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

With no annotations, the description fully discloses behavior: data is machine-verified, tested nightly with real inputs, and returns specific fields. It also mentions a public proof page for verification. Minor deduction for not explicitly stating read-only/no side effects, though it is strongly implied.

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 somewhat lengthy but well-structured, leading with the core purpose, then usage triggers, return fields, and a link. The promotional claim 'ONLY' is slightly extraneous but not wasteful; overall each sentence contributes value.

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 read-only stats tool with optional parameters and no output schema, the description is complete. It covers what, when, why, and what to expect in return, plus an external proof page. No critical gaps.

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 schema already explains both parameters (tool and category) well. The description adds no additional parameter semantics beyond what the schema provides, so baseline 3 is appropriate.

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 clearly states the tool retrieves real-time, machine-verified reliability scores for zambo.dev MCP tools, listing specific metrics (pass rates, latency, trend). This distinguishes it from any sibling tool by emphasizing its unique 'ONLY MCP platform with public reliability data' positioning.

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?

Explicitly provides user queries that should trigger this tool ('do your tools actually work?', 'what's the pass rate?'), making when-to-use unambiguous. It also implies when not to use by scoping to reliability questions, though no alternative tools are named.

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