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

With no annotations, the description carries the full burden of disclosing behavior. It clearly states the core transformation (place to coordinates), but it does not mention output format, coordinate order, ambiguity handling, or whether multiple results may be returned. This is adequate but minimal.

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 one compact, front-loaded sentence with no redundant words. Every part contributes to understanding the tool's function.

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 single-parameter, low-complexity tool with no output schema, the description is largely sufficient: it names the input and the output type. Minor gaps like coordinate format or multiple-match behavior prevent a perfect score, but the tool is simple enough that this is not a major omission.

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%, and the query parameter is already well documented with an example. The description reinforces the meaning by mentioning 'city or address' but adds little beyond the schema, 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 uses a specific verb ('Resolve') with a clear resource ('a city or address') and outcome ('latitude and longitude'). This distinguishes it from the weather-related sibling tools, making its purpose unambiguous.

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 when geographic coordinates are needed, and the sibling tools are clearly weather-related, so there is no real conflict. However, there is no explicit guidance about when to use this tool versus alternatives or any stated exclusions/prerequisites.

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?

With no annotations, the description carries the full burden and does disclose the API source and the core behavior of returning current conditions. It does not mention response shape, default unit behavior, or what happens if both place and coordinates are supplied, but for a simple read-only weather tool the disclosure is adequate.

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 entire description is a single 14-word sentence that front-loads the essential purpose. There is no filler or repetition of the schema.

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 current-weather tool with no output schema, the description covers what the tool returns and the two ways to specify location, while the input schema covers parameter details. It could mention request precedence or return fields, but nothing critical 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 coverage is 100%, so the schema already documents query, units, latitude, and longitude. The description adds only the high-level distinction that a place or coordinates can be used, which is already visible in the schema, so it stays at the baseline.

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 a specific verb and resource: retrieving current conditions from the Weather API, for either a place name or coordinates. 'Current' helps distinguish it from the hourly and daily forecast siblings, though it does not explicitly differentiate it from get_weather_dashboard.

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 for current conditions, which an agent can infer should be used instead of hourly or daily forecasts. However, it gives no explicit when-to-use or when-not-to-use guidance and does not name alternative 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?

With no annotations provided, the description carries the full burden. It discloses the default forecast length and data source, but omits location resolution behavior, units assumptions, whether coordinates and query are alternative inputs, and what happens if no location is supplied.

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 a single sentence with no filler. It conveys the core purpose, source, and default behavior efficiently, even though it could be more informative.

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?

Without an output schema or annotations, the description leaves important gaps: how location is specified, which parameters are expected, whether units default to metric, and what the returned forecast contains. The agent is not equipped to decide between this and the dashboard or hourly tools from the description alone.

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 80%, so parameters are mostly documented there. The description adds the default value of 10 for 'days', which is not in the schema, but it does not clarify the relationship between query and latitude/longitude or the units default.

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 provides a daily forecast from the Google Weather API and notes the default 10-day window. The 'daily' scope distinguishes it from current and hourly forecast siblings, though it does not explicitly name or contrast alternatives.

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 guidance is given for when to use this tool versus get_current_weather, get_hourly_forecast, or get_weather_dashboard. The only implicit signal is 'daily' in the description; there are no explicit when-to-use conditions or exclusions.

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?

With no annotations, the description carries the full transparency burden. It only adds the source API and default/max hour window; it does not disclose return format, how query relates to latitude/longitude, error behavior, or side-effect safety. The 'get' prefix implies read-only, but significant behavioral unknowns remain.

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 one compact sentence with no wasted words. It front-loads the primary purpose and includes the most important operational constraints. Every phrase 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?

The tool has no required parameters, no output schema, and no annotations, yet the description never explains that a location (query or coordinates) is needed. It also omits what the response looks like. While schema coverage helps for parameter meaning, the overall definition is not complete enough for a new agent to invoke it with confidence.

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 high at 80%, so the schema already documents query, units, latitude, and longitude. The description adds value by stating the default of 24 hours for the hours parameter, which is not present in the schema. It does not describe all params, but the schema handles most of that burden.

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 names the tool's function: returning an hourly forecast from the Google Weather API. It distinguishes this from siblings like get_current_weather and get_daily_forecast by the temporal granularity ('hourly'). The addition of 'default 24 hours, max 240' gives immediate scope.

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 hourly weather projections but does not explicitly state when to choose this over get_daily_forecast, get_current_weather, or get_weather_dashboard. No exclusions or alternatives are named, so the agent must infer selection from the tool name and sibling names.

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?

No annotations are provided, so the description carries the disclosure burden. It discloses the core behavioral scope—combined current, 24-hour, and 10-day data—but does not address response format, location-resolution behavior, or edge cases such as missing or ambiguous locations.

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 short sentences with the core behavior front-loaded and a practical use-case statement following it. There is no filler or redundant 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?

The description names the returned forecast slices and gives a solid basic contract, but with no output schema and four optional parameters it leaves important invocation details implicit, such as whether query or lat/long is preferred or required. It is adequate but has clear gaps for fully confident invocation.

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 the input schema already documents query, units, latitude, and longitude; the baseline is therefore 3. The description adds little beyond 'for a location' and does not clarify how query relates to lat/long parameters, though the schema covers their individual meanings.

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 that the tool returns a bundled resource—current conditions, 24-hour forecast, and 10-day forecast—for a location, which distinguishes it from get_current_weather, get_hourly_forecast, and get_daily_forecast. It uses a noun phrase rather than an explicit action verb like 'returns', so it is clear but not maximally 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 phrase 'Best for filling a weather UI' gives a concrete use case and implies this is the consolidated choice when an agent needs all forecast slices together. It does not explicitly name alternatives or state when not to use it, but the context is reasonably clear.

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