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

Discloses substantially more than the readOnly/idempotent annotations: it is a saved automated HTTP check, not a live session or completed order; it does not re-verify the checkout link or rails; it does not test platform/marketplace/network-level blocks; unpublished hosts, OSM, campaign shops and opted-out hosts return unknown; a fallback is http-only with checkout excluded. It also states the advisory nature and licensing constraints. Strongly beyond structured fields.

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 trigger phrases and result-field mapping are well front-loaded, but the body drifts into telegraphic fragments ('JSON: GET /api/precheck?url=.') and repeats the advisory caveat twice ('Results are advisory' / 'Advisory only, not a guarantee'). Several clauses (Data CC BY 4.0, ODbL) are attribution boilerplate rather than selection-relevant content.

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?

No output schema exists, and the description compensates fully by naming every returned field and its meaning (reachable_checkout, rails[], blockers[], last_checked, stale, lastReachableCheck) and explaining how stale freshness fields relate to the verdict. It also covers edge cases (unknown returns, fallback checks) that would otherwise cause the agent to misinterpret a null result as a failure.

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 single url param is already documented with an example. The description adds only marginal meaning — the endpoint form (GET /api/precheck?url=) and that ARC checks the store's own site. Baseline 3 is appropriate when the schema carries the parameter semantics.

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?

Opens with a concrete verb+resource: 'Check if an AI agent can reach checkout on a store before trying.' It also implicitly distinguishes from precheck_bulk ('One call per store'). It never names a sibling tool explicitly (can_agent_checkout, precheck_bulk), so an agent must infer the boundary rather than being routed to it.

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?

Gives explicit trigger phrasings ('can I check out at <store>?', 'is <store> agent-ready?') and a sequencing rule ('Call this first', 'before you hand a shopper a checkout link'). It also caps usage ('One call per store', 'Does not fetch the store and does not start a scan') and warns against misusing negative results. This is exactly the when-to-use guidance an agent needs.

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