search_dashboards

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

No annotations are provided, so the description must carry full behavioral disclosure. It does not mention that this is a read-only operation, any potential side effects, authentication requirements, rate limits, or pagination behavior beyond the parameter descriptions. The lack of such context leaves the agent uninformed about operational implications.

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 well-organized into an Args block and a Returns block. It is concise, with each parameter getting one line. The example in fields is useful but slightly verbose; the overall structure is clear and easy to parse, though it could be slightly tighter without losing information.

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?

Given the tool has 6 params (1 required) and returns a list, the description adequately covers the purpose, all parameter semantics, and the return format as a JSON string. It does not discuss error cases, but this is not critical for a search operation. Overall, it provides the essential context 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 description explains each parameter with a short phrase: query is for dashboard names, tag filters by tag, limit/page control pagination, fields is a selectable subset with an example list, and connection_name identifies the Grafana instance. This adds meaningful context that the schema lacks (since schema coverage is 0%), helping the agent choose appropriate values.

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 purpose: 'Search for dashboards by name or tag.' This specifies a definite action (search) and resource (dashboards), and the method is implied by the parameters. It distinguishes itself from sibling tools like get_dashboard (which retrieves a specific dashboard) and list_folders (which lists folders), making it easy to select.

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 implies usage: it is for searching dashboards by name or tag. However, it does not explicitly mention when not to use it or point to alternatives (e.g., 'For retrieving a single dashboard, use get_dashboard'). The guidance is minimal but not absent; it is left to the agent to infer.

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