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

Annotations already declare readOnlyHint=true, idempotentHint=true, openWorldHint=false, so the safety profile is covered. The description adds genuinely useful behavioral context beyond that: it is machine-legible, free, and requires no API key, which affects whether and how an agent invokes it. That is real added value over the structured fields.

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 dense sentences that front-load what it returns (freshness, history depth, coverage, endpoints) and lead with 'ONBOARDING SPEC'. It is tight, though the label and feed enumeration make it slightly list-heavy.

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-param, read-only tool with full annotation coverage and no output schema, the description covers what it answers, its scope, and its cost/auth posture. The only minor gap is the exact return shape, which the description only gestures at with 'machine-legible'.

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?

There are zero parameters, so the baseline is 4 by the rubric. The description correctly implies a parameterless call with nothing to configure, and 'no key' confirms no auth parameter is needed.

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 resource (metadata about feeds) and enumerates the feeds by name, and quotes the exact question it answers ('how stale is this and how far back does it go'). It is clearly distinguishable from siblings like get_stats or get_metric_history, though the label 'data dictionary' plus the enumerated feeds does the heavy lifting.

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 scope question ('how stale is this and how far back does it go') implies when to consult it, and 'free, no key' tells the agent there is no setup cost. But there is no explicit when-to-use vs. alternative guidance (e.g., vs. get_metric_history or list_datasets), so an agent must infer the routing.

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