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 of behavioral disclosure. It correctly implies a read-only listing operation, but does not explicitly mention pagination, rate limits, or any side effects. For a simple list operation, this is adequate but not thorough; it lacks explicit confirmation of safety or response limitations.

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 compact sentences. The first states the core function and return fields; the second immediately provides actionable guidance on next steps. There is no redundancy or filler, and the critical scoping information is front-loaded.

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 low complexity, the description fully covers what the agent needs: what it returns, and how to proceed. It is complete and self-sufficient for correct invocation and routing to sibling tools.

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 schema is inherently complete. The description adds no parameter details because none exist. Per the rubric, a baseline of 4 is appropriate for zero parameters, and the description does not need to explain anything about parameters.

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 Grafana datasources with specific fields (uid, name, type). It also differentiates from sibling query tools by framing itself as the prerequisite step, so an agent can immediately understand what it does and how it differs.

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 provides explicit usage guidance: it tells the agent to start here whenever querying is needed, explains that a datasource uid is required, and directs the agent to choose between query_sql and query_metrics based on the type. This clearly distinguishes when to use this tool versus the query siblings.

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