Google Rank Checker MCP: Rankings and Competitor Keywords

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

Annotations already declare read-only, idempotent, non-destructive, open-world behavior, so the bar is lower. The description still adds genuinely new context: one live Google search per keyword and that each keyword consumes API credits, which an agent needs before invoking a metered call. It omits the actual credit cost per keyword or any 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?

A single front-loaded sentence with the key facts (what it returns, the scope limits, the cost) in descending order of importance. Dense but no filler; the colon-led structure makes the core action readable at a glance.

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?

An output schema exists, so return values do not need explaining, and annotations cover the safety profile. What remains missing is the relative positioning against get_ranked_keywords and any indication of how expensive the credit cost is, minor gaps for a 7-parameter read-only tool.

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

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

Schema description coverage is 100%, including depth, device, country, language, and location, so the schema already carries the parameter meaning. The description only restates the keyword cap and single-country constraint, adding little 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?

States a specific verb and resource (check live Google position and ranking URL of a domain) plus the scope limits (up to 10 keywords, one country, top competing domains). It is clearly distinct from sibling tools like find_competitor_domains or get_ranked_keywords, though it never names an alternative explicitly.

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 word 'live' implies this is for on-demand checks rather than stored/historical data, which is the main axis separating it from get_ranked_keywords, but the description never states when to prefer one over the other. No prerequisites, exclusions, or alternative routing 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?

Beyond the read-only, idempotent, open-world annotations, the description adds the useful warning that every call costs API credits. It does not specify the credit amount or other cost details, but the cost disclosure is meaningful 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?

Two compact sentences front-load the purpose and returned competitive metrics, then end with the credit-cost warning. There is no unnecessary wording or structural clutter.

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?

Combined with the fully documented input schema, output schema, and safety annotations, the description provides enough information for correct invocation. The main remaining gaps are explicit sibling-selection guidance and a more precise statement of credit cost.

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 the domain format, country and language markets, and limit bounds already documented, so the baseline score applies. The description adds no parameter syntax, defaults, or interaction details 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 identifies the resource and scope: domains competing with a given domain in Google organic search, accompanied by shared keywords, average position, and estimated traffic. Its domain focus implicitly distinguishes it from keyword-oriented siblings, but it does not explicitly differentiate itself from find_competitor_keywords or get_ranked_keywords.

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 Google organic-search context implies use for SEO competitor discovery and analysis. However, there is no explicit when-to-use guidance, exclusion, or alternative for agents choosing among the competitor, ranking, and keyword 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?

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and non-destructive behavior, so safety is covered. The description adds a genuinely useful piece of context the annotations lack: that each call consumes API credits, which affects how freely an agent should invoke it. It does not mention pagination or rate limits, keeping it short of a 5.

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 tight sentences, front-loaded with the defining concept before the output fields and the cost note. Nothing is redundant and nothing is missing from the framing.

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 an output schema present, the description does not need to explain return values, and it still names the key metrics (volume, difficulty, position) to set expectations. Combined with the credit-cost warning, an agent has enough to call it correctly; only explicit sibling routing is absent.

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

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

Schema description coverage is 100%, with defaults, ranges, patterns and examples for all five parameters, so the schema does the heavy lifting. The description only echoes that the inputs are domains (competitor and your own), adding no format or constraint detail beyond what the schema already states — baseline 3.

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

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

The description gives a specific verb-and-resource definition and, crucially, defines the core concept: keywords a competitor domain ranks for in Google that your domain does not. That set-difference framing instantly separates it from siblings like get_ranked_keywords (your own rankings) and find_competitor_domains (domain discovery).

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 gap concept implies when to use it (competitive keyword research), but there is no explicit when-to-use or when-not-to-use guidance and no sibling is named. An agent must infer the boundary from the sibling names alone.

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

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

Annotations already declare readOnly, idempotent, non-destructive, and closed-world, so the safety profile is covered. The description adds genuinely new behavioral context beyond them: the call is free of charge and triggers no upstream supplier call, which tells the agent it is cheap in both cost and latency. It does not discuss caching or freshness of the balance 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?

A single front-loaded sentence packs the returned fields and the cost/latency caveat with no filler. The leading 'API credit balance:' label is mildly redundant with the title but functions as a scannable anchor rather than waste.

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 an output schema documenting the return shape, zero parameters, and rich annotations, the description's burden is small and it meets it: what the tool reports and that it costs nothing. Only the when-to-use signal is absent, which keeps it short of a 5.

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

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

The tool takes zero parameters, so there is nothing for the description to disambiguate; baseline 4 applies. The description correctly offers no parameter guidance, which is appropriate rather than a 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 names the exact resource (prepaid API credit balance) and enumerates the four facts it exposes: credits remaining, amount spent, suspension status, and per-call pricing rule. An agent can tell this is an account/billing read, distinct in substance from the SEO-data siblings, though no sibling is named explicitly.

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?

Usage is only implied: 'Free; no supplier call' hints it is safe to call speculatively (e.g., to verify credits before paid SEO queries), but the description never states when to use it or what alternative exists. Nothing misleads, but the agent must infer the check-before-spending workflow.

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

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

Annotations already declare read-only, idempotent, non-destructive and open-world, so the safety profile is covered. The description adds real value beyond them: the credit cost per call, the single-country scope, completeness of the keyword set, and the traffic-descending ordering that dictates how results arrive.

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 that leads with the resource and packs metrics, ordering and cost with no filler. It is dense but every clause carries information an agent needs.

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 an output schema, full parameter coverage and rich annotations, the description only needs to add scope, ordering and cost — which it does. The one soft spot is the 'every keyword' framing against a default limit of 100, with no mention that results are truncated and must be widened via 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?

Schema description coverage is 100%, so the schema already explains target, limit, country and language with defaults and formats. The description only reinforces that the target may be a domain or full URL and that the market is a single country; it adds no syntax or semantics beyond that, so baseline 3 applies.

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

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

Names a specific resource (ranked keywords for a domain or URL) and enumerates the returned metrics plus the sort order, so an agent knows exactly what it gets. It does not distinguish itself from the nearby sibling find_competitor_keywords, which is the main gap.

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

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

Usage is implied: analyze the ranking footprint of a given domain/URL in one market. The 'costs API credits per call' warning gives a practical trigger to think before calling, but there is no explicit when-to-use/when-not-to-use guidance and no pointer to which sibling to pick instead.

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