grafana_validar_dashboard

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

No annotations, so the description carries the burden; it does disclose what dimensions are inspected, which implies a non-mutating check, but never states explicitly that nothing is written or modified. It also leaves open whether validation fails fast, returns warnings vs errors, or checks live data source connectivity versus static references.

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?

One front-loaded sentence that names the checks immediately; nothing is padded. Minor deduction for the orphaned '19.' prefix, which is noise rather than useful structure.

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?

An output schema exists, so return values needn't be explained, and the enumerated validation targets are the key content. However, for a tool whose only input is an untyped nested object, the definition does not supply enough to call it confidently without inspecting the schema and guessing the payload shape.

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 coverage is 0% and the single parameter is a free-form nested object (additionalProperties: true) with no documentation. The description only says 'um dashboard' and never clarifies whether the argument is the full dashboard model JSON, a trimmed spec, or a uid reference — a real ambiguity given the schema is fully untyped.

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?

States a specific verb ('Validar') and resource ('dashboard') plus the three things checked: structural integrity, data source references and syntax. That distinguishes it from sibling tools like grafana_testar_consultas_dashboard (query testing) and grafana_testar_fonte_dados (connection testing). The leading '19.' is stray numbering noise, but the purpose itself is unambiguous.

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?

No guidance on when to call it — before creating/updating a dashboard, after import, or as a pre-flight check — and no mention of the adjacent validation siblings it overlaps with. An agent must infer both the trigger condition and where the dashboard payload should come from (e.g., grafana_obter_dashboard).

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