content_gap_analysisCompare your content against competitor URLs to identify missing keywords, heading gaps, and similarity scores.
Compare your content (URL or raw_text) against competitor URLs to find missing keywords, heading gaps, and similarity scores.
| Name | Required | Description | Default |
|---|---|---|---|
| yourContent | Yes | ||
| competitorUrls | Yes |
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the comparison behavior and result categories, but does not mention whether it fetches competitor URLs, how it handles raw_text, or any limitations. This is moderate transparency for a read-oriented analysis tool, with no annotation contradiction.
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?
A single focused sentence that front-loads the action and includes the key input modes and outputs. There is no filler or repetition, and every phrase contributes to understanding the tool.
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?
With no output schema, the description lists the output dimensions ('missing keywords, heading gaps, similarity scores'), which is sufficient to understand the result at a high level. It could add more on fetch behavior or return format, but the core invocation context is covered.
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%, so the description must compensate. It does clarify the semantics of both parameters: your content can be a URL or raw_text, while the second parameter is a list of competitor URLs. It doesn't describe the nested type/value object structure, but the schema itself provides that structure.
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 uses a specific, informative verb ('Compare') and names both the resources ('your content' vs 'competitor URLs') and the outputs ('missing keywords, heading gaps, similarity scores'). This makes the tool's function clear and differentiates it from single-purpose siblings like extract_keywords or compare_headings.
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 the use case—comparing your own content against competitors to identify gaps—but does not explicitly say when to prefer it over alternatives, nor does it mention exclusions. It gives enough context for selection but leaves alternative routing to the agent's inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.