audit

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

Annotations already cover readOnly, idempotent and non-destructive, and the description adds meaningful context beyond them: it never triggers an audit, it reads the stored score, and it explains the hard-block semantics including the orders_blocked case. It stops short of describing freshness/staleness of the stored score or error behavior when the host is unknown.

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?

Front-loaded with the core action and score outcome, then the routing instruction to scan_store. It is dense but every clause (hard-block, protocol adoption, no-audit, fallback) adds information; the heavy parenthetical could be split for readability but nothing is wasted.

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 what is returned: /100 score, grade, hard-block status and agent-protocol adoption (UCP, A2A, ARD). Combined with the fallback path for unscored hosts, an agent has everything needed to call and interpret this 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 single host parameter is documented in the schema with an example, so the schema carries the load. The description adds no format guidance beyond that, which is the expected baseline for a fully documented single parameter.

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?

States a specific verb and resource (check merchant/agent readiness for a host) and scopes it precisely: a deterministic /100 score for agent findability, comprehension and purchase. It clearly distinguishes itself from siblings like scan_store by being the read-only lookup.

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?

Explicitly states when to use it ('reads the latest stored score and never triggers an audit') and names the alternative for the opposite case ('if the host has no score yet, call scan_store to run one'). This is exactly the when/when-not/alternative guidance the dimension rewards.

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

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is clear. The description adds meaningful context: the report is public (same visibility as the web report) and describes the returned data structure. This goes beyond the annotations without contradicting them.

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 two sentences, front-loaded with the main purpose, and every clause adds value. It is concise yet information-dense, covering the object, scope, contents, and access level without unnecessary words.

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?

Given the tool has one required parameter, a read-only operation, and no output schema, the description sufficiently explains what the tool returns (check statuses, score, grade, link) and its public nature. This is complete for an agent to invoke it correctly without additional context.

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 input schema already covers the single 'host' parameter with a clear description and example. The tool description does not add additional parameter-level meaning, so it earns the baseline score for schema coverage being high (100%).

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 clearly states the tool retrieves the latest public agent-readiness report for a scanned store, specifying the report's contents (checks, statuses, pillars, score, grade, link). This distinguishes it from siblings like list_agent_ready_stores (listing stores) and check_merchant_readiness (likely initiating/checking readiness).

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 implies usage for a specific scanned store's latest report ('scanned store' suggests prerequisite), but does not explicitly state when to prefer this tool over alternatives or when not to use it. No alternative tools are mentioned by name, so guidance is only implied rather than explicit.

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

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the description's job is to add domain meaning. It does: it defines the inclusion criteria ('grade B or better and no block found') and the ranking basis ('score /100'), which tells the agent what set it is querying. It does not describe pagination or the shape of returned rows.

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?

Three sentences, front-loaded with what the index is before the usage guidance. No filler, though the second sentence is slightly dense with parenthetical criteria that could be trimmed.

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 some burden for return semantics, and it does convey the ranking dimension and inclusion criteria, which implies the relevant fields (score, grade, block status, vertical). It stops short of enumerating row fields or ordering rules, but an agent has enough to call and interpret the 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 description coverage is 100%, so both parameters (limit, vertical) are already documented with defaults and bounds. The description only restates them ('optionally filter by vertical and cap the number of rows') without adding format, allowed values, or behavior details beyond the schema. Baseline 3 applies.

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 states a specific resource and scope: a ranked index of e-commerce stores that pass an agent-readiness bar (grade B or better, no block found), scored /100. That is far more concrete than a bare 'list stores'. It never names the sibling tools (check_merchant_readiness, get_readiness_report), so the differentiation from a single-merchant check vs. a report is only implied by the word 'Index'.

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 gives two clear use contexts: routing a purchase toward a store agents succeed on, and benchmarking a store against peers. There is no explicit when-not guidance and no named alternative, so an agent must infer that per-store checks belong to the siblings.

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

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

Annotations cover the safety profile (readOnlyHint=false, openWorldHint=true, idempotentHint=false), and the description adds material context beyond them: ~30s runtime, public pages only, no order placed, and rate-limiting per caller and globally. This tells the agent both what side effects to expect and that retries may be throttled.

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?

Three sentences, zero waste, front-loaded with the action and its cost, then the return shape, then the routing condition. Every clause earns its place.

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, but the description states the return shape (readiness summary plus public report link) and covers runtime, scope, and rate limits. Nothing an agent needs to call 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 both url and vertical are already documented in the schema. The description adds no syntax or format guidance beyond it, so the baseline 3 applies.

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?

States a specific verb and resource ('Run a fresh AgentReady audit of an e-commerce store') and explicitly scopes the deliverable: the same readiness summary as check_merchant_readiness plus a public report link. An agent can distinguish this from check_merchant_readiness without opening either schema.

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 conditions: use it when check_merchant_readiness reports the host has no scan, or when the user wants a re-measure. It names the alternative tool and the condition that selects it, leaving nothing to inference.

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