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

Beyond the read-only and idempotent annotations, the description discloses key runtime behavior: it returns {"status":"draft"} until publication, the data is a single run reviewed by one person, and confidence intervals overlap. These are material caveats an agent would not learn from the annotations alone.

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 first clause front-loads what the tool returns and the pilot/ranking distinction, and the rest lists the returned metrics efficiently. It is dense and long for a single sentence but every clause conveys relevant scope or return-content detail; minor trimming of statistical field names could improve it.

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 compensates by enumerating the returned content: hand-verified checkouts with Wilson intervals, cart-or-better outcomes, blocks, median steps and time, cost per checkout, and store × model outcomes. It also states the draft status behavior, leaving little an agent needs to know before calling 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?

The tool takes zero parameters, so the baseline is 4; no parameter documentation is needed. The description adds no parameter information, but none is applicable.

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 names a specific resource (ARC Agent Shopping Index pilot results) and immediately scopes it with 'pilot, not a ranking,' which distinguishes it from the leaderboard sibling. An agent can tell this is a read of pilot benchmark data rather than a ranking or a store-level check.

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?

It clearly frames the context in which the data applies (3 models, OpenRouter personas, 35 non-Shopify stores, one run, one reviewer) and warns that intervals overlap and it is not a ranking, which implicitly routes ranking questions elsewhere. It does not explicitly name alternatives such as agent_leaderboard, so it falls short of a full when/when-not statement.

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