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

With no annotations, the description carries the disclosure burden and is unusually detailed: it defines freshness.status values, archival readability with explicit read-time messaging, the independent stale_for_its_own_cadence flag, withheld/excluded categories, and route availability. It stops short of stating authentication/rate-limit behavior, but for a zero-parameter read catalogue this is thorough.

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 dense but every clause adds operational meaning: purpose, freshness semantics, stale flag, category meanings, live measured counts, and the call to action. It is front-loaded with the catalogue purpose and uses parallel structure effectively; no filler or repetition.

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 parameterless catalogue with no output schema, this is complete: it specifies what fields each entry carries (coverage and freshness blocks), how the freshness statuses behave, what withheld/excluded mean for routability, and even gives current dataset/row counts. An agent can decide to call it and know what to expect without additional structured metadata.

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 input schema has zero properties, so the 0-parameter baseline of 4 applies. The description focuses on what the catalogue returns rather than parameter syntax, which is appropriate because there are no parameters to document.

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 identifies the tool as the feature-store catalogue for derived research panels, enumerating exactly what it exposes (existence, row counts, history depth, freshness). It also distinguishes it from sibling tools by stating it is the only place slugs for /api/v3/features/{dataset} are published, so an agent can immediately route to it.

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?

It gives explicit usage guidance: 'Call it first' and notes it is the sole publisher of dataset slugs. This tells an agent when to invoke it before feature-specific calls. It does not name alternative tools for exclusions, but for a catalogue the 'first' and 'only place' guidance is strong.

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