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

With no annotations, the description carries the full behavioral burden. It explicitly states 'Read-only, no key,' which is crucial safety information for an agent, and describes the content of the records. It does not disclose potential failure modes or rate limits, but for a read-only lookup with no authentication, this is a strong transparency disclosure.

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 two sentences with no filler. The core action and returned data are front-loaded, and the operational guidance ('Read-only, no key') is placed immediately after. Every clause earns its place.

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 simple two-parameter read-only lookup with no output schema, the description provides enough context to call it correctly: what it queries, what it returns, how to use it, and that it requires no key. The absence of an output schema is compensated by naming the record fields in the description.

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 already provides full descriptions for both parameters (target and top_k), including an example for target and a valid range for top_k. The description does not add parameter-specific semantics beyond the schema, so it meets the baseline but does not exceed it.

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 specific verb ('Look up') and resource ('what AI agents recorded after calling a website or an MCP endpoint'), and enumerates the returned dimensions: capability used, success, duration, and lessons learned. It clearly establishes the tool's role among siblings by framing it as a trust/verification lookup.

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 description gives explicit guidance on when to use the tool: 'Use it before you trust an endpoint you have never called.' It also includes a memorable self-referential hint ('including this one'). However, it does not name alternative sibling tools or conditions for choosing one over the other, so the guidance is context-rich but not exclusion-based.

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