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 and largely drops it. It never says whether the tool reads or generates content, what it returns (a prompt template? an analysis report?), whether the optional query changes behavior, or what happens with an empty query. 'Save hours every week' and 'battle-tested' are promotional claims, not behavioral facts.

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?

It is short, but the opening sentence is a marketing benefit claim rather than purpose, and 'battle-tested' and 'Save hours every week' do no descriptive work. The operative information is buried in the middle of the second sentence instead of being 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?

The tool is low-complexity (one optional param, no output schema, no annotations), so the description should be able to fully cover it, yet it leaves the return value and the effect of the query argument unexplained. An agent cannot predict what it will get back or how to phrase the call.

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, so the schema already explains that 'query' scopes the analysis. The description adds no syntax, format, or example for that parameter, so the baseline 3 applies rather than anything higher.

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 identifies a domain (retention diagnostics for restaurant/brand growth) and a deliverable type ('prompt and operating playbook'), which is more than a bare restatement of the name. However, 'toolkit' and 'playbook' are vague about the actual operation, and it never distinguishes this from the many sibling retention tools (retention-analyze-tool, retention-board-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?

There is no when-to-use guidance, no prerequisites, and no mention of any alternative. The nearest thing to guidance is 'No setup, works in any LLM chatbot', which describes portability rather than the situation that should trigger this tool over its many retention-* siblings.

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