Analyze brand vs. non-brand query performance using a regex pattern to reveal traffic and conversion splits.
Analyze performance split between Brand and Non-Brand queries using a regex.
| Name | Required | Description | Default |
|---|---|---|---|
| siteUrl | Yes | The site URL | |
| brandRegex | Yes | Regex to match brand keywords (e.g. 'acme|acme corp') | |
| days | No | Number of days to analyze (default: 28) | |
| engine | No | The search engine (default: google) |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose behavioral traits. It mentions using a regex for splitting but omits whether the operation is read-only, required permissions, or output format. Minimal transparency.
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?
Single sentence that is concise and front-loaded with the verb 'Analyze'. No wasted text, but could benefit from additional structure (e.g., listing key parameters or output).
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?
Description is too brief for a 4-parameter tool with no output schema. It does not describe the return format or key contextual details like the meaning of 'performance split' (is it traffic, conversions?). Incomplete for an AI agent to confidently 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 coverage is 100% with descriptions for all 4 parameters. The description adds no extra meaning beyond 'using a regex' and does not explain the optional parameters (days, engine). Baseline of 3 is appropriate.
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?
Description states a specific action (analyze performance split) using a specific method (regex). It clearly identifies the resource (Brand vs Non-Brand queries) but does not differentiate from sibling tools like brand_analysis or bing_brand_analysis.
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?
No guidance on when to use this tool versus alternatives. The description lacks context for usage scenarios, prerequisites, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.