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

With no annotations provided, the description must fully disclose behavioral traits. It indicates an authorization action (likely a mutation) but does not mention permissions, reversibility, side effects, or response behavior. This is insufficient transparency for a mutation 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 a single sentence, achieving conciseness. However, the brevity sacrifices clarity on behavioral details. It could be slightly expanded to include usage context without becoming verbose.

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 no output schema and simple parameters, the description lacks completeness. It does not specify return values, success signals, error conditions, or the implications of 'Account Boundary'. A more complete description would cover these aspects.

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?

Input schema already describes both parameters with high coverage (100%). The description adds no additional meaning beyond the schema, such as formatting expectations for 'site' or what 'Account Boundary' implies. Baseline 3 applies as no extra value is provided.

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?

Description clearly states the action 'Authorize a specific site or domain for an account', which is a specific verb+resource. However, it does not differentiate from sibling tools like 'sites_add' that might have similar functionality. The 'Account Boundary' parenthetical adds context but is not fully explained.

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 on when to use this tool versus alternatives such as 'sites_add' or 'sites_delete'. No explicit context or exclusions are provided, leaving the agent to infer usage from the brief description.

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 provided, so description must carry transparency burden. It states what the tool does but does not disclose any behavioral traits such as whether it requires prior authentication, indicates read-only nature, or describes the output format. For a simple list tool, this may be sufficient, but it could be more informative.

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 unnecessary words. It is front-loaded with the action and resource, making it easy to parse. Every word 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?

Given the tool's simplicity (no parameters, no output schema), the description is somewhat complete. However, it does not describe the output format (e.g., list of account names/IDs) or any prerequisites. For a minimal tool, this is acceptable but could be more thorough.

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 no parameters, and schema coverage is 100%. The description adds value by specifying the scope (Google and Bing accounts). With zero parameters, the baseline score is 4, and the description meets that by providing meaningful context.

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 authorized Google and Bing accounts. It uses a specific verb ('List') and specifies the resource ('authorized Google and Bing accounts'), distinguishing it from siblings like accounts_add_site and accounts_remove.

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. The description implies it's for listing accounts, but does not provide exclusion criteria or mention situations where other tools would be more appropriate. Given the simplicity of the tool, this is adequate but not helpful.

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 are absent, so description must disclose behavior. It only says 'Remove' without noting irreversibility, required permissions, or effects on related tools.

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?

Single sentence with no redundant words. Efficient and front-loaded.

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 destructive action with no output schema and no annotations, the description fails to explain outcome, safety, or retrieval of account IDs. Incomplete for safe use.

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 covers 100% of parameter details (accountId with description). Description adds no extra meaning, meeting 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?

Description 'Remove an authorized account' clearly states verb and resource. However, it does not differentiate from sibling tools like accounts_list or accounts_add_site.

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 on when to use or avoid this tool. No mention of prerequisites or alternatives like deactivating instead of removing.

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 bears full responsibility for behavioral disclosure. It states the tool identifies anomalies but does not clarify if it is read-only, how anomalies are calculated, whether it modifies data, or what to expect regarding rate limits or authentication. This is insufficient for an unannotated 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 a single, concise sentence that front-loads the purpose. While efficient, it could be slightly expanded to include usage guidance or behavioral details without becoming verbose. No redundancy, but the lack of structure beyond a single sentence reduces the score from 5 to 4.

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 absence of an output schema and annotations, the description should explain what the tool returns (e.g., list of anomalies, scores, dates). It only states it 'identifies' anomalies, leaving the agent without information on output format, pagination, or error handling. This is a significant gap for a tool with no structured return documentation.

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%—all three parameters have clear descriptions in the schema. The tool description ('Identify unusual daily spikes or drops in traffic') adds minimal context beyond the schema, so the baseline score 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 ('Identify') and clearly states the resource ('unusual daily spikes or drops in traffic'). It distinguishes this tool from siblings like analytics_trends or analytics_drop_attribution by focusing specifically on anomaly detection.

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 (e.g., analytics_trends for overall patterns, analytics_drop_attribution for drop attribution). The description only implies usage for identifying anomalies but provides no when-not-to-use or alternative suggestions.

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 the burden. It mentions a 'single batch' call but does not disclose any behavioral traits such as how data is returned, error behavior, rate limits, or whether it requires specific permissions. The description is too minimal to inform the agent about operational characteristics.

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 that directly states the tool's function and scope. There is no unnecessary text, and it is front-loaded with the key verb 'Get'. Every word 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?

Given the presence of 4 parameters and no output schema or annotations, the description is too brief. It does not explain the return format, how the dimensions are returned, any limitations on date ranges, or whether results are aggregated. This leaves the agent underinformed for safe 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?

The input schema has 100% coverage of parameter descriptions. The tool's description does not add meaning beyond the schema—it only abstracts the purpose. Baseline score of 3 is appropriate since the schema already documents each parameter's role.

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 purpose: to get audience segmentation data including New vs Returning, Age, and OS. It uses a specific verb 'Get' and resource 'audience segmentation', and the mention of multiple dimensions distinguishes it from sibling tools like analytics_trends or analytics_query.

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 prerequisites, when not to use it, or any specific use case context that would help an agent choose it over other analytics 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?

No annotations provided, and description does not disclose behavioral details such as data freshness, pagination, or auth requirements beyond what's in the schema.

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?

Single sentence is concise and front-loaded with purpose. However, it could include more context without becoming verbose.

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 annotations, no output schema, and a minimal description, the tool lacks sufficient context for an agent to understand all aspects of its use and behavior.

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 baseline is 3. Description adds no new meaning beyond the schema's parameter descriptions.

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?

Clear verb 'Get' with specific resource 'performance breakdown by country' and scope 'for the last N days'. Differentiates from sibling tools that focus on other dimensions.

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 on when to use this tool versus alternatives, nor any conditions for use.

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 of behavioral disclosure. The description only states it 'compares performance metrics' without detailing what metrics are included, whether the operation is read-only, or any side effects. This is insufficient for a tool with no annotation support.

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 at two sentences, front-loads the purpose, and contains no extraneous information. Every word adds value.

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?

Despite having 5 required parameters and no output schema, the description does not explain what performance metrics are compared or the format of the output. This leaves the agent uncertain about what to expect upon return, making it incomplete for full autonomous use.

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 each parameter having a clear description including date format (YYYY-MM-DD). The description adds little beyond the schema, only specifying that periods are compared. Baseline 3 is appropriate as the schema already documents parameters well.

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 compares performance metrics between two date periods, with a specific verb ('compare') and resource ('performance metrics between two date periods'). It distinguishes itself from sibling analytics tools by focusing on period-over-period comparison, which is unique among the many analytics tools listed.

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 explicit context for usage: 'Useful for week-over-week or month-over-month analysis.' This gives clear guidance on when to apply the tool, but does not include when-not-to-use or mention alternatives, though the sibling list contains many analytics tools that could be alternatives.

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 implies a read-only operation ('Analyze...in GA4') but does not explicitly state safety, auth requirements, or other behavioral traits. While typical for analytics tools, more clarity on side effects would improve transparency.

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 concise sentence (20 words) with no redundancy. It front-loads the action and prerequisite efficiently, though it could include more detail without being overly verbose.

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 should hint at what the analysis returns (e.g., metrics, dimensions). It only says 'analyze content performance', which is vague. The prerequisite is helpful, but lacking output context makes the tool incomplete for an agent.

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% description coverage, so the schema already documents each parameter's meaning. The description does not add any additional context or relationships beyond the schema, thus providing no extra value.

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 verb 'analyze' and the resource 'content performance by Content Group in GA4', making the purpose understandable. However, it does not differentiate from similar siblings like 'analytics_page_performance' or 'analytics_organic_landing_pages', which also analyze content.

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 a key prerequisite: 'Requires Content Groups to be configured in GA4 Admin', which tells when to use it. However, it does not mention when not to use it or suggest alternative tools among the many analytics siblings.

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 full burden. It does not disclose behavioral traits such as whether the tool is read-only, requires authentication, has rate limits, or returns funnel steps. 'Analyze' is ambiguous about what operations are performed.

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 concise (4 words), which is efficient but at the cost of clarity and completeness. It sacrifices important details that would help the agent understand the tool's purpose and usage.

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 complexity of conversion funnel analysis, the description is insufficient. It does not explain the output, how 'top converting' is defined, or what steps are involved. No output schema exists to compensate.

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% description coverage with clear parameter names (e.g., propertyId, startDate, endDate). The description adds no additional meaning beyond what the schema provides, so it meets the baseline of 3.

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 'Analyze top converting pages and events' specifies the resource (converting pages and events) and implies a focus on conversion, distinguishing it from generic analytics tools like analytics_top_pages. However, the verb 'analyze' is generic and could be more specific (e.g., 'list' or 'get funnel steps').

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 on when to use this tool vs. alternatives such as analytics_top_pages, analytics_trends, or other conversion-related tools. The description lacks context on prerequisites 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 must fully disclose behavioral traits. It mentions analysis of device/algorithm causes, but fails to explain whether the tool modifies data, requires specific permissions, or provides any output details. This is insufficient for an agent to understand non-functional aspects.

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 of about 20 words, front-loaded with the key action and scope. Every word earns its place, with 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 lack of output schema and annotations, the description is somewhat complete for a straightforward analysis tool. However, it omits details on return format, prerequisites (e.g., date range, data availability), and interpretation of results, leaving gaps for agent decision-making.

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 each parameter (days, siteUrl, threshold) having a clear description. The tool description does not add further meaning beyond summarizing the purpose. Baseline 3 is appropriate as 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 clearly states the tool's purpose: analyzing a significant traffic drop to identify device-specific causes or correlation with Google algorithm updates. It uses a specific verb ('analyze') and resource ('traffic drop'), effectively distinguishing it from sibling tools like analytics_trends or analytics_anomalies.

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 when to use (when there's a significant traffic drop and need to identify cause), but it does not explicitly state when not to use or provide alternatives. While context is clear, the lack of exclusions or comparison to other tools limits 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?

No annotations are provided, so the description must disclose behavioral traits. It does not mention permissions, data freshness, rate limits, or that the operation is read-only. It only says 'from GA4', which is already in the parameters.

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 front-loads the purpose ('Get ecommerce performance').

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, the description should explain what 'ecommerce performance' includes. Vague terms 'products, revenue' do not sufficiently describe the return structure for a tool with 6 parameters and no 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%, so the baseline is 3. The description adds 'products, revenue' as hints to what the tool returns, but does not add details about parameters beyond what the schema provides.

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 verb (Get), resource (ecommerce performance), and source (GA4). It is distinct from sibling tools, as no other tool focuses on ecommerce 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?

The description implies use for ecommerce performance but provides no explicit guidance on when to use this tool versus other analytics tools (e.g., analytics_performance_summary) 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?

With no annotations provided, the description must fully disclose behavioral traits. It only states that the tool retrieves data and that it matches GSC data, but it does not address important behaviors such as data range limits, required permissions, rate limits, or whether the operation is read-only. The description conveys a read operation, but lacks details that would help an agent anticipate side effects or constraints.

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, comprising a single sentence that is front-loaded with the verb and resource. It efficiently communicates the core purpose. However, given the brevity, some important details are omitted, but that is a matter of completeness rather than conciseness. The structure is clean and easy to parse.

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?

Despite having 6 parameters and 3 required fields, the description is very brief and does not explain the return format, what 'performance' means (e.g., metrics like clicks, impressions, etc.), or how the data matches GSC data. It also does not address the multi-account setup indicated by the 'accountId' parameter. The lack of output schema further increases the need for description completeness, which is not met.

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%, meaning each parameter already has a description in the input schema. The tool description adds the contextual note 'matches GSC data', which provides a hint about data consistency but does not elaborate on parameter usage or format beyond the schema. According to guidelines, baseline is 3 when coverage is high, and this description meets that baseline without adding much value.

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 verb 'Get' and the resource 'performance of organic landing pages in GA4'. It also provides the distinguishing feature 'matches GSC data', which helps differentiate it from siblings like 'analytics_top_pages' or 'bing_get_top_pages'. However, it does not specify which performance metrics are included, which is a minor gap.

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 explicit guidance on when to use this tool versus alternatives. The only hint is 'matches GSC data', which implicitly suggests it is for cross-referencing with Search Console, but it does not clearly state use cases, prerequisites, or when not to use it. For example, it does not contrast with other analytics tools that might serve similar purposes.

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 provided; description carries full burden. Only states it 'gets' metrics, implying read-only, but no disclosure of authentication needs, rate limits, data freshness, or pagination behavior. Lacks sufficient transparency for a tool with no 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?

Single sentence, no fluff. Front-loaded with purpose. Could be slightly more efficient by integrating parameter hints, but overall concise.

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?

No output schema provided, and description does not explain return format or how parameters like `pagePath` or `offset` affect results. For a detailed metrics tool with 8 parameters, more context is needed.

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 all parameters described. Description does not add extra meaning beyond what schema already provides, meeting the baseline expectation.

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?

Description clearly states 'Get detailed page performance metrics from GA4' with specific metrics (sessions, views, engagement). It differentiates from siblings like `analytics_top_pages` by emphasizing detail, but does not explicitly name 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?

Implied usage for retrieving detailed page metrics, but no explicit guidance on when to use this vs alternatives (e.g., `analytics_top_pages`, `analytics_performance_summary`). No when-not-to-use conditions.

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 full burden. It only states the action 'correlate' without explaining what that entails (e.g., statistical method, data merging, or result format). No disclosure of side effects or prerequisites.

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?

Single sentence with no unnecessary words, front-loaded with action and resources. Every word is valuable.

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 no output schema and the complexity of correlating two data sources, the description is too brief. It fails to explain what the output looks like, what 'correlate' means operationally, or any limitations.

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 schema already documents all parameters. The description adds no additional meaning beyond what is in the schema, meeting 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?

Description uses specific verb 'correlate' and explicitly combines two distinct resources (GA4 engagement metrics and PageSpeed Insights scores), making it clearly distinguishable from siblings like 'pagespeed_analyze' or 'analytics_top_pages'.

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 (e.g., using separate analytics and pagespeed tools). Usage is implied but not clarified.

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 provided; description mentions metrics but does not disclose if it is read-only, rate limits, or response structure. Missing details on how data is aggregated or any limitations.

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?

Single sentence, 15 words, front-loaded with action and resource. Every word adds value, no 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?

Adequate for a simple tool with few parameters, but lacks mention of default days (28) and does not specify output format (no output schema). Could improve by clarifying aggregation scope.

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 covers all three parameters with descriptions (100% coverage). Description adds no extra meaning beyond what is in the schema, so 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?

Clearly states it retrieves aggregate performance metrics (clicks, impressions, CTR, position) for the last N days, distinguishing itself from siblings like analytics_trends or analytics_query that focus on other aspects.

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?

Implied usage for aggregate summary but no explicit guidance on when to use vs. alternatives like analytics_trends or analytics_top_queries. Does not mention when not to use or 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?

No annotations are provided, so the description bears full burden for behavioral disclosure. It only mentions pagination but does not disclose whether this is a read-only operation, any destructive aspects, authentication needs, or rate limits.

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 efficient sentence with no wasted words. Front-loaded with the verb and relevant scope.

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 11 parameters, complex nested filters, and no output schema, the description is severely under-specified. It does not explain return values, filter syntax, or how different parameter combinations affect results.

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 baseline is 3. The description adds minimal value beyond the schema, only hinting at pagination (startRow and limit) which are already documented in 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 'Query search analytics data with optional pagination' clearly states a specific verb-resource pair (query analytics data) and mentions pagination. However, it does not distinguish from numerous sibling analytics tools that also query analytics data, such as analytics_top_queries or analytics_by_country.

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 generic query tool versus more specific siblings. With over 20 analytics-related sibling tools, explicit usage context is needed but absent.

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 are absent, so description must cover behavioral traits. It indicates a read operation ('get') but does not mention permissions, rate limits, or data freshness. The description is adequate for a simple query 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?

Single sentence efficiently conveys purpose. It is front-loaded with the main action and scope, though it could benefit from a second sentence on output format.

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?

No output schema exists, so the description should clarify return value structure. It mentions breakdowns but not whether results are paginated or aggregated. Adequate for a simple tool but leaves 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?

Schema coverage is 100% with descriptions for both parameters. The description does not add meaning beyond the schema; it mentions dimensions (page, country, device) but these are not parameters, so no enhancement.

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 verb 'get', resource 'realtime active users', and scope 'broken down by page, country, and device'. It distinguishes the tool from siblings focused on Bing or other analytics functions.

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. It implies use for realtime data, but lacks comparison to related analytics tools like analytics_trends or analytics_top_pages.

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 provided; description carries full burden. It discloses it is a read operation ('Get') but does not mention side effects, data freshness, rate limits, or authentication needs. The minimal description leaves behavioral traits unclear.

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, concise sentence that conveys the essential purpose and time range. No unnecessary words, and the structure is front-loaded with the action and resource.

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 no output schema and 4 parameters, the description is adequate but lacks detail on what 'search appearance type' means or what the output structure looks like. The agent may need to infer response fields. More details on appearance types and output would improve completeness.

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 description adds no additional meaning beyond the schema. Each parameter (days, limit, sortBy, siteUrl) is already described in the schema. The description does not provide extra context or constraints.

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 a performance breakdown by search appearance type for a specified period, using specific verb 'Get' and resource 'performance breakdown by search appearance type'. It distinguishes from sibling tools like analytics_top_queries or analytics_top_pages which focus on different dimensions.

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. While the description implies usage for appearance-type breakdowns, it lacks context on when to prefer it over other analytics tools or any exclusions. The agent must infer from the tool 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the type of data returned (rolling averages, seasonality, forecast) but omits important details like authentication requirements, rate limits, or data constraints. The description is insufficient for a tool with multiple parameters and no annotation support.

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 concise sentences, each adding value. The first explains the core outputs, the second lists supported analysis features. No wasted words.

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's complexity (10 parameters, no output schema, no annotations, many siblings), the description provides a high-level overview but lacks details on how parameters interact (e.g., days vs. startDate/endDate, window size relationship). It also does not explain the return format. However, the schema descriptions fill some gaps, making the description adequate but not 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?

All 10 parameters have descriptions in the schema (100% coverage), so the baseline is 3. The description mentions 'multi-dimensional analysis, metrics selection, and custom granularities,' which maps to parameters but adds no new 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 clearly states 'Get advanced time series data including rolling averages, seasonality strength, and trend forecasting,' which specifies the exact capabilities and distinguishes it from simpler siblings like analytics_trends or analytics_anomalies.

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 advanced time series analysis but does not explicitly state when to use this tool versus other analytics tools like analytics_trends or bing_analytics_time_series. No exclusions or alternatives are mentioned.

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 only mentions that the tool returns top pages by clicks or impressions for N days. It does not disclose any behavioral traits such as whether it returns a sorted list, if there is pagination, or any side effects. Since annotations are absent, the description carries the full burden but is 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 a single sentence, which is concise. However, it omits important details that could improve usability. It front-loads the core purpose but could be more complete without significantly increasing length.

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 moderate complexity (4 parameters, 1 enum) and absence of output schema and annotations, the description is insufficient. It does not mention default values, sorting order, or the structure of the returned data, making it incomplete for an AI agent to reliably use.

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% description coverage, so each parameter is already documented. The description adds contextual meaning ('top performing pages') but does not provide additional details beyond what the schema offers. Thus, a baseline score 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 that the tool retrieves top pages based on clicks or impressions over a specified time period. It distinguishes itself from sibling tools like 'analytics_top_queries' (which focuses on queries) and 'analytics_trends' (which shows trends), though it does not explicitly differentiate from other page-analysis tools.

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. Given the extensive list of sibling tools (e.g., 'analytics_page_performance', 'analytics_organic_landing_pages'), the description lacks context on appropriate use cases or when to prefer this tool over others.

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 full burden. It only states it 'gets' data, implying a read operation, but does not disclose behaviors like data freshness, limits, or error handling. The description is minimal in behavioral context.

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, front-loaded with the key action and parameters. No wasted words.

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 4 parameters and no output schema, so the description is adequate but could mention the return format or data source. It does not leverage the output schema context (none exists) to explain return values.

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 schema already documents all parameters. The description adds little extra meaning beyond reiterating the sortBy and days options. 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 verb 'Get' and the resource 'top search queries', and specifies the scoping by clicks or impressions over a period. However, it does not differentiate from sibling tools like analytics_query or analytics_top_pages, which could cause confusion.

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. Given the many analytics sibling tools, explicit usage context is missing.

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 must disclose behavioral traits like read-only or pagination, but it only states 'Analyze traffic sources'. It adds no information about safety, side effects, or performance, leaving the agent underinformed.

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, focused sentence that communicates the core purpose without waste. It is front-loaded and efficient, though slightly too brief for completeness.

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 7 parameters, no output schema, and no annotations, the description is inadequate. It does not explain return values, pagination behavior (though offset/limit exist in schema), or how it relates to sibling analytics tools.

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?

All 7 parameters have schema descriptions (100% coverage), so the description adds no extra meaning beyond the schema. The baseline of 3 is appropriate because the schema itself is sufficient.

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 analyzes traffic sources and specifies three dimensions (Channel, Source, Medium) in GA4, which distinguishes it from sibling tools that focus on queries, pages, etc., but it could be more specific about the metrics returned.

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 siblings like analytics_query or analytics_top_pages. The description lacks context for choosing this over alternatives.

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 only states the purpose without disclosing how trends are computed, what thresholds are applied, or what the output contains (e.g., trend direction, magnitude, statistical significance). This is insufficient for a 6-parameter 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?

A single, concise sentence that front-loads the core purpose without unnecessary words. It is appropriately sized for a straightforward 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?

With 6 parameters, no output schema, and no annotations, the description is too sparse. It does not explain the output format (e.g., list of trends with direction and metrics) or how parameters like threshold and minClicks influence results, leaving significant gaps for an agent.

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?

Since schema description coverage is 100%, the baseline is 3. The description adds minimal value beyond the schema—it mentions 'queries or pages' which aligns with the dimension parameter, but that is already described in the schema. No extra semantics are provided.

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 detects traffic trends (rising/declining) for queries or pages, which distinguishes it from sibling tools like analytics_top_queries and analytics_top_pages that focus on top items rather than trends.

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 such as analytics_anomalies, analytics_time_series, or other trend-related tools. An agent would have to infer usage from the tool name and siblings.

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 provided, so description must disclose behavioral traits. It only says 'Get', implying read-only, but lacks details on data aggregation, real-time nature, permissions, or any limitations. For a tool with zero annotation coverage, this is insufficient.

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?

Single sentence that is front-loaded with verb and resource, zero waste. Every word serves a purpose.

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?

No output schema exists, so description should hint at return structure or data shape. It does not. It also fails to clarify 'Engagement' or the role of accountId. For a tool with 4 parameters and no output schema, completeness is poor.

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?

Input schema covers all 4 parameters with descriptions (100% coverage), so the description does not need to add much. It adds no extra semantic meaning beyond what the schema provides, so 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?

Clearly states action 'Get' and specific resource 'user behavior breakdown' with three explicit dimensions (Device, Country, Engagement), and adds 'in a single batch' to indicate consolidated return, distinguishing it from tools like analytics_by_country.

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 analytics_by_country or analytics_trends. The description implies a batch approach but does not provide when/why this is preferred.

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 provided. The description does not disclose whether the tool is read-only, required permissions, or what 'performance' metrics are returned. Description carries full burden but fails.

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?

Single sentence, no fluff, front-loaded. However, it could be slightly more informative without increasing length significantly.

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?

No output schema and no description of return value. With many sibling tools, more context needed to differentiate. Incomplete for practical use.

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 baseline is 3. Description adds minimal context by implying the date ranges are the periods to compare, but no additional meaning beyond 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 states the tool compares performance between two date ranges in Bing, which is specific and distinguishes from trend or query tools.

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 on when to use this tool over alternatives like bing_analytics_trends or bing_analytics_detect_anomalies. The many sibling tools increase the need for contextual usage hints.

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 must fully disclose behavioral traits. It fails to mention whether the tool is read-only, what the output format is, authentication requirements, or rate limits. The only behavioral clue is the verb 'Detect', which implies analysis but lacks transparency.

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, clear sentence with no fluff. It is appropriately front-loaded with the verb. However, it could benefit from additional context without being verbose.

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 no annotations or output schema, the description should provide more context on what constitutes an anomaly, how the detection works, and what the tool returns. The current description is too sparse for an AI agent to invoke correctly without guesswork.

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 baseline is 3. The description does not add meaning beyond the schema, such as explaining how 'threshold' affects anomaly detection or what 'days' range is valid. It is adequate but not improved.

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 verb 'Detect' and the resource 'performance anomalies in Bing traffic', making the purpose specific. However, it does not distinguish from the sibling tool 'analytics_anomalies', which may have overlapping functionality.

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 sibling list includes many analytics tools, but the description lacks context or exclusion criteria, leaving the agent uncertain about selection.

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 full burden for behavioral disclosure. It only states a vague outcome ('identify the likely cause') without explaining how the tool operates, whether it is read-only, what side effects exist, or what the output format is. This is insufficient for safe invocation.

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 concise sentence with no wasted words. It efficiently communicates the core purpose, though it sacrifices depth for brevity. Given the tool's simplicity, this is appropriate but leaves other dimensions under-served.

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?

Despite having 3 parameters (1 required) and no annotations or output schema, the description provides minimal context. It does not explain return values, how the cause is determined, or any behavioral traits. For a tool with many siblings, completeness is lacking.

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?

Input schema coverage is 100% and all parameters have descriptions in the schema. The tool description adds no additional parameter context. According to guidelines, baseline is 3 when coverage is high, so no improvement is needed.

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?

Description states the verb 'Identify' and resource 'the likely cause of a Bing traffic drop', making the purpose clear. However, it does not differentiate from similar sibling tools like 'bing_analytics_detect_anomalies' or the generic 'analytics_drop_attribution'.

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 on when to use this tool versus alternatives. There is no mention of prerequisites, scenarios, or exclusions. Given many sibling tools with overlapping functionality, this is a significant gap.

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 must fully disclose behavioral traits such as authentication needs, error handling, or data limits. It only states 'Get page performance stats', omitting any behavioral details.

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 at one sentence, but it lacks sufficient detail to be fully informative. It is not overly verbose, but the brevity sacrifices clarity about what the tool returns.

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 output schema, no annotations, and only three parameters. The description fails to explain what 'page performance stats' includes, how the date range works, or what the response looks like, leaving the agent underinformed.

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 each parameter described (siteUrl, startDate, endDate). The description adds no additional meaning beyond the schema descriptions, so baseline score 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 verb 'Get' and resource 'page performance stats from Bing Webmaster Tools', with 'Top Pages' indicating scope. However, it does not distinguish from siblings like bing_get_top_pages or bing_analytics_page_query, which could be overlapping.

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, nor any conditions or prerequisites. The description is purely declarative without usage context.

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 provided, but description indicates a read-only retrieval operation ('Get'). Lacks details on authentication, rate limits, or data freshness.

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?

Single sentence with 10 words, no redundancy, directly states the tool's purpose.

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 and no annotations, the description lacks information about return value format and behavioral specifics, which is incomplete for a tool with 4 parameters and many siblings.

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 description adds no extra meaning beyond the 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?

Description uses specific verb 'Get' and resource 'query performance stats for a specific page', clearly distinguishing from sibling tools like bing_analytics_query or bing_analytics_page.

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 on when to use this tool vs alternatives; does not mention conditions, prerequisites, 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 provided, so description carries full burden. It correctly implies a read operation ('Get'), but fails to disclose additional behaviors such as authorization needs, rate limiting, or whether it only returns the 'top' queries. Adequate for a basic query tool but lacks depth.

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?

Extremely concise, one sentence. However, it could be structured with more details (e.g., output format, date range behavior). Still efficient, but not optimal for clarity.

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 5 parameters (1 required) and no output schema, the description is too minimal. It doesn't explain what the returned stats contain, how to interpret them, or any constraints (e.g., default limit of 1000 rows). Leaves agents guessing about the data structure.

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?

Input schema has 100% coverage with descriptions for all 5 parameters. The description adds no additional semantic meaning beyond the schema. Baseline of 3 is appropriate as 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?

Description clearly states the tool retrieves query performance stats from Bing Webmaster Tools, specifically 'Top Queries'. It uses a specific verb and resource, and while it doesn't explicitly differentiate from siblings like bing_analytics_page_query or bing_get_top_queries, the focus on 'Top Queries' provides some distinction.

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 on when to use this tool versus the many sibling tools (e.g., bing_analytics_query_page, bing_analytics_trends). Lacks context on prerequisites, like needing a siteUrl or date range boundaries.

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 must convey behavioral traits. It only states the basic function, omitting details like whether it is read-only, pagination behavior, data freshness, or rate limits.

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, front-loaded sentence with no wasted words. However, it could be more informative within the same length.

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 no output schema and many similar siblings, the description lacks essential context such as what 'combined' means, what fields are returned, and how it differs from siblings like bing_analytics_page_query.

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% (all three parameters have descriptions). The tool description does not add any extra meaning beyond the schema, so 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 action (Get) and resource (combined query and page performance stats for a site). However, it does not distinguish this tool from similar sibling tools like bing_analytics_page_query, which also implies a combination of query and page 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?

The description provides no guidance on when to use this tool versus alternatives. No context about prerequisites, exclusions, or typical use cases 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?

With no annotations, the description should disclose behavioral traits like read-only nature or required permissions. It merely states 'advanced time series analysis,' implying it retrieves data, but this is speculative and insufficient 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 a single sentence, which is concise, but the word 'advanced' is subjective and adds little value. It could be restructured to be more informative while remaining brief.

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 4 parameters, no output schema, and many sibling tools, the description is too scant. It fails to explain return values, level of detail, or how it differs from related tools like analytics_time_series.

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 baseline is 3. The description adds no additional meaning beyond what the schema provides for parameters like 'siteUrl,' 'days,' or 'metrics.' No further parameter details are offered.

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 'Advanced time series analysis for Bing performance data' clearly indicates the tool is for time series analysis, distinguishing it from other analytics tools. However, it lacks specificity on the exact resource being analyzed (e.g., clicks, impressions) and could be more precise.

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 siblings such as bing_analytics_trends or analytics_time_series. The description does not include any context about use cases or alternatives.

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 full responsibility for behavioral disclosure. It only states the purpose without revealing details like output format, whether the tool returns a list of queries, thresholds for trend detection, or any side effects. This is insufficient for a tool that analyzes performance metrics.

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, clear sentence that immediately conveys the core function. It is concise and front-loaded with the purpose. However, it could be slightly expanded with additional context without losing conciseness.

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 lack of output schema and the tool's analytical nature (detecting trends), the description is too brief. It does not explain what the output looks like (e.g., ranked lists, percentage changes), how the trend detection works, or what parameters like 'days' and 'threshold' influence. More context is needed for effective use.

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% description coverage for all four parameters, so the schema already documents each parameter's meaning. The description adds no further context beyond the schema. Baseline score of 3 is appropriate as the description does not need to compensate for missing parameter documentation.

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: detecting rising or declining trends in Bing query performance. It uses a specific verb ('detect') and specifies the resource ('Bing query performance'). However, it does not explicitly distinguish from sibling tools like 'bing_analytics_detect_anomalies' or 'bing_analytics_time_series', but the focus on 'trends' provides some differentiation.

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. Sibling tools such as 'bing_analytics_detect_anomalies' or 'bing_analytics_compare_periods' exist, but no conditions, exclusions, or prerequisites are mentioned.

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, and the description does not disclose behavioral traits like data requirements, rate limits, or side effects. It merely states the purpose without additional context.

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, front-loaded sentence with no unnecessary words, efficiently conveying the tool's purpose.

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 output schema, yet the description does not explain what the analysis returns (e.g., data format, metrics). Combined with missing usage guidelines, the description is incomplete for effective agent 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 coverage is 100% (all three parameters described). The description does not add any extra meaning beyond the schema. Baseline score of 3 is appropriate since the schema already defines the parameters.

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 verb 'Analyze' and the resource 'Brand vs Non-Brand performance on Bing', distinguishing it from similar tools like 'brand_analysis' by specifying the search engine. However, it does not explicitly differentiate from all siblings.

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, such as the sibling 'brand_analysis' tool. No prerequisites or exclusions are mentioned.

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 full responsibility for revealing behavioral traits. The description only says 'Get crawl issues' without mentioning whether the operation is read-only, if it requires specific permissions, or if there are rate limits. It does not disclose the return format, pagination, or any side effects, leaving significant behavioral gaps.

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 concise (9 words, one sentence), but it sacrifices necessary detail for brevity. While it is front-loaded and efficient, it is too sparse to be fully informative. A slightly longer description with more context would be appropriate.

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's moderate complexity (crawl issues could involve multiple types, dates, and filtering) and the lack of an output schema, the description is insufficient. It does not explain what constitutes a 'crawl issue,' whether there are any prerequisites (e.g., site verified), or how results are structured. The description feels incomplete for making an informed 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?

The input schema has only one parameter ('siteUrl') with a clear description, achieving 100% schema coverage. The description adds no additional meaning beyond the schema, so it meets the baseline of 3. It does not enhance understanding of the parameter's format or constraints.

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 gets crawl issues for a site from Bing Webmaster Tools. It uses a specific verb ('get') and resource ('crawl issues'), effectively distinguishing it from sibling tools like 'bing_crawl_stats' (which likely provides aggregate statistics) and 'diagnostics' (a broader tool). However, it does not specify the type of crawl issues (e.g., errors, warnings), which slightly reduces clarity.

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. Given the large number of sibling tools (e.g., 'bing_crawl_stats', 'diagnostics', 'seo_recommendations'), the absence of usage context or when-not-to-use instructions makes it harder for an AI agent to select the correct 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 provided, the description must carry the full burden. It states the tool is a read operation, which is clear, but omits details like required permissions, output format, or potential rate limits. This is acceptable for a straightforward tool but could be improved.

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, well-structured sentence that front-loads the action and resource, providing all necessary information without any wasted words.

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?

Although no output schema exists, the description succinctly states the returned data types (indexed, crawled, errors). This is sufficient for an agent to understand the tool's output, making it complete for its purpose.

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 siteUrl described as 'The URL of the site'. The description does not add further meaning, so it meets the baseline for parameter semantics.

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 'Get' and clearly identifies the resource 'crawl statistics' with explicit types (indexed, crawled, errors). It effectively distinguishes from sibling tools like bing_crawl_issues which focus on specific problems.

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 on when to use this tool versus alternatives such as bing_crawl_issues or bing_url_info. The description is adequate for a simple retrieval but lacks explicit when-not or alternative references.

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, and the description only states the action (get top pages). It does not disclose behavioral traits such as whether it's read-only, rate limits, authentication requirements, or behavior on invalid siteUrl.

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 concise (two sentences) and front-loaded. However, it could include more useful information without sacrificing conciseness.

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 should explain the return format or data provided. It only says 'Get top pages' without specifying what information is included (e.g., page URLs, metrics). This leaves the agent under-informed.

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 already fully describes the sole parameter (siteUrl) with 100% coverage. The description adds no additional meaning beyond the schema's description, so it meets baseline without improvement.

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 it retrieves top pages for a site, with a direct verb ('Get') and resource ('top pages for a site'). It also notes it's an alias for bing_analytics_page, providing some context. However, it doesn't explicitly differentiate from other siblings like bing_get_top_queries.

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 on when to use this tool versus alternatives. The alias statement hints at redundancy but offers no usage recommendations or 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?

No annotations provided, and the description does not disclose any behavioral traits like authentication needs, rate limits, or performance implications. It only notes it's an alias, but without elaboration.

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 short (one sentence plus alias reference), which is concise. However, it lacks important details that would justify its brevity, making it merely adequate.

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 and many sibling tools, the description should explain return values or scope. It does not. The tool is an alias, but its purpose relative to other tools is unclear.

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 each parameter having a clear description in the schema. The tool description adds no additional parameter meaning, so baseline score 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?

Description states it's an alias for bing_analytics_query and gets top queries, which indicates verb and resource. However, it fails to differentiate from its alias target or similar sibling tools like analytics_top_queries, making the specific purpose vague.

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 on when to use this tool versus alternatives such as bing_analytics_query or analytics_top_queries. The description does not mention any context or exclusions for 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?

With no annotations, description fails to disclose behavioral traits like rate limits, idempotency, required permissions, or side effects. Only states the action without any safety or constraint context.

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?

Extremely concise single sentence; front-loaded with purpose. However, it omits necessary detail, slightly reducing effectiveness.

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 4 parameters, no output schema, and no annotations, this description is critically incomplete. Lacks info on return values, failure modes, prerequisites, and integration context.

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 descriptions for all parameters, so description adds no further value. 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?

Description clearly states verb 'Submit' and resource 'URLs via IndexNow API', and names specific services (Bing, Yandex). Differentiates from siblings like bing_url_submit by referencing the IndexNow protocol.

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 on when to use this tool vs related siblings like bing_url_submit or indexing_submit_url. Usage context is only implied by the name and description.

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 provided, so description must disclose behavior. Only states 'Get historical stats' without explaining what data is returned, time range, or any restrictions. Lacks detail on mutation or safety.

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?

Single sentence, no extraneous words. Efficiently conveys core 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?

No output schema; description fails to mention what historical statistics are returned (e.g., impressions, clicks, CPC). Lacks context on time range or data granularity. Incomplete for a stats 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?

Schema coverage is 100% with descriptions for all three parameters. Tool description adds no extra meaning beyond schema. Baseline score 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?

Description clearly states verb 'Get', resource 'historical stats for a keyword', and platform 'Bing'. It distinguishes from siblings like bing_related_keywords that focus on related keywords rather than stats.

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 on when to use this tool vs alternatives like bing_related_keywords or bing_seo_cannibalization. No mention of prerequisites or situations to avoid.

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 only states the basic purpose without disclosing behavioral traits such as whether it is read-only, rate limits, or what exactly the 'inbound link counts' represent (e.g., total count or per page).

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, front-loaded sentence that efficiently conveys the core purpose. However, it could benefit from a bit more detail to improve completeness without becoming verbose.

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 no output schema and no annotations, the description is minimally complete. It tells what the tool does but does not describe the return value or any caveats. For a simple tool, this may suffice, but more context would be helpful.

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% for the single parameter, so the description does not need to add much. The description does not provide any additional semantic detail beyond the schema's description of 'The URL of the site'.

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 ('Get'), the resource ('inbound link counts'), and the source ('from Bing'). It is specific and distinguishes from sibling tools which cover different aspects of Bing SEO.

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 sibling list includes many other analytics and SEO tools, but the description does not mention any context for usage 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 provided, so the description carries full burden. It implies a read-only analytical operation but does not disclose any behavioral traits such as data mutability, authentication requirements, rate limits, or specifics of how 'lower than expected CTR' is determined.

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 concise sentence that is front-loaded with the key action and resource. Every word is informative, no 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 tool has no output schema, and the description does not hint at the return format or how to interpret results. Given the simplicity of the tool (2 params, analysis only), it is minimally complete but could benefit from specifying output type or usage examples.

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 baseline is 3. The description does not add any extra meaning beyond the schema's param descriptions. It does not explain the significance of siteUrl or minImpressions 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 identifies high-ranking Bing queries with lower than expected CTR, specifying the search engine and the condition. It distinguishes from siblings like bing_seo_cannibalization and seo_low_ctr_opportunities.

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 on when to use this tool versus alternatives. The description only states what it does, without mentioning when-not-to-use or contrasting with similar tools like seo_low_ctr_opportunities or bing_seo_lost_queries.

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 full burden for behavioral disclosure. It only states the purpose and does not mention whether the tool is read-only, requires authentication, has rate limits, or any other behavioral traits.

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 short sentence with no wasted words. It is front-loaded and easy to parse. However, it could be slightly more informative while remaining concise.

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 lack of output schema and annotations, the description should provide more context about what the output looks like and how to use the parameters effectively. It is incomplete for an agent to fully understand the 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 input schema has 100% description coverage, so the baseline is 3. The description adds no further context about parameters, but the schema already documents them adequately.

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?

Description clearly states the tool finds high-potential 'low-hanging fruit' keywords in Bing, using a specific verb and resource. However, it does not distinguish from the sibling tool 'seo_low_hanging_fruit' which may have similar functionality.

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 usage guidelines are provided. The description does not indicate when to use this tool versus alternatives, nor does it mention prerequisites 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?

No annotations provided, and the description does not disclose behavioral traits such as read-only nature, authentication requirements, rate limits, or error handling. It only states 'Get', implying idempotency, but lacks detail.

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?

Extremely concise, one sentence with no redundant words. Perfectly front-loaded.

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 tool with one parameter and no output schema, the description is minimally sufficient. However, given the large set of sibling tools, more context about the type of data returned would improve completeness.

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% for the single parameter siteUrl. The description adds no additional meaning beyond the schema, which is acceptable given full 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?

Description clearly states the tool gets historical rank and traffic statistics. It uses a specific verb and resource, but does not distinguish it from siblings like bing_keywords_stats or bing_analytics_trends, which also provide site statistics.

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 on when to use this tool versus alternatives. For instance, it doesn't clarify whether it returns historical data for a specific period or how it differs from other analytics 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?

No annotations exist, so the description must fully convey behavior. It only states the action without disclosing whether it's read-only, rate limits, required permissions, or data returned (e.g., does search volume include trends?). This is a significant gap for a data-gathering 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 a single, efficient sentence with no waste. However, it could be slightly more informative without losing conciseness (e.g., mentioning that results include volumes).

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, no annotations, and minimal description, the agent lacks context on return value structure, pagination, or limitations. The tool's purpose is clear, but operational completeness is poor.

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 schema adequately documents each parameter. The description adds no additional parameter meaning beyond the schema's field descriptions, justifying the baseline score of 3.

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 action ('Get'), resource ('related keywords and search volume'), and source ('from Bing'). It is specific and distinct from sibling tools, many of which are also Bing-related but don't duplicate this exact functionality.

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 on when to use this tool versus alternatives like bing_keywords_stats or bing_get_top_queries is provided. The description does not mention prerequisites, context, 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?

No annotations are provided, so the description should disclose behavioral traits like read-only nature, rate limits, or output format. It only states the basic purpose, omitting any operational details such as whether the tool modifies data or what the result looks like.

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 of 7 words, front-loading the core purpose with no redundancy or filler. It earns its place with maximum 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?

Without an output schema, the description should indicate what the tool returns (e.g., list of pages, scores) and how to interpret results. It does not, leaving an agent underinformed for a detection task.

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 clear descriptions for both parameters ('siteUrl' and 'minImpressions'). The description adds no additional meaning beyond the schema, so 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 verb 'detect' and the resource 'pages competing for the same query' with the scope 'Bing'. This is specific and effectively distinguishes it from siblings like 'seo_cannibalization' which likely targets other search engines.

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 on when to use this tool versus alternatives such as 'bing_seo_lost_queries' or 'bing_get_top_pages'. The description lacks context on prerequisites 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?

No annotations are provided, so the description must fully disclose behavior. It only states the high-level purpose without explaining how 'significant traffic loss' is determined, whether the operation is read-only, or any side effects.

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 concise at one sentence, but it is not overly detailed. It could benefit from a bit more context without being verbose.

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 lacks information on return format, result count, or how results are presented. This is insufficient for a query analysis 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?

Schema coverage is 100%, with both parameters having descriptions. The tool description adds no additional meaning beyond the schema, so the baseline score 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 verb 'Identify' and the resource 'queries that lost significant traffic on Bing compared to the previous period.' It is specific enough to differentiate from sibling tools like bing_seo_cannibalization, though 'significant' is somewhat vague.

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 the many sibling tools (e.g., bing_get_top_queries, bing_analytics_compare_periods). There are no when-not-to-use or alternative recommendations.

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 exist, so the description must disclose behavior. It only states it generates recommendations but does not mention authentication, rate limits, or what the output contains. This leaves the agent uncertain about side effects or required permissions.

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, which is concise. However, it is too brief and lacks structural elements like bullet points or separation of concerns. It earns its place but 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?

Given no output schema, the description should explain what 'prioritized SEO recommendations' entails (e.g., types of recommendations, format). It fails to provide enough detail for an agent to understand what the tool returns.

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% for the single parameter 'siteUrl', which is described as 'The URL of the site'. The description adds no additional meaning beyond the schema, so 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 verb 'Generate' and the resource 'prioritized SEO recommendations for a Bing site'. It distinguishes from sibling tools like 'bing_seo_cannibalization' which target specific issues. Thus, purpose is clear and specific.

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 no guidance on when to use this tool versus alternatives. It does not mention when not to use it or provide context for selection among many SEO-related siblings.

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 provides no behavioral details beyond the action itself. For a delete operation, there is no mention of permanence, authentication needs, or side effects. No annotations are present to compensate.

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 concise (one sentence), which is efficient, but it lacks structure and additional detail that would improve usability. It is not overly verbose, but it could be more informative without sacrificing brevity.

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 lack of output schema and annotations, the description should compensate with more context about the operation's effects, return values, or prerequisites. It does not, leaving the agent with insufficient information to understand the full impact of the 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 input schema has 100% description coverage for both parameters. The description does not add any extra meaning beyond what the schema already provides, so baseline score 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 action ('Remove a sitemap') and the context ('from Bing Webmaster Tools'). It effectively distinguishes this tool from sibling tools like list or submit, though it could be more 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?

No guidance on when to use this tool versus alternatives (e.g., sitemaps_list or sitemaps_submit). There is no mention of prerequisites, context, 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?

With no annotations, the description bears full responsibility for behavioral disclosure, but it only states the read operation. It omits details on pagination, error handling, rate limits, or return format.

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 at nine words, with no fluff. However, it could be slightly expanded to include sibling differentiation or usage hints without becoming verbose.

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's simplicity (one parameter, no output schema, no annotations), the description is still incomplete. It does not explain the expected return list format, whether pagination occurs, or what constitutes a valid site URL.

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%; the single parameter 'siteUrl' is adequately described in the schema. The description adds no extra meaning beyond the schema, so a baseline score 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 action (list) and resource (sitemaps for a Bing site), but fails to differentiate from the sibling tool 'sitemaps_list' which likely serves a similar purpose for a different search engine.

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 alternative sitemap tools like 'bing_sitemaps_submit', 'bing_sitemaps_delete', or 'sitemaps_list'. The description does not mention prerequisites or constraints.

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 exist, and the description does not disclose behavioral traits such as authentication requirements, rate limits, or side effects like overwriting existing sitemaps.

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—one sentence that communicates the core action. However, it could benefit from additional structure (e.g., bullet points for context).

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 no annotations or output schema and many sibling tools, the description is too minimal. It lacks information about return values, success/failure indicators, or typical use cases.

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 basic parameter descriptions. The tool description adds no additional meaning beyond what the schema already provides.

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: 'Submit a sitemap to Bing Webmaster Tools'. It distinguishes from siblings by specifying Bing, but lacks differentiation from 'sitemaps_submit'.

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 on when to use this tool versus alternatives like 'sitemaps_submit' or 'bing_url_submit'. No prerequisites or context provided.

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 exist, so the description must fully disclose behavioral traits. It only states 'add' without detailing side effects, authorization needs, or what happens if the site already exists.

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, front-loaded sentence with no wasted words. However, it is slightly too minimal, missing opportunities to add useful context without significant bloat.

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 only one parameter and no output schema or annotations, the description fails to mention return values, error scenarios, or any prerequisites, leaving the agent underinformed.

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 a clear description for the only parameter 'siteUrl'. The tool description adds no additional 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 clearly states the action 'Add' and the resource 'new site', targeting 'Bing Webmaster Tools'. This distinguishes it from sibling tools like bing_sites_list or bing_sites_delete.

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 vs alternatives, such as prerequisites (e.g., needing a verified site) or conditions where adding might fail (e.g., duplicate site).

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 the action 'remove' without detailing side effects, permissions, or reversibility.

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, clear sentence that is front-loaded and contains no unnecessary words.

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 delete operation with one parameter, the description is adequately complete, though it lacks detail on response or confirmation.

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 already describes the parameter 'siteUrl'; the description adds no additional meaning beyond what the schema provides, meeting the baseline for 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?

The description 'Remove a site from Bing Webmaster Tools' clearly states the specific action (remove) and resource (site), distinguishing it from sibling tools like sites_add or sites_list.

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, nor does it mention prerequisites 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?

Without annotations, the description alone must disclose behavioral traits. It calls the action a 'comprehensive health check' but does not specify whether it is read-only, what checks are performed, or the nature of the output. This vagueness leaves critical behavioral context unknown.

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, concise sentence with no extraneous information. Every word serves a purpose.

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 simplicity (one optional param, no output schema), the description covers the basic purpose but fails to describe the return value (e.g., a health report or score). This gap reduces completeness for an AI agent invoking the 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 description adds value beyond the schema by clarifying that omitting the optional 'siteUrl' parameter checks all verified sites. This complements the schema's parameter description (100% coverage) with usage semantics.

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 identifies the tool's action ('run a comprehensive health check'), the resource ('verified Bing sites'), and scope ('one or all'). This distinguishes it from sibling tools like 'sites_health_check' and 'traffic_health_check' by specifying Bing-specific sites.

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 does not provide any guidance on when to use this tool versus alternatives (e.g., 'sites_health_check', 'diagnostics', 'traffic_health_check'). It lacks criteria for choosing this tool over others.

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 bears the full burden. It merely states it 'list all sites', implying a read-only operation, but does not explicitly confirm it is non-destructive, require authentication, or mention any side effects. For a simple list, this is minimal but acceptable; however, a clear statement of read-only behavior would improve transparency.

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 of 7 words, front-loaded with the key action. Every word is necessary and no filler exists. It is highly concise.

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 zero-parameter list tool with no output schema, the description is minimal but arguably adequate. However, it lacks context about what information is returned (e.g., site names, URLs, verification status) and does not explain the 'verified' criteria. Given sibling tools like bing_sites_add, it could be more helpful by noting this is the read side of site management.

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 no parameters, so schema coverage is 100%. The description does not add parameter information, but none is needed. According to the scoring rubric, zero parameters baseline is 4.

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 verb ('list'), the resource ('sites'), and the context ('verified in Bing Webmaster Tools'). It distinguishes from sibling tools like bing_sites_add (which adds a site) and bing_sites_delete (which deletes), but does not differentiate from the similarly named 'sites_list' tool, which may be from a different context.

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. For example, it does not mention that this is the read-only list for Bing Webmaster Tools, or that it should be used before adding or deleting sites. The description offers no context for usage decisions.

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 bears full responsibility for behavioral disclosure. It accurately portrays a read-only operation (finding keywords) but does not discuss authentication, rate limits, or error handling beyond the purpose.

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?

Single sentence, front-loaded with the verb 'Find', and zero wasted words. Every term is necessary for understanding the tool's core 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 simple tool with one parameter, the description is complete enough to convey the primary function, but lacks details about return format or expected output. Could be more helpful with a brief note on what the tool returns.

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 a single parameter described as 'The URL of the site'. The description does not add extra meaning to the parameter, but the schema already sufficiently documents it. 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 'Find keywords ranking positions 8-15 on Bing (near page 1)', specifying the verb, resource, and scope. It effectively distinguishes itself from siblings like bing_seo_cannibalization or bing_get_top_pages by focusing on a specific rank range.

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 usage guidance or alternatives are mentioned. The description implies use when searching for keywords near page 1, but lacks when-not-to-use or comparative context with siblings like seo_striking_distance without 'bing_' prefix.

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 present, so description carries full burden. It says 'detailed indexing and crawl information' but does not specify what is returned, permission requirements, or rate limits. Minimal behavioral disclosure.

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?

Single sentence of 10 words, front-loaded with verb and resource. No unnecessary words.

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?

No output schema, no annotations, and description only provides high-level purpose. Agent lacks information on return structure, pagination, or usage constraints. Incomplete for a tool with no structured guidance.

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 has 100% coverage with descriptions for both parameters (siteUrl: 'The site URL', url: 'The specific URL to inspect'). Description adds no extra meaning beyond what schema already provides, so baseline 3.

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 'Get detailed indexing and crawl information for a URL in Bing', specifying the verb (Get) and resource (indexing and crawl info for a URL). It distinguishes from siblings like bing_crawl_issues or inspection_inspect.

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 on when to use this tool versus alternatives, such as bing_crawl_issues or bing_url_submit. No prerequisites or context provided.

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 provided; the description does not disclose that it is a read-only operation, authentication needs, or rate limits, leaving the agent without critical behavioral context.

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?

Single sentence that efficiently states the tool's core purpose without any 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?

Minimal description for a tool with no output schema and no annotations; lacks any explanation of quota behavior or return format.

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%; the description adds no extra meaning beyond the schema's 'The URL of the site'.

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 ('Get') and resource ('remaining URL submission quota') with context ('for Bing'), clearly distinguishing from siblings like bing_url_submit.

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 on when to use this tool versus alternatives (e.g., bing_url_submit), nor any prerequisites or conditions.

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 fails to disclose critical behavioral traits such as authentication requirements, rate limits, error handling, or idempotency. The bare description 'submit' does not inform the agent of any side effects or constraints.

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, front-loaded sentence with no waste. While concise, it could be slightly expanded to include a usage hint without becoming overly verbose. The minimal structure is appropriate for a simple tool but misses an opportunity to improve completeness.

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 low complexity and no output schema, the description is incomplete. It does not specify return values (e.g., success indication, error handling) or prerequisites, which are important for an agent to invoke the tool correctly without additional information.

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?

Input schema has 100% description coverage for both parameters, so the baseline is 3. The tool description adds no additional value beyond the schema's parameter descriptions, which already clearly define 'siteUrl' and 'url'.

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?

Description clearly states the action (submit), resource (a single URL), and target (Bing for indexing). It effectively differentiates from sibling 'bing_url_submit_batch' by specifying 'single URL', making the tool's 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 for submitting a single URL, but does not explicitly state when to use this tool versus alternatives like 'bing_url_submit_batch' or 'bing_url_submission_quota'. No exclusions or context for when to avoid it are provided.

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 provided, and description lacks details on side effects, rate limits, authentication requirements, or whether the submission is immediate or queued.

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?

Single sentence, no redundancy, front-loaded key information (action, target, batch nature).

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?

Missing output schema and description—agent cannot know success/failure details, error handling, or per-URL status. Batch semantics require more info.

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?

Adds value by noting urlList max 500, supplementing the schema descriptions that are already present for both parameters (100% 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?

Clearly states 'Submit multiple URLs to Bing for indexing in a single batch', distinguishing it from single URL submission tools like bing_url_submit and quota tools.

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?

Implies use for batch submission of multiple URLs, but no explicit guidance on when to use vs alternatives like index_now or when not to use (e.g., if site not verified).

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 provided, so the description must carry the burden. It does not disclose whether the tool performs read-only analysis, what data is aggregated, any permissions required, or implications of the analysis (e.g., rate limits across sources).

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?

Single sentence, front-loaded with key information. No wasted words, but could be slightly expanded to improve other dimensions without losing conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.