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occirank

Haloscan MCP Server

by occirank

get_keywords_related

Find related keywords for any seed keyword. Use filters on volume, competition, CPC, and more to refine SEO keyword research.

Instructions

Obtenir les mots-clés associés.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
lineCountNoMax number of returned results.
order_byNoField used for sorting results. Default sorts by descending volume.
orderNoWhether the results are sorted in ascending or descending order.
volume_minNo
volume_maxNo
cpc_minNo
cpc_maxNo
competition_minNo
competition_maxNo
kgr_minNo
kgr_maxNo
kvi_minNo
kvi_maxNo
kvi_keep_naNo
allintitle_minNo
allintitle_maxNo
word_count_minNo
word_count_maxNo
includeNo
excludeNo
keywordYesSeed keyword
exact_matchNo
depth_minNo
depth_maxNo
Behavior1/5

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

With no annotations provided, the description carries the full burden but only says 'Obtenir les mots-clés associés.' It fails to disclose any behavioral traits such as whether the tool is read-only, whether results are paginated, what the response contains, or any side effects. This is a severe gap.

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

Conciseness2/5

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

The description is very concise (one short sentence) but at the expense of essential information. It is not structured effectively; it lacks a description of return values, parameter groups, or usage examples. Frontier-loading is acceptable, but the content is insufficient.

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

Completeness1/5

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

Given 24 parameters, no output schema, and no annotations, the description is critically incomplete. It does not explain what the tool returns, how filtering parameters interact, or how to interpret the 'related' concept. An agent cannot use this tool effectively without external knowledge.

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

Parameters2/5

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

Schema description coverage is only 17% (4 of 24 parameters have descriptions). The tool description adds no parameter-level information beyond what exists in the schema. The many undocumented parameters (e.g., volume_min, cpc_min, competition_min, etc.) leave the agent without understanding their purpose or allowed values.

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

Purpose3/5

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

The description states it gets 'related keywords', providing a verb and resource. However, among many sibling tools with 'get_keywords_' prefix, it does not clarify what 'related' means (e.g., semantically related, co-occurring), making it vague and not distinguishing from similar tools like get_keywords_similar or get_keywords_match.

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 its many siblings. There are no examples, exclusions, or context for appropriate use cases, leaving the agent without decision support.

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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