ParaSure

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

The annotation only declares readOnlyHint: true. The description goes beyond by disclosing the cost ($0.10 USDC/call), the data source (5 years of Open-Meteo data), and that it 'returns real data, not sandbox.' This is valuable context for an agent deciding whether to trust the output and budget accordingly. No contradictions with 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 four sentences, each containing distinct useful information: pricing, entry-point status, return values, data source, and a usage directive. It is front-loaded with the most important call ordering information. No filler.

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 listing all return components (risk score, perils, historical frequency, overall risk level) and the data source. It also covers cost and usage order. For a two-parameter tool, this is complete and leaves little ambiguity.

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 provides complete descriptions for both parameters, including examples for location and an enum with the note that business type determines relevant perils. The description only restates 'business location and type' without adding new parameter semantics. Since schema coverage is 100%, the baseline score 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?

The description clearly states the tool's function: it takes a business location and type and returns a weather risk score, perils, historical frequency, and overall risk level. This distinguishes it from sibling tools that handle policy binding, quotes, and status checks. The phrase 'entry point for every agent flow' reinforces its primary role.

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 positions this as the mandatory first step: 'Entry point for every agent flow' and 'Always call this first before requesting a quote.' This gives clear when-to-use guidance relative to the sibling tools. No alternative uses are specified, but the directive is sufficient.

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 provide readOnlyHint=false, but the description adds critical behavioral context: returns policy_id, dates, trigger details, confirmation, and the sandbox disclosure that no real carrier is bound, no premium charged, and no coverage issued. This goes well beyond annotations and manages user expectations for a mutating tool.

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, each earning its place: purpose/returns, sandbox caveat, and source of quote_id. It is front-loaded with the primary action and avoids 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?

The description covers the action, return values, and sandbox behavior, which is essential given no output schema. It could be slightly more complete by explaining 'trigger details' or mentioning error cases, but for a 5-parameter tool with clear sandbox context, it is sufficiently complete.

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%, so the description is not required to explain parameters. It does add 'Pass quote_id from get_parametric_quote,' but this is already reflected in the schema description. No additional parameter semantics are provided beyond the schema.

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's purpose with a specific verb and resource: 'Accept a quote and initiate a bind.' This distinguishes it from siblings like get_parametric_quote (which creates quotes) and get_policy_status (which checks status).

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 provides clear context for when to use the tool by instructing to 'Pass quote_id from get_parametric_quote,' implying usage after quote creation. It also warns about sandbox behavior. However, it does not explicitly state alternatives or when not to use it, so it misses the full exclusion 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?

The description discloses valuable behavioral traits beyond the readOnlyHint annotation: it specifies the return contents (observed value vs threshold, trigger met, data source) and honestly notes that production calls NOAA/ERA5 while current data is simulated sandbox data. This is significant context for an agent.

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 long, front-loaded with the core purpose, and every sentence adds value—purpose, return values, and current data source/simulation caveat. No redundancy or filler.

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 simple one-parameter tool, strong readOnlyHint annotation, and clear schema, the description provides complete context: what it does, what it returns, and the production vs sandbox distinction. No output schema exists, but the description covers the return expectations.

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% with the parameter described as 'Policy ID returned by bind_policy,' which fully explains the expected value. The description adds no new parameter-specific details beyond what the schema already provides, so the baseline of 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?

The description clearly states the tool's purpose: to check whether a bound policy's parametric trigger is currently met. It uses a specific verb and resource, distinguishing it from siblings like assess_weather_risk by focusing on a bound policy's trigger rather than general weather risk.

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 the tool is used after a policy is bound, and the schema notes 'policy_id' comes from bind_policy. However, it does not explicitly state when not to use it or directly name alternatives, though the context is clear.

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 declare readOnlyHint=false, so the description doesn't need to restate that. It adds valuable behavioral context: 'Sandbox: carrier and premium are simulated — no real carrier is involved.' It also gives workflow context about passing the quote_id to bind_policy. It does not mention whether the call persists or is idempotent, but the annotation covers the read-only aspect.

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 the purpose, then the return values, then a sandbox caveat and next step. Every sentence adds value without unnecessary detail.

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 6-parameter tool with no output schema, the description covers the main return fields (quote_id, carrier, premium, trigger threshold, payout amount, coverage terms) and a key environmental caveat (sandbox simulation). The schema handles parameter details, so the description is sufficiently complete 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 has 100% coverage with descriptions for all 6 parameters, so the description does not need to add parameter details. It does not go beyond the schema for parameters, but it does mention the returned quote attributes, which is slightly beyond schema. 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?

The description clearly states the action and resource: 'Request a parametric insurance quote for a specific peril and coverage period.' It also lists the returned fields and distinguishes itself from sibling bind_policy by noting the next step, 'Pass the quote_id to bind_policy.'

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 that this tool is for obtaining a quote, and it indicates the follow-up usage with 'Pass the quote_id to bind_policy.' It does not explicitly exclude alternatives like assess_weather_risk, but the purpose is distinct enough that context is clear.

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?

The readOnlyHint annotation is supported by the read-oriented description. The description adds value by noting the sandbox simulation and enumerating the returned fields (client details, trigger threshold, premium, etc.), which informs the agent about data characteristics beyond a simple read flag.

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, front-loaded with the core purpose, followed by specific return fields and a sandbox caveat. No redundant or filler text.

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 tool, the description covers what statuses exist, what data is returned, and the simulated nature of the environment. It lacks only minor details like error behavior, but the output schema is absent so the field list provides sufficient completion.

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 fully documents the single parameter (policy_id) with a clear source ('returned by bind_policy'). The description does not add parameter-specific details, but with 100% schema coverage, 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?

The description clearly states the tool retrieves the full current status of a parametric policy record, listing specific states (active, triggered, settled, expired) and return fields. This distinguishes it from siblings by emphasizing 'full current status' versus more targeted operations.

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 explicit guidance on when to use this tool versus alternatives like check_trigger. Usage is implied by the 'Get the full current status' phrasing, but there are no exclusions or alternative naming. Thus only implied usage.

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 mark read-only, but the description adds valuable context: it is free, and sandbox only contains one carrier. This goes beyond the annotation without contradicting it, though it omits potential rate limits or error behavior.

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 the core action, followed by return contents, environment notes, and usage guidance. Every sentence contributes value 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 parameterless, read-only list tool with no output schema, the description fully covers what it returns, the sandbox constraint, and how it fits into the broader workflow. No critical information 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 has zero parameters, so there is no parameter semantics to elaborate. Baseline for 0 params is 4, and the description enriches the return value expectation instead.

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 all carriers on the ParaSure platform, with specific return fields (name, perils, regions, products). It distinguishes itself from siblings by positioning itself as a discovery step before calling get_parametric_quote.

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 says 'Use this to discover available coverage options before calling get_parametric_quote,' providing a clear when-to-use directive and workflow context. The sandbox limitation also sets expectations for usage in the current environment.

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