Zutrix MCP Server

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by Zutrix-Technologies

Overview Schema Related Servers Score Discussions

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Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v1.0.0
Disambiguation5/5
Each tool targets a distinct SEO data aspect: keywords, history, suggestions, SERP, competitors, backlinks, site audit, domain overview, AI visibility, and project list. There is no overlap or ambiguity between them.
Naming Consistency5/5
All ten tool names follow the same 'get_' prefix followed by a descriptive noun phrase, creating a predictable and consistent naming pattern.
Tool Count5/5
With exactly 10 tools, the server is well-scoped for an SEO monitoring and analytics platform. Each tool covers a meaningful data category without redundancy.
Completeness4/5
The read-only tool set thoroughly covers keyword tracking, SERP data, competitor analysis, backlinks, technical audits, domain metrics, and AI visibility. The only minor gap is the lack of write operations (e.g., adding/removing keywords), but this aligns with a monitoring-focused server.
Average 3.6/5 across 10 of 10 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits, but it only says 'get' without explaining how the gap analysis is computed, what data is returned, or any safety or limitation details. No annotation contradiction exists.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that efficiently conveys the tool's purpose without unnecessary words. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has a single parameter and no output schema, but 'gap analysis' introduces complexity. The description does not describe return format, pagination, or what the analysis includes, leaving gaps for an agent to infer. It is minimally adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for the single required project_id parameter. The description's 'for a project' aligns with the parameter but adds no new meaning beyond the schema's 'The project ID'. Baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns competitor domains and keyword/backlink gap analysis for a project. The verb 'Get' and specific resource differentiate it from siblings like get_backlinks or get_keyword_suggestions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. The description does not mention which scenarios favor competitor gap analysis over the sibling tools or any exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must carry the burden of explaining behavior. It only states the basic function and omits key details such as pagination behavior, whether it returns all tracked keywords or only those with rankings, or what 'current rankings' looks like in the response. It also does not explicitly confirm that this is a read-only operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence that wastes no words. It is appropriately sized for the tool's simplicity and front-loads the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description gives a high-level purpose but lacks details about the return structure and pagination. Since there is no output schema, the description should more explicitly state what 'current rankings' means and that pagination is supported. The presence of sibling tools also suggests more context could be given about its role, making this only minimally viable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% parameter coverage with descriptions for page, limit, and project_id. The description adds no additional meaning to these parameters 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.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get'), the resource ('tracked keywords with their current rankings'), and the scope ('for a project'). This distinguishes it from siblings like get_keyword_history (historical data) and get_keyword_suggestions (suggestions, not current tracked rankings).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no explicit guidance on when to use this tool versus alternatives. The description implies it is for retrieving current rankings, but it does not mention exclusions or when to prefer get_keyword_history or other sibling tools. No comparison or context is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It only reveals that the operation is a read ('Get'), but does not mention response format, pagination, data freshness, potential errors, or any other behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no extraneous words. It is front-loaded with the action ('Get') and delivers the core information efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description should compensate by explaining what the returned SERP data includes. It lacks that detail, and it doesn't mention any limitations or the role of optional parameters, leaving it incomplete for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides 100% coverage of parameter descriptions, so the baseline is 3. The description does not add additional meaning beyond what the schema documents, such as defaults for device, country, and language.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Get') and resource ('SERP data') with scope ('for a tracked keyword in a project'). It clearly distinguishes this tool from siblings like get_keyword_history, which focuses on historical data, and get_keyword_suggestions, which provides suggestions rather than current results.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'for a tracked keyword in a project' implies the target use case, but the description does not explicitly explain when to choose this tool over alternatives such as get_keyword_history or get_keyword_suggestions, nor does it state exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description is the only source of behavioral context. It adds some transparency by listing the categories of backlinks returned (new, lost, broken), but it does not clarify whether the operation is read-only, how the data is structured, pagination behavior, or any limitations. This is a partial disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is concise, front-loaded, and free of unnecessary detail. Every word adds value by specifying the resource and data categories.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the core purpose but falls short in providing a complete picture. There is no output schema, and the description does not explain the return format, how the different link types are presented, or any other behavioral expectations. For a simple read tool, this is acceptable but not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already describes both parameters (project_id and limit) with full coverage, including the default and maximum for limit. The description adds no additional parameter-level meaning, so the baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get backlink profile data') and the specific resource ('backlinks'), and explicitly mentions the included data types (new, lost, broken links). This distinguishes it from sibling tools, which focus on keywords, competitors, SERP, etc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, nor does it mention any exclusions or prerequisites. It simply describes the function without context for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears full burden for behavior disclosure. It mentions credit usage, which is helpful, but does not state that this is a read-only operation, describe data freshness, rate limits, or the scope of 'comprehensive' metrics beyond the three examples. This leaves significant behavioral ambiguity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that front-loads the core purpose, then adds the important credit usage note. Every word earns its place; there is no fluff or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema and no annotations, so the description must carry the load. It lists three metric categories but lacks details on return format, whether data is current or historical, or how country/language parameters affect results. It is adequate for a simple overview tool but leaves gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with descriptive text for all three parameters, so the schema already documents domain, country, and language. The description adds no extra meaning beyond the schema, warranting a baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Get' with a clear resource 'comprehensive domain metrics' and lists key metrics (organic traffic, backlinks summary, domain rank). This distinguishes it from sibling tools that target specific data like get_backlinks or get_keyword_history.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies this is a high-level overview tool by calling metrics 'comprehensive' and notes it 'Uses explorer credits', which is a resource constraint. However, it does not explicitly state when to choose this over sibling tools or mention alternatives, so usage guidance is only implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden, but it merely restates the tool's name. It doesn't disclose return format, pagination, any read-only characteristics beyond the verb 'Get', or limitations like data granularity. Feels like a one-line placeholder.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single concise sentence that front-loads the core purpose without any fluff. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read tool with a complete schema, the description is adequately scoped but lacks output format details since no output schema exists. It doesn't explain what the history data looks like or how the days parameter shapes the returned series, leaving some ambiguity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides 100% coverage with detailed descriptions for keyword_id (format) and days (range/default), so the description adds minimal parameter-level meaning. The phrase 'specific tracked keyword' reinforces keyword_id but doesn't clarify how days affects the response.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Get') and resource ('ranking position history') scoped to 'a specific tracked keyword', which clearly distinguishes it from siblings like get_serp_results (current SERP) or get_project_keywords (list). The 'over time' aspect uniquely identifies this as a historical tracking tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for historical ranking data but provides no explicit when-to-use vs alternatives or exclusions. It doesn't reference sibling tools like get_serp_results for current rankings, leaving the decision to the agent based on the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It does disclose that using the tool consumes 'planner credits,' which is a useful behavioral trait. However, it does not mention whether this is a read-only operation, any rate limits, auth requirements, or what the response looks like. The cost disclosure earns a midpoint score, but more context would be needed for full transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence of about a dozen words, front-loaded with the action and resource. The parenthetical detail about planner credits is efficiently integrated. Every word earns its place, and there is zero redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (3 params, all documented) and no output schema, the description is mostly complete for a 'get' tool. It covers what it returns (ideas and metrics) and flags a cost consideration. It could arguably benefit from a mention of the return format or pagination, but for the tool's complexity, it is sufficiently comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All three parameters have descriptions in the schema, making baseline 3 appropriate. The main description adds the phrase 'seed keyword' which reinforces the keyword parameter, but does not add new meaning beyond the schema. No additional parameter-level detail is provided in the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific verb ('Get') and resource ('keyword ideas and metrics') for a provided 'seed keyword'. It distinguishes from siblings like get_project_keywords by emphasizing the seed keyword input, and the parenthetical about planner credits adds a distinguishing cost nuance.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no explicit guidance on when to use this tool vs. alternatives. The description mentions 'uses planner credits' but does not explain when this is appropriate or that other tools like get_project_keywords might be better for retrieving existing project keywords. Usage context is entirely absent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It clearly implies a read-only operation ('Get') and adds context about the data source (AI-generated responses across specific models). However, it does not mention limitations, authentication, output format, or whether data is real-time or historical, which are relevant behavioral details for this type of tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence. It front-loads the verb and resource, adds useful detail about models, and contains no redundant or extraneous words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (one required parameter, no output schema, no annotations), the description is mostly complete. It clearly explains the core function and what kind of data is returned. The only gap is that it does not specify the structure or fields of the output, but for a simple tool, this may be sufficient. The description provides enough context for an agent to select the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter, project_id, is fully described in the schema ('The project ID'), achieving 100% schema coverage. The description adds no additional meaning to the parameter, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Get') and resource ('AI search visibility data') and clearly explains how the feature works by mentioning brand appearance in AI-generated responses across models like ChatGPT, Claude, Gemini, and others. This clearly distinguishes it from sibling tools like get_serp_results or get_keywords, which focus on traditional SERP or keyword data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by stating exactly what data the tool provides (AI visibility), so a user needing AI brand visibility would understand this is the right tool. However, it does not explicitly mention when not to use it or name any alternative tools, leaving the usage guidance implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the behavioral disclosure burden. The verb 'List' implies a safe read operation, but the description does not explicitly state that it is read-only, nor does it mention any rate limits, permissions, or pagination behavior. It provides basic transparency 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that directly states the action and target. Every word is purposeful, and there is no repetition or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (zero parameters, no output schema), the description adequately conveys its purpose and the general content of the response (projects with enabled features). However, it stops short of detailing the response structure, which would be valuable since no output schema is present.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero parameters, so the baseline is 4. The description does not need to explain parameter semantics, and 'with their enabled features' hints at what the response contains rather than parameters. No further parameter information is required.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'List' with a clear resource 'your Zutrix SEO projects' and adds 'with their enabled features' to define the scope. It sharply distinguishes this tool from sibling tools like get_project_keywords or get_serp_results, which focus on project-specific data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit usage guidance is provided. The description does not mention when to choose this tool over alternatives, nor any prerequisites or exclusions. For a list tool that likely serves as an entry point to other project-scoped tools, saying 'use this to get projects before using project-specific tools' would be helpful.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the behavioral transparency burden. It adds the critical cost notice 'Uses audit credits', which informs the agent of resource consumption. However, it does not mention read-only status, rate limits, or execution characteristics like synchronous vs. asynchronous behavior, leaving some gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two short sentences that front-load the purpose and outputs, then state the credit usage. Every word earns its place, with no redundant phrases or unnecessary details, making it highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool with no output schema, the description adequately covers the purpose, return categories, and credit consumption. It could optionally mention whether results are historical or cached, but as-is it provides a solid context for an agent to select and invoke the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema covers 100% of parameters with a description for the single 'url' field. The description reinforces that the tool audits a URL but does not add new syntax or format details beyond 'Full URL to audit', so it provides minimal additional semantic value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Run' and resource 'technical SEO audit on a URL', clearly stating the tool's action and scope. This distinguishes it from sibling tools like get_keyword_history or get_backlinks, which focus on different SEO data types.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use the tool—when a technical SEO audit is needed—and lists concrete outputs (performance, meta tags, headings, images, links) that clarify its domain. It does not explicitly name alternatives or exclusions, but the scope is sufficiently clear among the sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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