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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered. The description adds useful context that the content is static reference material mirrored from 7be.io/llms.txt, which tells the agent results are stable and citable. It says nothing about pagination or output shape, but neither is a concern for a one-section lookup.

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?

Two sentences, front-loaded with the substantive content and the concrete price fact, followed by a provenance note. Nothing is redundant, though the parenthetical price detail is slightly more specific than needed for a routing decision.

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 single optional enum parameter tool with no output schema, the description covers subject matter, scope, and source of truth adequately. The only gap is the absence of routing guidance versus the store-focused siblings, which is a minor omission for a self-contained reference tool.

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 coverage is 100% and the enum already documents all twelve sections, so the schema carries the parameter burden. The description adds mild semantic value by mapping some section names to content ('how AI orders are counted', 'platforms and key pages') and implying the default behavior of returning everything. Baseline 3 applies when the schema does the heavy lifting.

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 enumerates exactly what the tool returns: what 7BE is, its pricing model (10% of each order), how AI orders are counted, platforms and key pages. That is far more specific than the title 'About 7BE'. It doesn't explicitly contrast with siblings like find_stores, but the informational nature is unmistakable.

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?

Usage is only implied: an agent should call it when it needs background on pricing or measurement. There is no explicit when-to-use/when-not statement and no mention of when to prefer find_stores or store_ai_visibility instead. The llms.txt reference hints that this is the canonical FAQ source, but that is inference rather than guidance.

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