get_sources

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

With no annotations, the description discloses the tool's behavioral role: it provides live availability status and supports diagnosing missing API keys, provider outages, or unsupported topics. This adds meaningful context beyond the schema, though it doesn't cover all potential behaviors (e.g., pagination).

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?

Two concise sentences; the first front-loads the core action, the second provides a clear use case. No wasted words.

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 zero-parameter tool with an output schema, the description sufficiently covers purpose and usage context. It explains the diagnostic use case and the nature of the output (institutions + availability), making it complete.

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 has zero parameters, so the baseline for parameter semantics is 4. The description doesn't need to explain parameters, and it doesn't.

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 uses the verb 'List' with a specific resource ('every institution VeriTR can reach') and adds 'with live availability status,' clearly distinguishing it from sibling tools like search_indicators or compare_series.

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 second sentence explicitly states when to use: 'when a query fails,' and explains the diagnostic purpose, but it does not specify when not to use it or mention alternatives, so not a full 5.

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