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

Annotations already cover the safety profile (readOnlyHint=true, openWorldHint=false, destructiveHint=false), so the lower bar applies. The description adds genuine behavioral context by disclosing that the response reports data freshness and coverage boundaries, which tells the agent the corpus is not necessarily up to the current date.

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?

Two sentences, tightly written, with the return contents front-loaded and the usage cue second. Every clause earns its place and only one call-to-action is given.

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?

With no parameters and no output schema, the description must convey what the agent gets back, and it does so adequately (counts, ingest timestamps, earliest covered filing date). It stops short of stating the result shape or units, but it is complete enough for a zero-argument status tool.

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 takes no parameters, so the baseline of 4 applies; there is nothing for the description to disambiguate. The listed return fields describe output, not inputs, and correctly do not pretend otherwise.

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 names the specific resource (each dataset) and enumerates the exact fields returned — row counts, latest ingest timestamps, earliest covered filing date — plus concrete dataset types (Form 4, 8-K, registrations). It is clearly distinguishable from siblings like get_schema and the get_insider_* query tools.

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?

"Call this to learn what date range a query can be answered from" gives an explicit use context and frames it as a prerequisite check before querying. It does not name an alternative tool or state when not to use it, so it falls short of a 5.

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