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

Annotations already declare readOnlyHint=true, and the description adds useful behavioral content about what the response includes: dataset/series counts, cadence notes, and terms links. It does not contradict the annotations and gives enough context for a simple read-only listing.

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, front-loads the core purpose and output contents, and ends with clear starting guidance. Every sentence adds value with no repetition of already-structured annotation data.

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 zero-parameter, read-only listing tool with no output schema, the description provides sufficient context: what is listed, what the entries contain, and where this tool fits in the workflow. Nothing critical is missing for an agent to select and invoke it correctly.

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?

The tool has zero parameters and the schema has no properties, so parameter semantics are trivially satisfied. The description appropriately avoids inventing parameter details that do not exist, matching the baseline for a zero-parameter tool.

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 uses a specific verb ('List') and resource ('official statistical sources served by this data layer'), with concrete examples (Statistics Canada, FRED) and output details (counts, cadence notes, terms links). It is clear, though it does not explicitly differentiate itself from the sibling list_datasets, so it stops short of a 5.

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 phrase 'Start here to see what exists' gives clear guidance that this is the initial discovery entry point among the sibling tools. It does not state when not to use it or explicitly name alternatives, so it lacks full exclusionary guidance.

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