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

No annotations provided, and the description does not confirm it is read-only or non-destructive. For a reporting tool, this is a gap; it should at least indicate it only reads data.

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.

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 mentions cost and ROAS and dimensions, but lacks full metric list, pagination behavior, or any mention of row limits. 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 4 parameters are fully described in the input schema (100% coverage). The 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 tool returns paid channel performance broken down by channel, campaign, source, and medium with cost and ROAS. It differentiates from siblings like ga4_paid_search_performance which only covers search.

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 it's for all paid channels but doesn't explicitly state when to use this versus other sibling tools like ga4_channel_performance or ga4_google_ads_performance. Guidance is implicit but not explicit.

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 such as read-only nature, rate limits, data freshness, or side effects. The transmission of query parameters implies a read operation, but the agent must infer this.

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 (one sentence) with no unnecessary words. However, it could be more structured by listing dimensions and metrics separately 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 no output schema and the tool's complexity (multiple dimensions and metrics), the description is insufficient. It does not explain the output format or how the breakdown is structured, leaving the agent to infer from the tool name.

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 minimal value: it mentions 'Optional channel filter', which corresponds to the channel parameter, but does not elaborate on other parameters or their relationships.

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 specifies the dimensions (campaign, source, medium) and metrics (sessions, conversions, revenue), with an optional channel filter. This distinguishes it from sibling tools like ga4_channel_performance or ga4_paid_search_performance, which focus on specific breakdowns.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase 'Optional channel filter' hints at usage but does not explicitly state when to prefer this tool over alternatives. No guidance on when to use this vs. other GA4 performance 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 are provided. The description mentions 'rollup' but fails to disclose behavioral traits such as default grouping definition, permission requirements, read-only nature, or return format. Minimal transparency for a data-retrieval 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?

One sentence, concise and to the point. However, it could be structured with bullet points for clarity, but it's not 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?

No output schema exists, and the description only lists metrics without explaining the response structure, pagination, or error behavior. Given the lack of annotations and output schema, the description is incomplete for agent usage.

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 baseline is 3. The description adds no extra meaning beyond the schema's parameter descriptions (start_date, end_date, property_id, limit). It does not elaborate on how these parameters affect the rollup.

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 returns a default channel group rollup with specific metrics (sessions, users, conversions, revenue) for channels like Organic Search, Paid Search, etc., distinguishing it from sibling tools that focus on specific channels or campaigns.

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 such as ga4_paid_search_performance or ga4_campaign_performance. The description implies an overview purpose but lacks when-to-use or when-not-to-use advice.

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 only states the output and sorting, but does not mention idempotency, auth needs, rate limits, or data freshness. The agent cannot infer safety or operational 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 extremely concise with two sentences. The first sentence delivers the key purpose upfront, and the second adds sorting detail. No superfluous information.

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

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool returns a report but has no output schema. The description gives a high-level idea of the output dimensions but lacks specifics like response format, column names, or whether it includes date range. Given the complexity of GA4 reports, this is mildly insufficient.

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 parameter details (e.g., meaning of 'key events', date range constraints). Baseline score of 3 is appropriate as the description does not improve parameter understanding.

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: it breaks down conversions and key events by session source, medium, and channel group, and sorts by key events descending. This distinguishes it from sibling tools that focus on specific channels or campaigns (e.g., ga4_channel_performance, ga4_campaign_performance).

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 guidance on when to use this tool versus alternatives. It lacks explicit context about when this breakdown is appropriate or when to prefer sibling tools like ga4_all_paid_performance or ga4_organic_search_performance. No when-not or prerequisite info 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?

No annotations provided, so description should compensate. It discloses the prerequisite (GA4 link) but does not state that the tool is read-only, has rate limits, or other behavioral traits. The term 'performance' implies non-destructive, but not explicit.

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 plus a requirement line. Front-loaded with key identifier 'Paid: Google Ads...' and metric list. No superfluous words; every part 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?

Covers what data is returned and the prerequisite, but does not mention default sorting, pagination behavior, or what happens when limit is reached. Given no output schema, description could be more complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3. Description does not add additional parameter meaning beyond what is already in the schema. Parameters are adequately described in schema, but no extra context 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 it returns paid Google Ads performance data at campaign × ad group × keyword granularity, with specific metrics listed. Distinguishes from siblings like ga4_campaign_performance and ga4_paid_search_performance by specifying 'Google Ads' and the precise 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?

Mentions prerequisite 'Requires Google Ads ↔ GA4 link' but does not explicitly guide when to use this over siblings such as ga4_all_paid_performance or ga4_paid_search_performance. Usage context is implied but not directly addressed.

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 burden. It states the tool returns top landing pages by specified metrics and mentions an optional filter. However, it does not disclose whether data is historical, any rate limits, permission needs, or response format. The schema covers parameters, but the description adds limited behavioral context beyond its core function.

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 followed by a parenthetical example. It is front-loaded with the core purpose ('Top landing pages by sessions/engagement/conversions') and wastes no 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 no output schema, the description hints at the return type (top landing pages with metrics) but does not specify exact columns or ranking details. For a simple listing tool, it is largely complete, but could be slightly improved by noting it returns a ranked list.

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 baseline is 3. The description reiterates the channel filter with examples, adding minimal new information 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?

The description clearly states the tool returns top landing pages with key metrics (sessions, engagement, conversions) and mentions an optional channel filter. This effectively distinguishes it from sibling tools that focus on other dimensions like campaigns or channels.

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 landing page analysis with optional channel filtering but provides no explicit guidance on when to use this tool versus alternatives like ga4_channel_performance or ga4_campaign_performance, given the sibling list.

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 describes what data is returned (metrics and breakdowns) but does not disclose behavioral traits such as rate limits, authentication requirements, or data freshness. For a reporting tool, it is adequate but not comprehensive.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single sentence front-loaded with key information: tool purpose, metrics, and breakdown options. No wasted words; efficient and scannable.

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 schema fully describes parameters and no output schema is provided, the description sufficiently tells what the tool returns and how to break down the data. It is complete for a straightforward reporting tool with good sibling 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?

The schema covers 100% of parameters with descriptions, but the description adds value by explaining the breakdown options and metrics in context. It clarifies that the default breakdown is landing page and lists the available dimensions, going beyond the schema's technical 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?

The description clearly states the tool is for Organic Search traffic, listing key metrics (sessions, users, engagement, conversions) and breakdown dimensions. It uses 'SEO' as a prefix and 'Organic Search' to distinguish from paid or channel-specific tools among 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?

The description implies usage for organic search performance analysis, but lacks explicit guidance on when to use vs alternatives like paid search or campaign tools. Sibling names provide context, but no direct exclusions or preconditions are stated.

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 mention behavioral traits like read-only nature, rate limits, or side effects. The tool is likely read-only but this is not stated, leaving the agent uninformed about 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, front-loaded sentence with no extra words. All key information (subject, metrics, breakdown options) is included efficiently.

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?

Description covers the essential return values (sessions, conversions, cost, CPC) and breakdown dimension, but does not specify row structure or pagination. Given no output schema, this is reasonably complete for a simple report 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 description coverage is 100%, so baseline is 3. The description mentions breakdown dimensions but these are already fully documented in the schema's enum and parameter descriptions, adding minimal extra meaning.

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 specifies the tool returns metrics (sessions, conversions, cost, CPC) for Paid Search traffic, with breakdown options. It distinguishes itself by explicitly targeting Paid Search, differentiating from sibling tools like ga4_organic_search_performance.

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 ga4_all_paid_performance or ga4_google_ads_performance. Description lacks any usage conditions or exclusions.

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

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

With no annotations, the description bears full burden. It states the time window (last 30 min) and breakdown options, but does not disclose output format, authentication needs, rate limits, or that it returns only one metric. Adequate but lacking 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?

The description is a single 18-word sentence that conveys the core functionality efficiently. No unnecessary words, but could be slightly front-loaded with the action verb.

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

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description does not explain the return format (e.g., list of dimension-value pairs with count), nor does it contextualize the tool among siblings for realtime vs historical data. Given no output schema, more detail 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 67% (property_id and breakdown described, limit not). The description adds value by explaining the breakdown concept and listing example dimensions, but does not detail property_id's override behavior or the limit parameter's purpose. Partially compensates.

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 current active users in the last 30 minutes, with explicit breakdown options (screen/page, country, device, or audience). This distinguishes it from sibling tools that focus on historical performance reports.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives like ga4_run_report or ga4_channel_performance. It does not mention that this is for realtime data while others cover longer time ranges.

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 present, so the description must fully disclose behavioral traits. It only states 'Flexible GA4 Data API runReport' and 'Pass any dimensions + metrics', lacking details on rate limits, data freshness, or whether the operation is read-only. The minimal description does not adequately cover behavioral 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 two sentences, front-loading the key purpose ('Flexible GA4 Data API runReport') and immediately stating usage context. Every sentence is necessary and concise, with no extraneous 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 complexity of 8 parameters, no output schema, and no annotations, the description is too minimal. It does not explain return format, error handling, or limitations (e.g., maximum rows). For a flexible API tool, the agent needs more context to use it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage for all 8 parameters. The description adds no new semantic value beyond the schema's existing parameter descriptions, such as the examples and default values. 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 tool is for flexible GA4 Data API runReport, specifying it handles arbitrary dimensions and metrics. It explicitly distinguishes from sibling preset tools by stating 'Use for custom reports the preset tools don't cover.'

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear guidance on when to use this tool ('custom reports the preset tools don't cover'), implying it should not be used when preset tools suffice. However, it does not explicitly list or exclude alternative sibling tools.

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