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 it discloses nothing about what happens on invocation, whether a working directory or data is required, what framing the 'playbook' imposes, or what comes back. 'No setup' actively implies a zero-input behavior that the optional query parameter does little to clarify.

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?

Only three sentences, but all of them are promotional filler ('Save hours every week', 'battle-tested', 'No setup, works in any LLM chatbot') that convey no operational information. Brevity without substance is under-specification rather than conciseness.

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 structurally simple (one optional param, no output schema, no annotations), which lowers the bar, but the description still gives an agent no basis for choosing it over dozens of near-identical diagnostic siblings or for predicting its output. An agent could invoke it, but could not justify invoking it.

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?

Schema description coverage is 100% for the single optional 'query' parameter, so the schema already explains its meaning and the description adds nothing beyond it. Per the high-coverage baseline, 3 is the appropriate ceiling here, though the description conspicuously never acknowledges the query parameter exists.

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 never states a concrete operation — it advertises 'a battle-tested prompt and operating playbook for restaurant/brand growth' rather than saying what the tool produces or analyzes. 'Channel diag' in the name implies channel diagnosis, but the text only restates the value proposition, and it does nothing to separate itself from the many sibling *-diag-tool and fnb/restaurant diagnostic tools.

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 indication of when to use this tool, when not to, or which of the numerous sibling tools (channel-analyze-tool, channel-board-tool, channel-formula-tool, fnb-store-diagnostic, restaurant-ops-diagnostic) it should be preferred over. 'Works in any LLM chatbot' is a marketing claim, not usage guidance.

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