update_existing_dashboard

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

Annotations already declare destructiveHint=true and readOnlyHint=false, but the description adds essential behavioral context: the partial overwrite semantics and the critical warning that there is no undo and previous state is not recoverable. This goes beyond the structured annotations and is highly valuable for an agent deciding whether to invoke the tool.

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 three sentences, front-loaded with the main action, and every sentence carries meaningful information. There is no redundant fluff, and the warning is placed at the end as an important caveat. It is appropriately concise for the tool's complexity.

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 8 parameters, a required dashboard_id, and an output schema, the description covers the essential context: what it does, when to use it, the partial-update semantics, and the destructive irreversibility. The annotations cover idempotency and read-only hints, so the description does not need to repeat those. No critical context is missing for safe and correct 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?

The input schema has 100% description coverage for all parameters, so the baseline is 3. The description adds value by explaining the general parameter behavior ('anything omitted is unchanged') and linking parameters to use cases (widgets, layout, config). This helps the agent understand that parameters are independent and optional, with no default-resetting behavior.

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 uses a specific verb ('Modify') and resource ('existing dashboard'), and clearly states the update semantics (overwrites given fields, omitted unchanged). It distinguishes itself from sibling tools like get_dashboard_details and create_new_dashboard by explicitly targeting modifications.

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 use cases ('when need to add widgets, change layout, or update dashboard config'). While it doesn't name alternatives directly, the context of sibling tools makes it clear that creation or retrieval are separate. It could be stronger by explicitly saying 'use create_new_dashboard for new dashboards', but the guidance is clear enough.

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