get_v1_keyword_difficulty_checkerFind out how hard it'll be to rank in the top 10 for any keyword. Group: Keyword Research. Billing per call: 1 Credits.
| Name | Required | Description | Default |
|---|---|---|---|
| country | No | ||
| keyword | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden for behavioral disclosure. However, it only states the tool's purpose and billing details. It does not mention required inputs, error handling, rate limits, or what kind of result is returned (e.g., a numeric score). The agent has no insight into side effects or constraints beyond the obvious read-only nature of a difficulty checker.
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 the purpose front-loaded in the first sentence. The second sentence includes group and billing info, which is somewhat redundant but not verbatim from metadata (since annotations are absent). It is efficiently structured and contains 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 the tool's simplicity (2 parameters, no output schema), the description still fails to explain what the output will look like or how to interpret the difficulty result. It does not mention any limits, examples of output, or how the scoring works. The agent is left without key information to confidently use and interpret the tool's response.
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 elaborate on the parameters 'country' and 'keyword'. While the parameter names are somewhat self-explanatory, the description adds no additional context about acceptable formats, default values, or optionality. With no schema descriptions, the burden falls on the description, which fails to compensate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: finding how hard it will be to rank in the top 10 for a keyword. This is a specific verb+resource with a clear outcome, and it naturally distinguishes from sibling tools like backlink checkers or rank checkers by focusing on difficulty.
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 keyword research ('Group: Keyword Research') but provides no explicit guidance on when to choose this tool over alternatives, nor any exclusions or prerequisites. It lacks a clear 'use this when...' statement, so agents must infer applicability.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct SEO function: backlinks, broken links, keyword difficulty, keyword generation per platform, rank checking, SERP analysis, and website metrics. The platform-specific keyword generators (Amazon, Bing, Google, YouTube) are clearly differentiated. No two tools overlap in purpose.
All tools follow a uniform 'get_v1_' prefix followed by a descriptive noun phrase, creating a predictable and coherent pattern. The consistent use of snake_case and the same verb prefix makes the toolset easy to scan and understand.
With 11 tools, the set is well-scoped for an SEO data provider. Each tool represents a meaningful API endpoint without unnecessary duplication or bloat. The count falls comfortably within the ideal range for a focused server.
The toolset covers core SEO workflows: link analysis (backlinks, broken links, authority), keyword research (difficulty, generators, rank), and SERP/traffic metrics. Minor gaps exist, such as missing site audit or content explorer tools, but the provided surface handles typical use cases effectively.