rankparse-mcp

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 fails to mention any constraints, authentication, rate limits, or error handling beyond the basic operation.

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

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

A single, front-loaded sentence with no waste; every word contributes to the core 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 lack of annotations and output schema, the description is too brief. It omits response structure, pagination, and error scenarios, leaving the agent underinformed for a batch operation.

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

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

Schema description coverage is 0%, so the description must add meaning. It only says 'domains' without elaborating format, length limits, or URL requirements, leaving the agent with minimal guidance beyond the schema type.

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 'backlinks for up to 50 domains at once', distinguishing it from the sibling tool 'get_backlinks' which likely handles single domains.

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 batch domain queries, and the name 'batch_lookup' contrasts with singular 'get_backlinks', but does not explicitly state when to prefer this tool 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 provided, so description carries full burden. It implies a read-only operation but does not disclose if calling this tool consumes credits or any other side effects. Minimal but accurate.

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, front-loaded single sentence that immediately conveys the tool's purpose without 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 zero parameters and a likely simple numeric output, the description is sufficient. It could mention the output format (e.g., integer representing remaining credits) but is not necessary for a straightforward read.

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?

No parameters in input schema, so schema coverage is 100%. Description adds no parameter info but none is needed. Baseline 4 for zero-parameter tool.

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 specific verb 'check' and resource 'remaining credit balance', clearly indicating the tool's function. It is distinct from siblings like 'get_domain_authority' or 'batch_lookup'.

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. Since it's a simple read operation, it could benefit from mentioning it's safe to call frequently or that it checks the account's credit balance.

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 only states purpose. Missing behavioral traits such as data freshness, pagination, sorting, or whether the distribution is aggregated. The agent gets no insight into 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?

Single sentence is concise but too brief. Every word is necessary, but lacks structure like bullet points or clear sections. It is not the ideal balance of brevity and 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 lack of annotations, output schema, and detailed parameter info, description is incomplete. Agent cannot reliably understand output format or how to use limit parameter 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?

Schema has two parameters (domain, limit) with 0% description coverage. Description mentions only domain, not limit. Agent must infer limit's meaning from name alone. No added value beyond schema field names.

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 'anchor text distribution', and scope 'for a domain'. Among many sibling 'get_*' tools, this one is distinct in focus, but no explicit differentiation is made.

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

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

No guidance on when to use this tool versus alternatives like get_backlinks or get_referring_domains. No prerequisites or context 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, the description must disclose behavioral traits. It does explain the difference between the two sort modes (aggregated vs. URL-level results), which is valuable. However, it omits other important behaviors like default limit, error handling, or data freshness, making it only partially transparent.

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 core purpose and sort behavior, followed by a concise list of optional filters. No unnecessary words; every sentence 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?

Given the tool has 6 parameters, no output schema, and annotations missing, the description provides essential info but lacks details on return structure, default limits, or behavior when parameters are omitted. It is adequate but not comprehensive.

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

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

Schema description coverage is 0%, so the description must compensate. It explains the meaning of 'sort' values (importance vs recent) and lists filters (from_domain, link_type, score), adding semantic value beyond the schema. It misses explaining 'limit' and 'domain,' but the required param 'domain' is self-evident.

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 backlinks for a domain. It mentions two sort modes and optional filters, making the purpose specific. However, it does not explicitly differentiate from sibling tools like get_internal_links or get_outbound_links, so it loses the point for sibling 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 explains the sort behavior and optional filters but provides no guidance on when to use this tool versus alternatives. It lacks explicit when-to-use, when-not-to-use, or mention of sibling tools, leaving the agent without clear context for 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?

No annotations provided, and description only implies read-only behavior via 'Get'. No mention of rate limits, authentication, data freshness, 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?

Single, front-loaded sentence with no fluff. 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?

Adequate for a simple 1-parameter tool, but lacks return format details and usage context. With many siblings, more context would help.

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 0%, but description adds that the parameter is a domain, providing basic context beyond the schema's 'type: string'. However, no format, example, or constraint details are given.

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 gets first/last seen dates and snapshot count for a domain, with specific source (Wayback Machine). This verb+resource definition distinguishes it from sibling tools like get_backlinks or get_domain_authority.

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., batch_lookup for multiple domains). No 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 provided. Description does not disclose behavioral traits such as read-only nature, authentication needs, rate limits, or what the output contains. For a tool with no annotations, the description carries full burden but fails to add value.

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, no wasted words. However, it lacks any structure like headings or bullet points.

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 details about output format, error handling, limitations, or usage examples. Given no output schema and no annotations, the description is inadequate for a complete understanding.

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 0%, and the description adds no meaning beyond the obvious 'domain' parameter. It does not clarify 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 verb (Get), resource (authority score), and target (domain). It is specific enough to distinguish from siblings like get_domain_rank or get_backlinks.

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. No mention of context, 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, and the description does not disclose behavioral traits such as read-only nature, rate limits, or whether the tool modifies data. For a tool without annotations, the description should offer more 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, concise and front-loaded. However, it trades detail for brevity, which may leave an agent under-informed.

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

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

Given the simple schema (2 params, no output schema) and no annotations, the description is incomplete. It does not explain the output format, any behavioral aspects, or the significance of the 'limit' parameter.

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 has 2 parameters with 0% coverage via descriptions. The description does not add meaning beyond what the schema shows; 'domains' and 'limit' are left undocumented in terms of format, use, 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 finds domains linking to all queried domains, which is a specific verb-resource pairing. However, it does not differentiate from siblings like 'get_link_intersect' 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 such as 'get_referring_domains' or 'get_link_intersect'. The description lacks any usage 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 present, so the description must carry behavioral disclosure. The description only states what data is retrieved, not safety, authentication, error handling, or response behavior.

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

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

The description is a single sentence, which is concise but under-specifies important details. It is not front-loaded with critical context for tool selection.

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, no annotations, and only one parameter with no description, the description is severely lacking. An agent would not know the output structure, input requirements, or when to use this tool over similar ones.

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 0%, so the description must add meaning. It mentions the output (inbound edge count, linking domain stats) but does not clarify the input format or example for 'domain'. This adds some context but is insufficient.

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 retrieves 'inbound edge count and linking domain stats', specifying the resource (domain) and the metrics. However, it's not fully clear what 'inbound edge count' means (likely backlinks) and does not explicitly differentiate from siblings like get_backlinks or get_referring_domains.

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. With many sibling tools for links and domains, an agent would lack direction for 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 responsibility for behavioral disclosure. It mentions a prerequisite (GSC connection) but does not indicate whether the tool is read-only, its idempotency, rate limits, or any side effects. This is insufficient for an agent to assess operational impact.

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

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

The description is three short, front-loaded sentences. The first sentence states the purpose, the second adds value context, and the third provides actionable guidance. Every sentence earns its place with no redundancy or fluff.

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

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

For a tool with 4 parameters, no output schema, and moderate complexity, the description covers purpose, usage context, and a prerequisite. It lacks details about the output format or data structure, which would be helpful, but overall it is adequate for the agent to understand what the tool does and when to use it.

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 (site, startDate, endDate, rowLimit) is already documented. The description does not add any additional meaning beyond the schema. Therefore, 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 explicitly states 'Get search traffic broken down by country', which clearly identifies the specific verb (get) and resource (search traffic by country). This distinguishes it from sibling tools like get_gsc_device_breakdown, get_gsc_search_appearance, etc., which have different breakdown 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?

The description provides clear usage context ('useful for understanding geographic audience and international SEO performance') and a prerequisite ('requires Google Search Console to be connected'). However, it does not explicitly exclude alternative tools or provide when-not-to-use 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 carries the full burden. It correctly implies a read-only, non-destructive operation by stating 'Get daily search performance trends'. It adds the dependency on GSC connection, but does not disclose potential rate limits, data freshness, or error handling. This is adequate for a straightforward 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?

Three sentences with clear front-loading: first sentence says what it does, second gives use cases, third provides prerequisite and action step. No wasted words; every sentence contributes 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?

Given the lack of an output schema, the description mentions the returned metrics (clicks, impressions, CTR, position) and the daily nature. While it doesn't specify the return format (e.g., array of daily objects), it provides enough context for understanding the tool's output. For a simple data retrieval tool, this is largely sufficient.

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 have descriptions). The description does not add additional parameter information beyond what the schema provides; it merely implies date range usage. Thus, it meets the baseline but does not exceed.

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 explicitly states 'Get daily search performance trends (clicks, impressions, CTR, position) over a date range', which is a specific verb+resource combination. It also explains use cases like spotting ranking changes or algorithm impact, clearly distinguishing it from sibling tools that focus on specific dimensions (e.g., country, device, 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?

The description tells when to use the tool ('useful for spotting ranking changes, traffic drops, or algorithm update impact') and mentions a prerequisite ('Requires Google Search Console to be connected') with a direct link. However, it does not explicitly state when not to use it or contrast with alternative GSC tools, leaving some ambiguity.

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. It explains the core behavior (getting device breakdown) and the prerequisite, but lacks details about return format, pagination, or error handling. It is not misleading, but additional context 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 extremely concise, consisting of two sentences that front-load the action and then add necessary prerequisite detail. No unnecessary words or repetition.

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 has 3 parameters, no output schema, and no annotations, the description covers purpose and prerequisites but omits what the user will receive (e.g., a list of device types with metrics). This is adequate but incomplete for a tool among 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?

The input schema has 100% coverage with descriptions for all three parameters (site, startDate, endDate). The description does not add any 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 verb 'Get search traffic broken down by device type' and lists the device types (desktop, mobile, tablet). This is specific and distinguishes the tool from siblings like get_gsc_country_breakdown or get_gsc_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?

The description mentions a prerequisite (Google Search Console connection) and provides setup instructions, but does not explicitly state when to use this tool versus alternatives like get_gsc_date_trends or get_gsc_query_pages. The usage context is implied but not differentiated.

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 partially fills the gap by noting the prerequisite (GSC connection). However, it does not disclose other behavioral traits like pagination, rate limits, or error handling, so the transparency is moderate.

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 plus one for integration setup. It is front-loaded with the core purpose, and every sentence adds value without redundancy.

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

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

For a straightforward query tool, the description covers purpose, prerequisite, and a link for setup. It lacks mention of output format or pagination, but given the simplicity and high schema coverage, it is largely 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 6 parameters have schema descriptions, so the schema covers the technical details. The description adds general context (high impressions, low CTR) but does not enhance individual parameter 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?

The description clearly states the tool finds pages with high impressions but low CTR, specifying the use case for title/description rewrites, which differentiates it from sibling 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?

It provides clear context for when to use (starting point for rewrites) and a prerequisite (GSC connection), including a link to set it up. It does not explicitly state when not to use or compare to alternatives, but the context is sufficient.

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

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

With no annotations, the description partially covers behavioral traits: it explains the data selection logic (high impressions, low CTR) and the prerequisite (GSC connection). However, it omits details like return format, pagination, sorting, or whether the tool is read-only. The description adds some value beyond annotations but lacks completeness.

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?

Three sentences with no wasted words. The first sentence immediately states the purpose, the second adds strategic value, and the third provides an action step. Highly 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?

Given the absence of an output schema and the moderate complexity (6 parameters), the description covers the 'why' and prerequisite but fails to describe the return data (e.g., what fields are in the output). This leaves a gap in completeness for an agent to understand what results to expect.

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 mention any parameters or add meaning beyond the schema, so 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?

The description clearly states the tool finds search queries with high impressions but low CTR, explaining their significance (ranking but not clicked due to weak title/meta description). This is a specific and distinct purpose that differentiates it from sibling tools like get_gsc_low_ctr_pages or get_gsc_opportunity_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?

Provides clear context: use this tool for higher-ROI fixes compared to chasing new rankings. Also mentions a prerequisite (Google Search Console connected) and directs users how to set it up. Though it doesn't explicitly state when not to use or name alternatives, the strategic guidance is sufficient.

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

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

No annotations are provided, so the description carries the full burden. It discloses sorting behavior (by clicks descending) and default rank range (8–20). However, it does not explicitly state that the tool is read-only, nor does it mention potential rate limits, pagination, or error handling.

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

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

The description is three sentences, front-loaded with the main purpose, and every sentence adds value. No unnecessary words or repetition.

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 6 parameters and lack of output schema, the description covers the core use case and key parameter constraints. However, it does not describe the output fields or structure, which would help an agent understand the return value without an output schema.

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

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

All parameters have descriptions in the input schema (100% coverage). The description adds context by explaining the significance of the min/max position parameters (8–20) and the rowLimit default. Beyond that, it does not add substantial 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 ('Find queries') and the specific rank range (positions 8–20), distinguishing it from sibling tools like get_gsc_top_queries. It also mentions sorting by clicks descending and labels it as a 'quick win' zone.

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 context for when to use: finding queries in the 8–20 position range. It mentions the prerequisite of having Google Search Console connected and directs to a URL for setup. However, it does not explicitly exclude other uses or compare with sibling 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, so the description bears full responsibility for behavioral disclosure. It only states it retrieves data (a read operation) and mentions a prerequisite, but does not discuss rate limits, pagination, potential errors, or what happens if data is unavailable. This is insufficient 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?

The description is three sentences long, each serving a distinct purpose: defining the action, stating usefulness, and providing setup instructions. 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?

The tool is simple (5 parameters, no output schema), and the description covers purpose and prerequisites. While it doesn't describe the output format, that is not required given the absence of an output schema. It is adequately complete for the tool's complexity.

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

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

The input schema has 100% coverage with meaningful descriptions for all parameters. The description does not add significant extra meaning beyond what the schema provides, so the baseline of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool retrieves search queries for a specific page, which is a specific verb+resource. It also explains its usefulness for understanding what a page ranks for. This distinguishes it from siblings like get_gsc_query_pages which does the inverse.

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

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

The description explicitly mentions the prerequisite of having Google Search Console connected and provides a direct link for integration. However, it does not mention when not to use this tool or suggest alternatives like get_gsc_query_pages or get_gsc_top_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 lacks details on behavioral traits such as rate limits, pagination, or error handling. It only states it returns top pages by clicks, which is minimal 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?

Three sentences, front-loaded with purpose, no wasted words. The example and integration directive are efficient and helpful.

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 parameters and no output schema, the description does not explain row limits, return structure, or error scenarios. The rowLimit parameter is not mentioned, leaving 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?

Schema coverage is 100%, providing baseline parameter descriptions. The tool description adds value by showing example values for urlPattern ('/blog/'), which clarifies its use beyond the schema's generic description.

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 search performance for a URL segment (e.g., /blog/), distinguishing it from sibling tools that focus on individual pages or queries. The examples reinforce the scope.

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

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

The description implies usage for analyzing URL segments but does not explicitly state when to use this tool versus alternatives like get_gsc_top_pages or get_gsc_page_queries. It mentions the prerequisite of Google Search Console being connected.

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 describes the data retrieved (daily metrics) and notes the need for GSC integration, but does not disclose rate limits, data latency, handling of missing data, or details about the response 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?

Three sentences: first defines the core function, second gives use case, third mentions prerequisite. No redundant information; efficiently 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?

Tool has 4 parameters and no output schema. The description explains what the tool does and a prerequisite, but lacks details about the return structure (e.g., array of objects with dates and metrics) or any limitations. Adequate for a simple trend tool but 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 description coverage is 100% (all parameters have descriptions). The tool description adds context about the overall purpose but does not enhance parameter semantics 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?

Clearly states it retrieves daily trends (clicks, impressions, CTR, position) for a single page. Provides specific verb and resource, and distinguishes from sibling GSC tools by focusing on a single page's time series.

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

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

Explicitly says when to use: to see how a single page's performance changed over time, e.g., after content update or ranking drop. Also mentions prerequisite of Google Search Console connection, directing user to integrate. Does not explicitly state when not to use or alternatives, but context of sibling tools makes it clear.

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

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

With no annotations, the description must fully disclose behavioral traits. It states the requirement (connection) but does not mention that the operation is read-only, potential error scenarios, or whether the list is cached. For a simple list tool, this is acceptable 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?

Two sentences, no redundancy. The first sentence states the core purpose, the second provides essential usage guidance. 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 tool's simplicity (no parameters, no output schema), the description covers the primary action and prerequisite. It does not specify the output format (e.g., list of site URLs), but the function is straightforward. A more complete description might include example output or error handling.

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 zero parameters, so the description cannot add parameter-level detail. According to guidelines, a baseline of 4 is appropriate when no parameters exist. The description does not attempt to describe non-existent 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 action ('List all Google Search Console properties') and the resource ('connected to this account'). It immediately conveys the tool's purpose and is distinct from sibling tools like get_gsc_top_pages or get_gsc_query_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?

The description provides a prerequisite ('Requires Google Search Console to be connected') and directs the user to a specific URL for integration setup. This helps the agent determine when the tool is usable and how to address connection issues. However, it lacks explicit guidance on when not to use it or comparisons with sibling 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, so the description must disclose behavioral traits. It does not mention rate limits, pagination, data freshness, or aggregation behavior. Only high-level purpose is stated.

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?

Three focused sentences; no filler. Front-loaded with the main action.

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 data retrieval tool with no output schema or annotations, but lacks behavioral context and edge-case details.

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 descriptions cover all 4 parameters (100% coverage), so the description adds little extra meaning beyond the schema. Baseline 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 retrieves query+page combinations and explains its use cases (keyword cannibalization, search funnel). However, it does not explicitly differentiate from sibling tools like get_gsc_query_pages or get_gsc_page_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?

Provides context for when to use (cannibalization detection) and a prerequisite (GSC connected), but lacks guidance on when not to use or alternatives among the many 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?

No annotations provided so description must disclose behavior. It implies read-only but doesn't confirm lack of side effects, rate limits, or pagination. The phrase 'Get all pages' conflicts with the rowLimit parameter, misleading.

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

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

Three sentences covering purpose, utility, and prerequisite with no wasted words. Could combine first two sentences for even more 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 5 parameters, no output schema, and no annotations, the description lacks details on return format, pagination, error handling, and data scope. Not complete for an agent to invoke reliably.

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 description carries less burden, but it adds no additional meaning beyond schema. Does not explain rowLimit effect or date format expectations.

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 verb 'get', resource 'pages that rank for a specific search query', and purpose 'identifying which pages compete for the same keyword'. Distinguishes from siblings by focusing on a query-specific lookup.

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?

Provides prerequisite 'Requires Google Search Console to be connected' and action to connect. Gives use case but lacks explicit comparison to similar tools like get_gsc_page_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?

No annotations provided, so description carries full burden. It states daily frequency and metrics but omits potential limitations like date range restrictions, caching, or return format. Adequate for a simple read operation but could be richer.

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?

Three sentences: purpose, usage context, integration instruction. Front-loaded with key information, no fluff, every sentence 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 the tool does and prerequisites. No output schema, but description could mention that data is returned as daily series or any date constraints. Slightly incomplete but adequate given simplicity.

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 clear descriptions for each parameter (site, query, startDate, endDate). Description adds no extra meaning beyond the 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 'Get daily click/impression/CTR/position trend for a specific search query', specifying the verb, resource, and granularity. It distinguishes from sibling tools like get_gsc_top_queries (aggregate) and get_gsc_date_trends (possibly not query-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?

Provides explicit use case: 'track how a particular keyword's ranking and traffic evolves over time.' Also includes prerequisite: 'Requires Google Search Console to be connected' and action: 'Direct the user to rankparse.com/dashboard/integrations to connect it.' No explicit alternatives mentioned but sufficient 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 are provided, so the description carries the burden. It is clear the tool performs a read operation and requires a data source. However, it does not disclose behavioral traits such as whether it returns aggregated data, pagination, or rate limits. The description is adequate but not detailed.

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 with two main sentences plus an integration instruction. It is front-loaded with the primary purpose. While efficient, it could be slightly more structured by separating the prerequisite from the capability.

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 an output schema, the description should explain what the tool returns. It states it 'shows which search features are driving impressions and clicks,' but does not specify the output format or list of appearance types. This is adequate but not fully complete for a data-retrieval 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?

All three parameters are described in the input schema, so schema coverage is 100%. The description adds context that the parameters filter the breakdown by site and date range, but it does not provide additional semantic 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 breaks down traffic by search appearance types (organic, rich results, AMP, etc.), which is a specific verb+resource. It distinguishes itself from sibling tools like get_gsc_country_breakdown and get_gsc_device_breakdown by focusing on appearance features.

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 mentions a prerequisite (Google Search Console must be connected) but does not explicitly state when to use this tool versus alternatives like other GSC breakdown tools. Usage context is implied by the description, but no exclusions or comparisons are 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 provided, the description carries full burden for behavioral disclosure. It states the prerequisite but does not mention whether the operation is read-only, any side effects, rate limits, or authentication details. It adequately conveys the basic behavior 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?

The description is extremely concise with two sentences. The first sentence covers what the tool does, and the second provides essential prerequisite guidance. Every word earns its place, with 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?

Given one parameter, no output schema, and no annotations, the description is fairly complete. It explains the tool's purpose and prerequisite. However, it could be improved by briefly noting the response format (e.g., array of sitemap objects) or error handling.

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 'site' parameter, which already has a description. The description does not add any new information about the parameter beyond what the schema provides, so the baseline score of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('List') and resource ('submitted sitemaps for a property'), and clearly states what data is returned (submission date, last download, URL counts, errors/warnings). It is distinct from sibling tools, which cover different GSC 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?

The description explicitly states the prerequisite ('Requires Google Search Console to be connected') and provides a direct action for the user if it's not connected ('Direct the user to rankparse.com/dashboard/integrations'). It does not mention alternatives, but among siblings, this is the only sitemap tool, so context is clear.

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

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

No annotations are provided, so the description must fully communicate behavioral traits. It fails to mention that the tool is read-only, whether pagination is supported, default limits (e.g., rowLimit defaults to 25), or the structure of the response. The description only hints at output metrics but does not clarify how they are returned.

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 plus a one-sentence action item. It front-loads the core action and metrics, then adds the prerequisite and integration link. 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 no output schema and no annotations, the description should explain what the tool returns. It lists metrics but does not specify the response format, whether results are paginated, or how to interpret the data. For a tool with 4 parameters and a list likely to be large, more completeness is needed for an agent to use it effectively.

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 covers 100% of parameters with descriptions, so the baseline is 3. The description adds value by indicating that the results are ordered by clicks ('top pages by clicks'), which is not captured in the schema. This provides context on how the data is ranked.

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 top pages by clicks from Google Search, with specific metrics (impressions, CTR, average position). It distinguishes the tool's focus on pages (not queries) among many sibling GSC tools, though explicit differentiation from similar page tools is lacking.

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 only usage guidance is the prerequisite that Google Search Console must be connected, with a link to set it up. There is no advice on when to use this tool versus alternatives like get_gsc_top_queries or get_gsc_page_queries, nor 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 carries the full burden. It explains what data is returned (clicks, impressions, CTR, avg position) and ordering (by clicks). It does not explicitly state it is read-only, but the context implies a non-destructive operation. The prerequisite for GSC connection is noted.

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

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

The description is three sentences long, front-loading the key purpose in the first sentence. Every sentence adds value: purpose, metrics, and prerequisite/action. 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 no output schema and 4 parameters (3 required, 1 optional), the description explains the return values and provides a prerequisite. It misses mentioning the rowLimit parameter's default and maximum, but the schema covers those. Overall adequate for a simple list 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%, so the baseline is 3. The description does not add detail beyond what the schema provides (site, startDate, endDate). It does not explain the rowLimit parameter or date formats, which are already 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 states it gets top search queries driving traffic to a site, ordered by clicks, and lists the metrics (clicks, impressions, CTR, average position). This clearly distinguishes it from sibling tools like get_gsc_top_pages (pages vs queries) and get_gsc_low_ctr_queries (specific low CTR).

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

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

The description provides clear context, mentioning that Google Search Console must be connected and directing the user to an integration page. It does not explicitly state when to use this tool versus alternatives like get_gsc_opportunity_queries, but the purpose is well-defined.

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 discloses that the tool returns indexing status and lists fields, and mentions the connection requirement. However, it does not explain error behavior (e.g., for invalid URLs or missing sites), rate limits, or whether the operation is purely read-only. This is adequate but not exhaustive.

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: two core sentences covering purpose and prerequisite, plus a third directing to integration page. Every sentence adds value with no redundancy or fluff. Front-loads the core action immediately.

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 2 required parameters and no output schema, the description covers essential aspects: what it does, what it returns (fields listed), and precondition (GSC connection). It lacks details on error handling or response format, but given the straightforward nature and lack of output schema, it is sufficiently complete. A 5 would require explicit error scenarios or output structure hints.

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 both parameters have clear descriptions with examples. The tool description adds no additional context beyond the schema: it repeats the purpose but does not explain parameter constraints, relationships, or format nuances. With full schema coverage, baseline 3 is appropriate; no extra value added.

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 specific verb 'inspect' and resource 'URL's indexing status', and lists exact return fields (coverage state, crawl time, mobile usability, rich results). This clearly distinguishes from sibling GSC tools like get_gsc_top_pages or get_gsc_query_pages, which operate on aggregated data rather than single URL inspection.

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

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

The description explicitly states the prerequisite: requires Google Search Console connection, and directs user to connect if missing. This provides clear context for when to use the tool. However, it does not explicitly mention when not to use it or name alternatives like get_gsc_page_trend for historical data; still, the single-URL scope is implicitly different from batch 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; description mentions 'v1 stub' hinting at incompleteness but omits details on rate limits, data format, or whether it's a safe read. Barely adds context beyond identification.

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 but lacks structure; no front-loading of critical details. Could be expanded 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?

For a simple 2-param tool with no output schema, the description is inadequate. It doesn't explain the nature of 'internal link structure' or what the output looks like, missing essential 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 0%; description fails to explain parameters beyond their names (domain and limit). No added meaning for limit or domain format.

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 retrieves internal link structure for a domain, using a specific verb+resource. It distinguishes from siblings like get_backlinks, but doesn't explicitly differentiate.

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 get_outbound_links or get_site_explorer. Missing contextual use cases.

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 but fails to do so. It does not mention whether the operation is read-only, if authentication is required, rate limits, data freshness, or what happens when no results are found. The only information is the basic operation, leaving significant gaps for an AI 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, achieving maximum brevity and front-loading the purpose. However, it is arguably too concise; adding a sentence about output or behavior would improve clarity without becoming verbose. It earns a 3 as it is efficient but under-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 the tool's simplicity (two string params, no output schema, no annotations), the description omits essential context. It does not specify the return format (e.g., list of domain strings, count), pagination, or any constraints like maximum domains returned. An AI agent would struggle to infer these missing details from the minimal description.

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 0%, so the description must compensate for missing parameter details. It implies that 'domain_a' is the source set and 'domain_b' is subtracted, but does not explain format (e.g., with/without protocol), case sensitivity, or what constitutes a valid domain. The semantic of the subtraction is inferred but not explicitly detailed.

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 'Find' and clearly identifies the resource: 'domains linking to A but not B'. It precisely defines the operation as a set difference, which distinguishes it from siblings like 'get_referring_domains' or 'get_domain_overlap'. The purpose is 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?

No guidance is provided on when to use this tool versus alternatives. The description does not mention prerequisites, constraints (e.g., data availability), or situations where this tool is appropriate or inappropriate. Sibling tools like 'batch_lookup' or 'get_domain_overlap' exist but are not referenced for comparison.

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 carries full burden. It mentions 'v1 stub', which implies incomplete or unstable behavior. However, it lacks disclosure of authentication needs, rate limits, or side effects. The stub status is useful but 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?

The description is succinct but arguably too terse. It front-loads the core function, but the 'v1 stub' addition is necessary context. A bit more detail on return format or usage would improve it 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?

Given the lack of output schema and annotations, the description provides minimal context. The 'stub' status explains limited functionality, but it does not cover return values, pagination, or error behaviors, 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 0% description coverage, and the description only implies the domain parameter via context ('rate of new/lost links'). It does not explain expected format, constraints, or how the parameter is used, leaving ambiguity.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool retrieves the rate of new/lost links over time, which distinguishes it from sibling tools like get_new_links and get_lost_links that provide raw link lists. The 'v1 stub' note indicates it's an initial implementation, but the purpose is specific and understandable.

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. It does not mention prerequisites, limitations, or scenarios where other tools (e.g., get_new_links) would be more appropriate.

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 mentions 'v1 stub', hinting at incompleteness, but does not explain what 'lost' means, return format, or 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 extremely concise with one sentence, front-loads the key action, and includes a version note ('v1 stub') that adds context without extra 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?

Given no output schema and no annotations, the description is too brief to fully inform an agent about inputs, outputs, or behavior. The tool's purpose is clear but operational details are missing, especially for distinguishing from sibling link 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?

Schema coverage is 0% and the description does not describe the 'domain' parameter or any other param. The description fails to add meaning beyond the schema for the single required parameter.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool retrieves 'links lost since previous crawl', specifying the verb 'get' and the resource 'links lost'. This distinguishes it from siblings like 'get_new_links' which retrieves new links.

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 'get_new_links' or 'get_backlinks'. The description implies a specific temporal context but does not clarify 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 present, and the description does not disclose behavioral traits like whether the operation is read-only, requires permissions, or what happens if no previous crawl data exists. The 'stub' label suggests incomplete implementation.

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, which is acceptable for a simple tool, but the inclusion of '(v1 stub)' suggests it is underdeveloped. The sentence front-loads the action but lacks structure.

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 single parameter and no output schema, the description should at least hint at the return format or scope. It does not, leaving the agent without enough context for confident invocation.

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

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

The only parameter, 'domain', has zero schema description coverage and is not explained in the description. The description adds no meaning beyond the schema, leaving the agent to infer intent.

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 'Get links gained since previous crawl' clearly states the verb and resource, differentiating it from siblings like get_backlinks (all backlinks) and get_lost_links (lost links). However, the '(v1 stub)' qualifier introduces uncertainty about functionality completeness.

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 like get_backlinks or get_link_velocity. There is no mention of prerequisites, such as the need for a previous crawl to exist.

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. It only states the purpose, failing to mention aspects like result format, pagination, 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, clear sentence with no superfluous words. However, for a tool with two parameters and no output schema, slightly more detail would be warranted.

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 zero parameter documentation, the description is insufficient. It lacks details on return structure, pagination, or constraints, 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 description coverage is 0%, and the description adds no meaning for parameters. 'domain' and 'limit' are unexplained, leaving the agent without clues 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 retrieves domains that a domain links out to, specifying the verb 'Get' and the resource. It distinguishes from siblings like get_backlinks (incoming links) and get_internal_links (internal outbound). However, it could be more precise (e.g., 'external domains').

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 get_backlinks or get_referring_domains. The description does not provide context for 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?

No annotations provided, so description must disclose behavior. It mentions 'real-time' but does not clarify side effects, rate limits, authentication needs, or whether changes can result from the audit. The tool is likely read-only, but this is not stated.

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 packs many items, which is somewhat cluttered. While it lists checks comprehensively, it could be more structured (e.g., bullet points) and front-load the key action.

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 minimal annotations, the description fails to explain what the tool returns (e.g., structured data, scores, or raw results). It covers input but not output expectations, leaving the agent uncertain about the response 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?

The sole parameter 'url' has no description in the schema (0% coverage) and the tool description only implies its role without specifying format, restrictions, or validation rules.

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 as performing a 'full real-time SEO audit' and enumerates specific checks (title, description, canonical, etc.), making it distinct from sibling tools that focus on individual aspects like schema markup or backlinks.

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., get_schema_markup for JSON-LD). The description lacks context on prerequisites, limitations, or recommended scenarios.

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 adds billing detail ('1 credit per result returned') but doesn't disclose other behaviors like rate limits, ordering (though sort param exists), or whether results are exhaustive. Schema covers parameters but description lacks beyond billing.

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

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

Two concise sentences: first identifies purpose and examples, second states output and billing. No unnecessary words, well-structured for quick reading.

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 description only says 'Returns domains with DA scores.' This is vague; agents need to know the exact fields (e.g., domain string, DA value, possibly platform, TLD, etc.) to use the results accurately. With 6 input parameters, output specification is 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 coverage is 100% with good descriptions for all 6 parameters. Description lists platform examples (WordPress, Shopify) in text, but doesn't add meaning beyond what schema provides. Baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Get all domains running a specific platform or technology' and provides examples like WordPress, Shopify. It explains the output includes DA scores, and distinguishes from sibling tools like get_platform_trends by focusing on domain lists.

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 it mentions billing, it does not discuss when not to use it or compare with siblings like get_platform_trends or get_tech_stack. Implied usage for platform-based domain discovery.

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. It states the output is a ranked list with domain counts, but omits details about sorting order, pagination, rate limits, or whether the list is exhaustive (e.g., 'all detectable' is ambiguous).

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 front-loads the action ('Get a ranked list...') and provides a succinct, zero-waste description. Perfectly concise for a parameterless 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?

Given no parameters and no output schema, the description covers the essential semantics: returns a ranked list of platforms with counts. It could specify the output format (e.g., JSON array) or clarify ranking criteria, but the core is present.

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 (100% coverage, zero params). Baseline is 4 because no additional parameter explanation is needed. The description does not add parameter info, but none is required.

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 ranked list of detectable platforms with domain counts, with a concrete example ('WordPress vs Shopify'). This is specific and actionable, though it does not explicitly differentiate from similar siblings like 'get_platform_domains'.

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 (e.g., 'get_tech_stack' or 'get_platform_domains'). The description only vaguely mentions a use case ('comparing platform adoption') without exclusions or 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 are provided, and the description does not disclose any behavioral traits beyond the basic function. It omits details such as pagination, rate limits, data freshness, or whether results are limited to top domains.

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 phrase with no redundant words. It is optimally 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 three parameters and no output schema or annotations, the description is far from complete. It does not cover parameter behavior, return format, or edge 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 description coverage is 0%, and the description does not explain any parameters (domain, limit, score). It adds no meaning beyond the schema's property names.

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 'Get unique domains linking to a domain' uses a specific verb ('Get') and resource ('unique domains') and clearly distinguishes from siblings like get_backlinks (which likely returns all links) and get_domain_overlap.

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 vs. alternatives. Siblings like get_backlinks or get_link_velocity could serve similar purposes, but the description offers no comparative 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 are provided, so the description bears full responsibility. It only mentions 'v1 stub', implying incompleteness, but does not disclose error handling, data freshness, rate limits, or any side effects. Minimal 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 very short, which is acceptable, but it omits crucial details. It is front-loaded with the purpose, but the brevity sacrifices 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 that there is no output schema and no annotations, the description must provide more context. It fails to explain the output format, error conditions, or any usage constraints, 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 0% description coverage for the 'url' parameter. The description simply says 'for a URL' without adding format constraints, allowed schemes, or behavioral implications (e.g., what happens if URL is invalid).

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 action (get) and resource (schema.org markup for a URL). The '(v1 stub)' suffix indicates a provisional state, but the core purpose is unambiguous. Among sibling tools, it is distinct.

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. No context about prerequisites, limitations, or comparison to siblings like get_page_seo or get_site_explorer.

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

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

The description discloses a key behavioral trait: 'May return partial results when the query fan-out hits time budget.' With no annotations, this is the only transparency provided. It is useful but lacks other details like read-only nature or potential 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?

Two sentences, each adding unique information: purpose and behavioral quirk. No redundant phrasing, front-loaded, and efficient.

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 covers the basic purpose and a key caveat. However, it does not define what 'similar link profiles' means, what the output looks like, or any prerequisites, leaving gaps for an AI 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 schema has a single parameter 'domain' with 0% description coverage. The description provides no explanation of this parameter, leaving its meaning and format entirely to the schema. This fails to add value beyond structured data.

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 finds domains with similar link profiles. This is a specific verb-resource combination that distinguishes it from siblings like get_referring_domains or get_domain_overlap, which focus on different 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?

No guidance on when to use this tool versus alternatives. The only usage-related hint is about partial results under time budgets, but it does not provide selection criteria or when not to 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 alone must convey behavioral traits. It only lists components but does not disclose whether the operation is read-only, any rate limits, data freshness, or scope of the request. An agent would lack context on 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 of 10 words that efficiently communicates the core purpose. No extraneous 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?

Given the tool's many siblings and the absence of an output schema, the description does not specify return format, whether it is a summary or detailed report, or how it integrates with other tools. An agent would need more context to anticipate the output.

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 sole parameter 'domain' has 0% schema description coverage. The description adds no additional meaning, format, or example beyond the parameter name itself, despite the need to compensate for the lack of schema guidance.

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 full SEO overview including backlinks, authority, top pages, and anchor text. It distinguishes itself from sibling tools that focus on individual aspects (e.g., get_backlinks, get_domain_authority).

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 when a comprehensive SEO overview is needed, but does not provide explicit when-to-use or when-not-to-use guidance, nor does it mention relevant alternatives among the many sibling 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, so description carries full burden. Lists what checks are performed but lacks disclosure on side effects, rate limits, or error handling; adequate but not exhaustive.

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 front-loads purpose and lists specifics efficiently, though slightly verbose with many checks; 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?

For a single-parameter tool with no output schema, the description lists what is checked but does not explain result format or behavior for invalid domains, leaving gaps for 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 0%, so description must compensate. It mentions 'domain' implicitly but adds no format, example, or constraint beyond the schema's type string.

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 'Real-time site health check' and enumerates specific checks (HTTPS, HSTS, redirect, etc.), distinguishing it from sibling tools that target individual 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 overall health assessment among many specific sibling tools, but no explicit guidance on when to use or when to avoid, nor mention of 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 provided, so the description carries full burden. It indicates this is a non-destructive read operation that retrieves sitemap data, but lacks details on error handling, caching, or required permissions. Adequate but limited.

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-loads the primary action and output, with no redundant 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 no output schema and 2 parameters, the description is adequate but could be more complete. It specifies return fields but not structure or behavior when sitemap is missing, making it moderately 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 0%, and the description only implies the 'domain' parameter but does not explain 'limit'. Without parameter descriptions, the AI agent has insufficient guidance for correct invocation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states the action 'discover and parse' and the resource 'domain's sitemap', and specifies the return fields (URLs with lastmod, changefreq, priority). This distinguishes it from sibling tools like get_backlinks or get_page_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 on when to use this tool versus alternatives. The sibling list includes many other get_* tools, but the description does not provide context for selection 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?

Describes 'real-time' detection but lacks details on side effects, authorization, rate limits, or error behavior. No annotations provided, so description carries full burden but falls short.

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 and scope, listing many technology types. Could be more structured (e.g., bullet points), but still concise 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?

Provides essential purpose and scope but lacks output format details, error handling, and usage constraints. Given no annotations or output schema, more detail on what the agent can expect 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?

Only one parameter 'domain' with no additional description. The tool description does not clarify expected format (e.g., with/without protocol, subdomain inclusion), failing to compensate for 0% 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?

Clearly states the tool detects technologies for a domain, listing specific categories (frameworks, CMS, etc.) and claims 50+ technologies. Differentiates from siblings focusing on links, SEO, and site health.

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?

Implicitly suggests use for technology profiling, but no explicit guidance on when to use versus alternatives like get_page_seo or get_site_explorer, nor when not to 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 bears full responsibility for disclosing behavioral traits. It states 'get' which implies a read operation, but does not disclose any potential side effects, authentication needs, rate limits, or data freshness. The description adds no behavioral context beyond the tool name.

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 short (one sentence), which can be seen as concise, but it omits essential information. It is not well-structured because it fails to front-load key details about parameters or behavior. While brevity is valued, here it sacrifices 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 lack of annotations, no output schema, and two parameters with 0% schema description coverage, the description is severely incomplete. It does not specify the return format, the meaning of 'most-linked', or the effect of the optional limit parameter. For a tool with many siblings, this provides insufficient context for correct selection and invocation.

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

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

Schema description coverage is 0%, meaning the schema provides no descriptions for the two parameters (domain, limit). The tool description also does not explain what these parameters mean, their format, or expected values. For example, 'limit' could be a number but its purpose (e.g., max pages to return) is left ambiguous. This is a critical gap.

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 'Get most-linked pages for a domain' clearly states the verb (get) and resource (pages) with a specific scoping criterion (most-linked for a domain). However, it does not explicitly distinguish from sibling tools like get_backlinks or get_link_velocity, which could overlap in 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 such as get_backlinks or get_link_intersect, nor does it mention any prerequisites or context where this tool is preferred.

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