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

No annotations are provided, so the description carries the full disclosure burden, yet it only says the pack 'Includes the complete prompt, usage guide, and edge-case handling' — it never states what the tool returns, whether it invokes a model, or how the prompt pack is delivered. The only behavioral hint is that it is a static prompt bundle rather than an analyzer, which is thin for a zero-annotation 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?

Three short sentences with no bloat, but the lead ('Turn expertise into output') is pure filler placed where the actual purpose should be, and the rest is promotional rather than informative. It is concise without being useful.

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 prompt-pack tool with no output schema and no annotations, the description should explain what artifact the caller receives (prompt text, guide, checklist) and what a 'dashboard diagnosis' covers. Instead it leaves the return content and diagnostic scope undefined, which is inadequate given the complexity signals.

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?

There is a single optional parameter with 100% schema description coverage ('Optional user query to scope the analysis'), so the schema already fully documents it. The description adds nothing about how the query influences the output or what happens when it is omitted; baseline 3 applies.

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 restates the name ('dashboard diag tool prompt pack') and adds marketing language about 'professional results in minutes' without stating what operation the tool actually performs or what a 'diag' produces. It never distinguishes the tool from dashboard-analyze-tool, dashboard-board-tool, dashboard-formula-tool, or dashboard-tpl-tool, all of which share the same prefix.

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?

'Helps restaurant and brand teams produce professional results' gestures at an audience but gives no when-to-use criteria, no prerequisites, and no routing guidance against the many sibling dashboard tools. An agent has no basis for choosing this over dashboard-analyze-tool or dashboard-formula-tool.

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