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

Annotations already cover safety (readOnlyHint=true, destructiveHint=false, openWorldHint=false), so the description only needs to add context — and it does: it warns about empty schemas to skip and flags that `full` returns heavy per-dataset descriptions instead of the compact index. It does not mention response size limits or cost implications of `full`.

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, then a compact block covering what is returned and warnings, then a short line per parameter. Every sentence carries information; 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 two-parameter read-only catalog call, the description covers purpose, timing, return contents, skip conditions, and both parameter behaviors. An output schema exists, yet the description still usefully summarizes the payload shape.

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 carry both parameters — and it does, with syntax ('optional comma-separated filter (e.g. "bls,bea")') for `schemas` and a behavioral tradeoff description for `full`. This fully compensates for the empty 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?

States a specific verb and resource ('List the data sources FactIQ has, plus the shared table structure') and enumerates exactly what comes back (visible schemas, per-schema dataset index, shared DDL). The 'Call this once before exploring' framing distinguishes it from siblings like search_datasets and describe_dataset as the entry-point inventory tool.

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 clear timing guidance ('Call this once before exploring') and an actionable exclusion rule ('schemas_without_data — skip them'). It does not name alternative tools such as search_datasets or describe_dataset, so the routing is implied rather than explicit.

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