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

Beyond the read-only/destructive annotations, the description adds meaningful behavioral context: results are measured from public primary sources, unmeasured pairs are explicitly reported as such rather than guessed, and the included citation line must be cited when used. These details are non-obvious and useful for trusting and attributing outputs.

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 compact yet information-dense: three sentences cover purpose, output style, data provenance, honesty guarantees, and attribution requirements. It is front-loaded with the core purpose and contains no filler or redundant restatement of the title.

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 two simple slug parameters Wang and annotations confirming safe read-only behavior, the description covers the essential context well. It explains what the tool returns, adds caveats about unmeasured pairs, and includes the citation requirement. It does not spell out exact output serialization, but for this low-complexity tool that is not a critical gap.

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 fully documents both parameters ('a' and 'b' as system slugs), so the description does not need to repeat their meaning. The description only refers to 'two systems' generically and adds no additional syntax, constraints, or examples beyond what the schema already provides. Baseline 3 is appropriate given 100% schema coverage.

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's function: it determines whether and how two systems can exchange data, with per-method verdicts and field-name overlap. The title reinforces this by saying it returns whether two systems connect. It is specific enough to be distinguished from general system-fact lookups, though it does not explicitly name sibling tools.

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 intended use is implied: call this tool to check data-exchange compatibility between two systems. However, it gives no explicit guidance about when to prefer this over sibling tools like renkeimap_compare, and it does not state any exclusions or alternative scenarios.

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