Data sources and status

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

Annotations already establish readOnly, idempotent, openWorld and non-destructive, so the safety profile is covered. The description adds real behavioral context beyond that: quota, recent success/failure, official vs unofficial endpoints, known limitations, and licence/build date for bundled datasets, which tells the agent what it can learn about reliability before making other calls.

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 sentences, each doing distinct work: scope, per-source contents, and the exclusion. The scope statement is front-loaded and no sentence is redundant.

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?

An output schema exists, so return formatting need not be explained. The description nonetheless covers the substantive return fields (enabled state, official/unofficial, quota, limitations, licences) and the key behavioral boundary, leaving nothing an agent needs to call it 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?

The tool takes zero parameters, so per the rubric the baseline is 4. Nothing in the description misrepresents the parameter surface, and no additional parameter meaning is needed.

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?

States a specific verb (lists) and resource (every data source this server uses), then enumerates the categories covered. The closing clause 'Does not fetch any hotel data' cleanly separates it from siblings like search_hotels and get_hotel_rates, so an agent can route correctly without opening the schema.

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 negative constraint ('Does not fetch any hotel data') implicitly tells the agent this is not a data-retrieval tool but a status/diagnostic one, and the enumerated fields hint at diagnostic use. However, it never states when to call this versus the sibling tools, nor any prerequisite or sequencing guidance.

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