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

With no annotations, the description carries the full burden and does well: it discloses staging status, unpaid/feature-flagged, NOT live-verified, 'informational only', and that it returns explicit unknowns where coverage is missing. It omits auth needs, rate limits, and return shape, but the limitation disclosure is unusually candid.

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-loads the most decision-relevant caveat (staging, not live-verified), then lists scope and exclusions in terse fragments. Every line carries information; only minor tightening is possible.

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 4-param, no-output-schema, no-annotation tool, the description covers scope and limitations well but leaves objective and depth semantics and the actual response structure unstated. An agent still lacks enough to invoke it fully 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?

Schema description coverage is 0% across 4 params, so the description must compensate. It documents countries and dimensions (including the max-4 rule and rejected values) effectively, but 'objective' and 'depth' are entirely undocumented, leaving two of four parameters ambiguous.

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 enumerates accepted countries and research dimensions, which implies a multi-country business-environment research tool, but it never states an explicit verb+resource outcome (what a 'research' call actually returns beyond 'explicit unknowns'). An agent can infer the scope from the enum-like lists, yet the core purpose remains implicit rather than stated.

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 strong in-scope guidance (accepted countries, accepted dimensions, max 4) and an explicit out-of-scope list (roadmap-only: tax, foreign_ownership, permits, economy). However, it never names a sibling tool or says when to prefer this over xrplme_get_country_data or xrplme_list_countries, so alternative selection is left to inference.

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