CalRisk Insurance Center

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

Annotations already declare readOnlyHint=true, openWorldHint=false and destructiveHint=false, so safety and locality are covered by structured data. The description adds that this is a starting/orientation call and that content is static reference material, but no rate limits, auth requirements or return format are described, so the added behavioral value is modest.

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 short sentences, front-loaded with the resource identity and followed by the actionable directive. Every clause earns its place by listing concrete returned 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?

There is no output schema, but the description compensates by enumerating the categories of information returned (licence, lines, states, contact, hours), which is exactly what an agent needs to decide to call it. With zero parameters and full annotation coverage, nothing material 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?

The tool takes zero parameters, so there is no parameter semantics for the description to clarify; the baseline for a zero-parameter tool applies. The description correctly signals that no inputs are needed by framing this as a plain informational lookup.

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 concrete resource (the agency itself) and enumerates exactly what it returns: licence, lines and states written, contact details and hours. This is immediately distinguishable from the siblings check_appetite, request_quote and start_online_quote, which are all transactional actions rather than static reference data.

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?

"Call this first" gives explicit ordering guidance that tells the agent when to reach for this tool ahead of the others. It stops short of naming alternatives or stating when not to use it, so it falls one step below fully explicit routing guidance.

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, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds the scope (CalRisk writes a line in a US state) but nothing beyond that – no hint that the result is a boolean, no coverage/precision caveats.

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 tightly-scoped sentence with the key qualifiers (line, state, US) front-loaded and zero filler. It is a fragment rather than a verb-led sentence, which slightly weakens scanning, 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?

For a simple two-parameter read-only check with no output schema, the definition is adequate but leaves the return value unspecified – an agent can't tell whether it gets a boolean, a confidence level, or reasons for decline. The core input semantics are fully covered, so this is a modest gap.

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%, with the line enum and the two-letter state format fully documented in the schema. The description only restates 'a given line of insurance in a given US state', adding no format or constraint detail beyond the schema, 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?

The description states a specific determination: whether the named agency writes a given line in a given state. It's clearly a boolean eligibility/appetite check, not a quote or info lookup, though it never names the siblings it differs from (request_quote, agency_info).

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?

No when-to-use guidance is provided: the description does not say to run this before request_quote/start_online_quote, nor any exclusion or prerequisite. Usage must be inferred from the tool name and sibling set.

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=false, destructiveHint=false and openWorldHint=true, but the description adds genuinely useful outcome context: this is 'not a bound policy and no price is promised', a licensed agent follows up, and consent must be obtained before contacting. That clarifies the real-world consequence of the call beyond the 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?

Three tight sentences with no filler, front-loaded on the action and immediately followed by the collection checklist and the expectation-setting caveat. Every sentence carries information.

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 an 8-parameter write-ish tool with no output schema, the description covers the flow, the consent prerequisite, and the expected outcome, which is enough to call it correctly. Minor gaps remain: it does not say whether email or phone is required when the other is absent, nor what a failure/decline looks like.

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 75%, so the schema already documents most parameters including the line enum and the consent semantics. The description restates the same fields ('name, an email or phone, the line, the state and what they need covered') but adds no format or edge-case detail; baseline 3 is appropriate.

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 ('Send a quote request to CalRisk Insurance Center's licensed staff'), which is clearly distinct from a generic info lookup. It does not explicitly contrast itself with the sibling start_online_quote, so an agent must infer that this is the human/agency route versus a self-serve route.

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 implies usage context ('get their OK before calling', agent replies) and lists the information to collect, which functions as an implicit precondition checklist. However, it never states when to prefer this over start_online_quote or check_appetite, and no explicit when-not guidance is given.

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 genuine context beyond them: the link is client-facing and lives on the agency's own quoting platform (openWorldHint=false is consistent with this). It does not state that the tool returns a URL string nor whether the link is single-use or expiring.

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 sentence with no padding, which is efficient, but it is under-specified rather than concise. Nothing about usage or the return value is front-loaded, so it reads more like a label than a usable definition.

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 one-optional-parameter tool with no output schema, the description is nearly adequate, conveying the artifact (a client link) and its delivery channel. It omits the fact that the output is a URL and any routing guidance against request_quote, which is the main gap.

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% with a single enum-constrained 'line' parameter, so the schema already carries the parameter semantics. The description never mentions 'line' at all, adding nothing, but the baseline of 3 applies when 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 identifies the resource (a client-facing quoting link on the agency's own platform), which tells the agent what is being returned. But it is a noun phrase with no verb ('returns', 'generates'), and it never distinguishes itself from the sibling request_quote, which an agent will inevitably confuse it with.

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?

There is no when-to-use guidance and no comparison against request_quote, check_appetite, or agency_info. The word 'client' hints at the audience but the agent is left to infer whether this is for handing to a prospect versus kicking off an internal quote request.

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