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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only implies a read-only operation via 'Retrieves' but does not mention permissions, pagination, rate limits, or any side effects. This is minimal disclosure for a tool that likely fetches a list of accounts and properties.

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 wasted words. It is front-loaded with the action and clearly states the resource. It is appropriately concise for a tool with no parameters and no complex logic.

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 that the tool has no parameters and an output schema exists (which likely describes the returned summary structure), the description is largely complete for its purpose. It clearly identifies the domain (Google Analytics accounts and properties). A slight gap is that 'summaries' is vague, but the output schema should resolve this. Overall, adequate for a simple read-only listing tool.

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 the schema coverage is 100% vacuously. According to the rubric, a 0-parameter tool receives a baseline score of 4. The description does not need to explain parameters, and it appropriately omits any parameter details.

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 ('Retrieves') and a clear resource ('the user's Google Analytics accounts and properties'). It is not a tautology and conveys the primary function. However, it does not explicitly differentiate itself from sibling tools like get_property_details, which also deals with properties, leaving some ambiguity about the scope of 'summaries'.

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 no guidance on when to use this tool versus alternatives. It does not mention any distinguishing conditions, such as when to use get_property_details for a single property instead. This is a clear gap for an agent trying to select the appropriate tool.

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 of behavioral disclosure. It only states 'returns' without explicitly noting read-only behavior, permissions, error handling, or rate limits. The sparse wording leaves the agent without important context for a non-trivial operation.

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, front-loading the core purpose. Every word is necessary and it is appropriately sized for a simple tool.

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 is simple with one well-documented parameter and an output schema, so the description does not need to explain return values. However, it lacks any usage context or mention of when to call it, which is a gap given the sibling tools. It is minimally complete but not comprehensive.

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 description does not mention the parameter at all, but the schema provides a detailed description of property_id with accepted formats, achieving 100% coverage. Baseline is 3 since the schema fully documents the parameter.

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 ('Returns') and resource ('the property's custom dimensions and metrics'), making the tool's function clear. It is distinct from siblings like get_account_summaries or run_report, which have different purposes.

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 provided on when to use this tool versus alternatives. The description does not mention conditions, prerequisites, or exclusions, leaving the agent to infer usage from the name alone.

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 must carry behavioral context. 'Returns details' implies a read-only operation)Skip no mutation is signaledasi. Still, it does not disclose authorization needs, rate limits, or any side effects. This is adequate for a simple getter but not rich.

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 short, front-loaded with the core purpose, and uses a compact bullet list for the parameter formats. Every sentence contributes useful information with 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?

For a single-parameter getter with an output schema present, the description is largely complete: it defines the purpose and the exact accepted parameter formats. The main missing piece is usage/alternative context, but that is not essential for a straightforward read operation.

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 only states that property_id can be an integer or string. The description adds meaningful detail by specifying the accepted formats, including the 'properties/' prefix form. This fully covers the single parameter and goes 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 a specific verb and resource: 'Returns details about a property.' It is distinct from sibling tools like run_report or list_google_ads_links. However, 'details' is somewhat vague and could be more explicit about what information is included.

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 guidance about when to use this tool versus alternatives. It does not mention exclusions, prerequisites, or scenarios where a sibling tool would be more appropriate, so an agent must infer usage from the name.

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 behavioral burden. Saying 'Returns a list' signals a read-style operation and the property scoping is useful, but it does not disclose other traits such as whether links have statuses, whether filtering exists, or whether any authentication nuance applies.

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 wasted words. The action, object, and scope are immediately clear.

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 list tool with an output schema, the description is nearly sufficient. It may lack explicit alternatives and deeper behavioral nuance, but these are minor given the tool's low complexity.

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 only parameter, property_id, is well documented with accepted formats. The description adds little beyond reinforcing that the list is scoped to a property, so 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 uses a specific verb ('Returns a list of') and names the resource ('links to Google Ads accounts') and scope ('for a property'). It is clear, though it doesn't explicitly differentiate from sibling tools like get_account_summaries or get_property_details.

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 should be used when a list of Google Ads links for a property is needed. It does not provide explicit guidance about when to prefer it over alternatives or when not to use it.

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 full burden. It clearly implies a read operation with 'Returns,' and the explanation of annotations adds domain context. It does not disclose pagination, authorization requirements, error behavior, or explicitly state it is read-only, but it is not misleading.

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 concise and front-loaded with the core purpose in the first sentence. The additional sentences provide useful domain context about annotations without excessive 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?

For a simple one-parameter tool with a rich input schema and an output schema, the description covers purpose and domain context effectively. It lacks mention of pagination or permissions, but these are not critical given the tool's simplicity and the presence of an output schema.

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 property_id parameter fully documented including accepted formats. The description adds no additional parameter semantics, so 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 verb and resource: 'Returns annotations for a property.' The resource is distinct from sibling tools such as run_report or get_property_details, but no explicit differentiation is made.

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 explains what annotations are and typical use cases (service releases, marketing campaigns, traffic changes), which implies when this tool might be useful. However, it does not explicitly state when to use this tool versus alternatives or provide any 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 behavioral burden. It discloses a key limitation: dimension_filter and metric_filter are applied independently, with detailed examples of what cannot be expressed and workarounds. It also mentions quota management and pagination via limit/offset. However, it omits operational details like realtime data latency (~30 min window) and that the operation is read-only, though these are somewhat implied by the nature of a report. The thorough filter-limitation disclosure elevates this above average.

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 very long and contains redundant sections: the identical 'Notes' about filter independence appears twice (once under dimension_filter, once under metric_filter). More problematically, it includes a 'Hints for date_ranges' section even though date_ranges is not a parameter in the schema, which could mislead the agent. The structure is front-loaded with a clear purpose but suffers from repetition and an irrelevant block, reducing efficiency.

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 tool with 9 parameters, nested objects, and complex filter logic, the description is highly complete. It covers all parameters with examples, cross-references supporting tools, and provides strategic advice for handling filter limitations. The presence of an output schema means return values don't need explanation. The main gap is the phantom date_ranges hints and a slight lack of explicit realtime data-window constraints, but overall it is thorough enough for an agent to invoke 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?

Although the schema already documents every parameter (100% coverage), the description goes far beyond by providing concrete JSON examples for dimension_filter, metric_filter, and order_bys, and by linking each complex parameter to dedicated hint tools. It clarifies accepted formats for property_id and enforces that dimensions must be realtime dimensions, metrics must be realtime metrics. This is exemplary parameter guidance that adds substantial meaning 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 opens with 'Runs a Google Analytics Data API realtime report.' — a specific verb and resource that immediately distinguishes it from the sibling run_report (standard reporting). The term 'realtime' in the first sentence and in the tool name makes the scope 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?

While it doesn't explicitly compare to run_report, the description clearly frames when realtime data is appropriate and guides the agent to supporting tools (get_standard_dimensions, get_custom_dimensions_and_metrics, and the hint tools). It also provides decision guidance for complex filter combinations, offering two strategies and recommending one based on quota. This is more than implied usage, though it stops short of an explicit 'use this instead of X' statement.

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 of behavioral disclosure. It effectively communicates key behaviors: snake_case field naming, the independent application of dimension and metric filters, pagination via limit/offset, quota considerations, and the requirement that order_bys must reference included dimensions/metrics. It does not mention idempotency or side effects, but for a read-only report this is acceptable.

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 extremely long and repetitive, with the same note about dimension_filter and metric_filter independence appearing verbatim twice. While it is structured with headings and examples, the redundancy and sheer length prevent it from being concise; many sentences could be consolidated.

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 tool with 11 parameters and nested objects, the description is remarkably complete. It covers argument formats, examples, behavioral limitations, pagination, quota, and even workarounds for complex filters. The presence of an output schema means return values need no explanation, and nothing essential for correct usage appears 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%, but the description goes far beyond the schema by providing detailed hints, worked examples for date_ranges, filters, order_bys, and clarifying the snake_case convention. It also explains constraints like the independence of filters and the requirement that order_bys reference included fields, adding significant value for correct invocation.

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 'Runs a Google Analytics Data API report,' which is a specific verb and resource. It distinguishes the tool from siblings like run_realtime_report by name and the general nature of the report, but it does not explicitly call out the difference, so it falls short of a 5.

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 no guidance on when to use this tool versus alternatives like run_realtime_report. It focuses entirely on parameter details and examples, but does not mention use cases, prerequisites, or exclusions, leaving the agent to infer 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.