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

Annotations already declare readOnlyHint and destructiveHint=false, and the description affirmatively confirms 'Read-only' while adding substantial behavioral context: the tool reads 'off the live records, never typed', enforces a mandatory caveat, and clarifies that the Sato Score is an openness/activity/verifiability grade, not a safety or quality rating. This is meaningful disclosure beyond the annotations.

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?

The description is compact relative to the information it carries, and the purpose is front-loaded in the first sentence. Every section (context, rule, semantics, return shape, example) serves a purpose, though the return-shape field listing and the example could arguably be trimmed without loss.

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?

With no output schema, the description carries the full burden of explaining return values — and it does, specifying the exact JSON shape including a, b, rows, caveat, rules, comparison_page, and source. It also includes a mandatory-rule caveat and an example call. For a tool of this complexity, nothing needed to invoke it correctly is missing.

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%, so the schema already documents all three parameters with examples and the response_format enum. The description adds a concrete example invocation ({ a: 'coinbase-agentkit', b: 'solana-agent-kit' }) which is mildly helpful, but does not materially extend the schema's parameter meaning — hence the baseline 3.

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 opens with a specific verb-resource question — 'how do these two directory listings compare on the axes Sato Hub tracks for both?' — and lists the exact axes returned. This clearly distinguishes it from siblings like get_metrics or get_listing_history, which track a single listing over time rather than comparing two.

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 description gives strong context on when this tool is appropriate: it answers a pairwise comparison question and returns the same table the /compare pages render. It also states what the tool cannot do — there is NO winner field and none can be derived — which functions as an explicit 'when not to use' rule, though it does not name sibling alternatives like search_agents or get_listing_history by name.

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