though it never states a condition under which another tool should be used instead.

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