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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds one genuinely new behavioral fact — 'Live nightly-probe counts', i.e. data freshness — but says nothing about result ordering, sizes, or failure behavior beyond what the schema implies.

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 short sentences, front-loaded with the use case, then the data-freshness note, then the call examples. No filler and nothing redundant with the schema.

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 eight enum sections and no output schema, the description never explains what 'summary', 'compare', or 'demand' actually return, which is the main ambiguity an agent faces here. The annotation and schema coverage make it callable, but not fully self-explanatory.

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 100%, so the baseline is 3. The description adds value beyond the schema by stating 'No arguments needed' and showing '{}' versus '{"section":"compare"}', which clarifies that defaults yield a usable result and demonstrates how to target a section.

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 states a concrete purpose — surfacing which MCP servers are most reliable, biggest, or best in given categories — backed by the title 'Top MCP servers: live reliability and size'. It is clear what the tool produces, but it never explicitly contrasts itself with siblings like compare_tools or find_tool_for_task, so an agent must infer the boundary.

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 opening 'Use when asked which MCP servers are most reliable, biggest, or best for Postgres, payments, browser or GitHub' gives explicit trigger conditions with concrete example domains. It does not name when NOT to use it or point at an alternative sibling, so it stops 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.