list_datasources

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

With no annotations provided, the description carries the full burden. It accurately describes the listing behavior and the data returned (uid/name/default/project count) which implies a read-only operation, but it does not disclose potential edge cases, performance implications, or any side effects. For a simple list operation, this is adequate but not exceptional.

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 concise, front-loaded with the main verb ('list'), and uses two sentences to cover purpose and usage context without redundancy. Every word earns its place, and the structure is easy to scan.

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 tool with no parameters, no output schema, and a straightforward listing operation, the description fully covers what the tool does and returns. It also provides relevant context about when to use it (multi-datasource environments). No additional information is needed for an agent to correctly select and invoke it.

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, and schema description coverage is 100% (vacuously). The description does not need to explain parameters, and the baseline of 4 is appropriate since there are no parameters to clarify.

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: listing all Loki log data sources on the Grafana instance, along with specific attributes (uid, name, default status) and the count of registered projects per datasource. This is a specific verb+resource combination that distinguishes it from sibling tools focused on logs, labels, and queries.

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 explicitly says 'In a multi-data-source environment, use it first to confirm which data source to query,' providing clear context on when to use this tool. However, it does not mention any alternatives or when not to use it, so it falls short of a full 5, but gives solid usage guidance.

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