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

Beyond the provided annotations (openWorldHint=false, destructiveHint=false), the description discloses the three-state return contract: true, false, or null, with null's reason values 'dismissed' or 'error'. It also explains that this is a blocking elicitation and advises 'ask again later' behavior for null results. This is rich behavioral context that the annotations do not carry.

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 compact and front-loaded: it opens with the core action, immediately distinguishes from elicit_form, and then gives the essential return contract. Every sentence carries functional information; there is no filler or repetition of schema details.

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 only 3 parameters, an output schema, and annotations, the description is fully sufficient. It covers when to use it, the exact return semantics including edge cases, and the relationship to siblings. No critical operational detail appears to be missing for an agent to invoke it 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 input schema already covers all parameters at 100% with descriptive text for message, labels, and timeoutSeconds. The description adds contextual meaning around the message as a 'single yes/no question' and labels via the JS confirm() model, but it does not substantially augment the parameter semantics beyond the schema. Baseline 3 is appropriate for complete schema coverage.

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 verb ('Ask'), a specific resource ('the user an OK/Cancel confirmation'), and explicitly positions the tool as a convenience wrapper over elicit_form modeled on JavaScript's confirm(). It also distinguishes it from sibling elicit_form by stating 'Use this for a single yes/no question.' An agent can immediately understand what this tool does and how it differs from at least one sibling.

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 gives explicit usage guidance: 'Use this for a single yes/no question; use elicit_form to collect arbitrary fields.' This tells the agent when to choose this tool over an alternative. The return semantics also clarify how to treat the result, and the caveat about 'no answer was obtained' reinforces appropriate re-prompting behavior.

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?

Beyond the readOnlyHint annotation, the description discloses that the default is a passive report derived from the initialize handshake and, critically, that probeElicitation:true runs a live round-trip and 'the user may see a dialog'. 'Read-only; safe to call anytime' aligns with the annotations rather than 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?

Purpose is front-loaded in the first clause, and each subsequent sentence carries distinct information: use cases, probe behavior, and safety. Nothing is wasted, but it is a single dense paragraph whose length could be relieved by light restructuring.

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?

The output schema covers return values and the annotations cover the read-only safety profile, so the description only needs to cover purpose, usage, and side effects — which it does. The sole gap is the absence of an explicit when-not-to-use statement.

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 schema's own description of probeElicitation already documents the default, the dialog side effect, and the output field (probes.elicitationForm). The description adds only framing ('classify what really happened'), so the baseline of 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: 'Check whether the connected MCP host actually supports elicitation (and sampling/roots)'. The title 'Diagnose the host's elicitation support' and the explicit naming of siblings (elicit_form/elicit_confirm) make its diagnostic role unambiguous and clearly distinguish it from the action tools it gates.

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 three concrete use cases — deciding whether to call elicit_form/elicit_confirm, explaining why a prompt did or didn't appear, and contributing a capability fingerprint — and names the alternative tools explicitly. It lacks an explicit when-not-to-use exclusion, which keeps it a point below the top.

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 only indicate non-destructive and non-open-world behavior, so the description adds value by stating the return format and the sensitive-content restriction. It does not describe cancellation behavior, but the output schema likely covers expected outcomes.

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 concise sentences, each earning its place: purpose, alternative, and safety constraint. Front-loaded with the core action and return value, with no redundant wording.

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 form elicitation tool with a rich schema, an output schema, and clear annotations, the description covers purpose, usage, safety, and return shape. Nothing critical is missing for an agent to select and invoke it 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?

Schema description coverage is 100%, so every parameter is already documented in the schema. The description adds little beyond the schema, mentioning 'caller-supplied JSON schema' and the raw return, which is acceptable given the high coverage.

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 action ('trigger a form elicitation'), the resource ('caller-supplied JSON schema'), and the return value ('raw {action, content}'). It also distinguishes itself from the sibling elicit_confirm, so an agent can immediately tell which tool to use.

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 directs agents to prefer elicit_confirm for plain OK/Cancel questions and forbids use for secrets or credentials. This gives clear when-to-use and when-not-to-use guidance, including a named alternative.

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