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

No annotations are supplied, so the description carries the full disclosure burden, yet it only says the pack "includes the complete prompt, usage guide, and edge-case handling" — vague boilerplate that does not clarify whether the tool returns a reusable prompt template, performs an actual analysis, or emits guidance text. Nothing is said about output format, whether the optional query scope changes behavior, or any limits.

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 sentences that are almost entirely promotional filler: "Turn expertise into output" and "produce professional results in minutes" carry no selection signal. The one informative clause (contents of the pack) is buried at the end rather than front-loaded.

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 one-parameter, no-annotation, no-output-schema tool the description still needs to explain what the analysis produces and how it differs from the many related retention and analysis tools. It instead describes the deliverable as a "prompt pack," which leaves the agent unable to predict the response or confirm 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?

There is a single optional parameter whose schema description coverage is 100%, so the schema already explains 'query' adequately. The description adds no meaning beyond it — it never mentions scoping, defaults, or what happens when query is omitted — so the 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 tool name ("retention analyze tool prompt pack") and wraps it in marketing language ("Turn expertise into output", "professional results in minutes") without ever saying what retention analysis is performed, what inputs it expects, or what kind of result is produced. It does not distinguish this tool from the four sibling retention tools (retention-board-tool, retention-diag-tool, retention-formula-tool, retention-tpl-tool).

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 only contextual hint is an audience ("restaurant and brand teams"), with no statement of when to choose this tool over the retention-board/diag/formula/tpl siblings. There are no prerequisites, exclusions, or triggering conditions, so an agent has to guess from the name alone.

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