Serpstat MCP Server

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 effectively describes key behaviors: returns large datasets (full top-100 for each keyword/date), includes competitor analysis with historical data, does not consume API credits, and warns about response size management. It lacks details on error handling or rate limits, but covers essential operational traits.

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 well-structured and front-loaded with the core purpose, followed by important warnings and usage tips. Every sentence earns its place by adding critical information about dataset size, recommendations, filtering, tagging, and API credit impact, with no redundant or verbose content.

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 complexity (10 parameters, no output schema, no annotations), the description does a strong job by explaining the tool's purpose, behavioral traits, and usage guidance. It could improve by detailing the output structure (e.g., format of returned data) since there's no output schema, but it adequately covers input handling and operational context for effective use.

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 documents all 10 parameters thoroughly. The description adds marginal value by mentioning keyword tagging (related to 'withTags') and filtering recommendations (implied for 'dateFrom', 'dateTo', 'keywords'), but does not provide significant additional semantics beyond what the schema descriptions already cover.

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 purpose: 'Get complete Google top-100 SERP history for tracked keywords in a rank tracker project.' It specifies the verb ('Get'), resource ('SERP history'), and scope ('tracked keywords in a rank tracker project'), distinguishing it from siblings like 'get_rt_project_url_serp_history' which focuses on URLs rather than 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 description provides clear usage context with warnings about large datasets and recommendations for pageSize (20-50), plus advice to use date and keyword filters to reduce response size. It mentions keyword tagging for grouping/filtering but does not explicitly state when NOT to use this tool or name specific alternatives among siblings, though it implies it's for keyword-based SERP history.

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