monitor_setup_grafana

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

With no annotations, the description carries the full burden of behavioral disclosure. It says the tool generates Grafana dashboard JSON, which indicates the core output, but it does not explain whether the tool writes a file, calls the Grafana API, uses the api_key, overwrites an existing dashboard, or only returns JSON. These are significant unstated behaviors.

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 a single front-loaded sentence with no filler or redundancy. Every phrase adds information: the action, the resource, and the included components. It is appropriately sized for a straightforward generation tool.

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 annotations and no output schema, the description leaves crucial operational details unexplained: how api_key is used, what role service_name plays, how panel_types affects the generated JSON, and whether the output is returned or persisted. It also fails to distinguish this tool from very similar siblings, making it incomplete for reliable agent invocation.

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?

Schema description coverage is 100%, so each parameter is already documented in the schema. The description adds little beyond the phrase 'panels and data sources', which loosely maps to panel_types but does not clarify how data sources are selected or how service_name and dashboard_name are used. Baseline 3 is appropriate because the schema handles the heavy lifting.

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 a specific action and resource: 'Generate Grafana dashboard JSON with panels and data sources'. It conveys what is produced, but it does not differentiate the tool from the closely related sibling tools like grafana_generate_dashboard or prom_generate_dashboards, which likely have overlapping purposes.

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?

There is no when-to-use or when-not-to-use guidance. The description only states what the tool does and does not mention alternatives such as grafana_add_panels or grafana_generate_dashboard, so selecting among the Grafana/monitoring siblings is left entirely to inference.

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