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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and closed-world, so 'Reads only' adds nothing. However, with no output schema the description usefully discloses what comes back: immutable versioned URLs plus latest/ aliases in two formats, row counts, method version, and licence terms (CC-BY-4.0, attribution ARC). That return-shape detail is real value 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?

A single dense sentence, front-loaded with the resource and its contents. The store_answers parenthetical is the one slightly off-topic insertion, but it is short and does not bury the core payload.

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 parameterless metadata tool with no output schema, the description covers the essentials an agent needs: what the snapshot is, what fields it exposes, the formats and alias scheme, and the licence. It does not mention pagination or size limits, but those are largely inapplicable here.

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 there is nothing for the description to disambiguate; the baseline for a parameterless tool applies. No parameter claims are made that could mislead.

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 ('Latest open ARC dataset snapshot') and enumerates its contents (immutable versioned download URLs, latest/ aliases in CSV and Parquet, row counts, method version, licence). It is clearly distinguishable from the sibling tools, which all concern stores, agents, or leaderboards rather than dataset metadata, though it never states a verb like 'returns' or 'describes'.

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 parenthetical 'start with store_answers: one plain answer per store on whether AI agents can find products and get a checkout link' gives a starting point for analyzing the dataset, but it does not say when an agent should call dataset_info versus siblings such as ask_arc or get_agent_facts. Usage is only implied.

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