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Agent.ai MCP Server

by OnStartups

content_audit_generate_audit_action

Crawl a website to generate a structured content audit with SEO/AEO scores, prioritized action plan, content gap analysis, keyword cannibalization detection, and page-level inventory.

Instructions

Crawls a website and produces a structured content audit with SEO/AEO scores, a prioritized action plan, content gap analysis, keyword cannibalization detection, and a page-level inventory.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
website_urlYesFull URL including https:// (e.g. https://example.com).
audit_scopeYesfull_site
optimization_focusYesbalanced
output_variable_nameYesVariable name for the result.content_audit
Behavior3/5

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

No annotations are provided, so the description must bear the burden. It correctly indicates the tool performs a crawl (implying external network access) and generates a structured audit. However, it does not disclose potential side effects (e.g., rate limits, site impact), required authentication, or time cost. The description is moderately transparent.

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

Conciseness5/5

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

The description is a single, efficient sentence front-loaded with the verb 'crawls'. It lists key outputs without redundancy. Every element adds value, and no unnecessary words exist.

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

Completeness3/5

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

With no output schema, the description outlines expected deliverables (scores, action plan, gap analysis, etc.), giving the agent a good idea of the result. However, it lacks details on parameter usage, process duration, or return format, leaving gaps in completeness.

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 50% (2 of 4 parameters have descriptions in schema). The tool description does not describe individual parameters (e.g., audit_scope, optimization_focus) beyond listing output components. It adds no meaning beyond the schema, so the score is below baseline 3.

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

Purpose5/5

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

The description clearly states the tool's action ('Crawls a website') and specifies the outputs ('structured content audit with SEO/AEO scores, prioritized action plan, content gap analysis, keyword cannibalization detection, page-level inventory'). This distinguishes it from sibling tools like content_audit_render_audit_report, which handles rendering rather than generation.

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?

The description does not explicitly state when to use this tool versus alternatives (e.g., content_audit_render_audit_report for rendering or other content tools). It lacks 'when-to-use' or 'when-not-to-use' guidance, leaving the agent to infer usage from the purpose alone.

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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