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

No annotations are supplied, so the description carries the full behavioral burden and largely fails it: it never states the return shape, whether the output is static boilerplate or generated per call, or what the optional query actually changes. The claim of a "battle-tested prompt" implies the payload is a fixed prompt asset, which is the one useful signal, but nothing else about execution is disclosed.

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 lead sentence ("Save hours every week") is pure marketing and occupies the position where the core function should be. Front-loading a benefit over the verb-plus-resource wastes the most valuable line of the definition.

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?

Complexity is low — one optional parameter, no output schema, no nested objects — so the bar is modest, and the description does convey that a reusable prompt/playbook asset comes back. Still missing is what the template actually contains and how it differs from the gen/check siblings, which an agent needs in order to pick correctly.

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 at 100% schema description coverage, so the schema already explains "query" as scoping the analysis; baseline 3 applies. The description adds no meaning beyond that — it never mentions the parameter or how scoping alters the returned template.

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 calls itself a "tpl tool toolkit" that gives "a battle-tested prompt and operating playbook for restaurant/brand growth" — it restates the name rather than stating a concrete verb and resource. It never says whether the tool returns a template, renders a prompt, or produces a document, and it does nothing to separate itself from ir-kb-gen-tool or ir-kb-check-tool in the same family.

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 instruction, no condition that selects this tool over its ir-kb siblings, and no prerequisites. The only usage-adjacent claim, "works in any LLM chatbot," is about the artifact rather than about when an agent should call this tool.

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