audit

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

The description discloses key behavioral traits beyond the annotatiations: it is a lookup-only operation that never initiates a new third-party audit, and it depends on prior scans by the merchant. It also enumerates the specific output components (score, grade, hard-block status, protocol adoption). This adds significant value beyond the read-only and idempotent hints.

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?

Two sentences, each earning its place: the first states the purpose and output details, the second explains the precondition and non-behavior. The information is front-loaded and tightly packed without redundancy.

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 simple one-parameter, read-only tool with no output schema, the description is complete. It explains the return values, the precondition, and that no new audit is triggered. It is sufficient for an agent to select and invoke the tool correctly.

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 schema already provides a good description of 'host' with an example, and coverage is 100%. The description adds the constraint that scores only exist for stores that have been scanned, which gives the parameter contextual validation. This goes beyond the schema's basic type description.

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 checks an AI agent's ability to buy on an e-commerce store and returns a deterministic readiness score with grade, hard-block status, and protocol adoption. It distinguishes itself from triggering a new audit, making its purpose specific. The verb 'Check' and resource 'host' are explicit.

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 provides clear context: scores exist only for stores that have been scanned, and this tool never triggers a new audit. This implies when to use it (for existing scans) and when not (for new audits), though it doesn't explicitly name alternatives like list_agent_ready_stores. This is strong guidance but falls short of fully contrasting with sibling tools.

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 declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds behavioral context by specifying the grade cutoff (B or better) and ranking logic, which are useful 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 three sentences, front-loaded with a clear purpose, then use cases, then parameter options. Every sentence earns its place with no redundancy or fluff.

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's simplicity (2 optional params, no output schema), the description adequately covers purpose, use cases, and parameter behavior. It doesn't enumerate return fields, but for a list tool with a scoring metric, this is sufficient.

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% (both limit and vertical are described). The description mentions 'filter by vertical and cap the number of rows,' which aligns with the params but adds little beyond what the schema already states. Baseline 3 is appropriate as the schema does the heavy lifting.

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 lists e-commerce stores meeting a specific criterion (grade B or better) and ranks them by an agent-readiness score. This distinguishes it from siblings like check_merchant_readiness (which likely checks a single merchant) and get_readiness_report (which likely provides a detailed report).

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 explicitly provides two use cases: routing purchases toward reliable stores and benchmarking stores against peers. It does not explicitly name alternatives or state when not to use, but the use cases give clear context for when this tool is appropriate.

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