Skip to main content
Glama

audit_seo_aeo_geo_readiness

Audit HTML or Markdown for SEO, AEO, and GEO readiness by checking Schema.org tags, broken links, and citation gaps to improve search visibility and AI answerability.

Instructions

Audits HTML/Markdown code for SEO, AEO (Perplexity/SearchGPT direct answers), and GEO (Generative AI indexability) compliance, scanning for missing Schema.org tags, broken link risks, and citation gaps.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
code_or_markdownYesHTML or Markdown code content to audit
Behavior4/5

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

With no annotations, the description carries the full burden and it discloses the specific behaviors (scanning for Schema.org tags, broken link risks, citation gaps), which goes beyond a generic 'audits' statement. It implies a read-only audit operation, though it does not explicitly state the absence of side effects or describe the output format, a minor gap at this complexity level.

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, front-loaded sentence that immediately states the action and resource, then lists specific checks. Every word contributes to understanding the tool's scope, with no redundancy or filler.

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

Completeness4/5

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

The description covers the purpose and the nature of the checks, which is sufficient for a simple one-parameter tool without an output schema. While it does not explicitly describe the return format, it implies a report of findings (missing tags, broken link risks, citation gaps), which is adequate for an agent to call it correctly.

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

Parameters3/5

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

The schema already provides 100% coverage for the single parameter 'code_or_markdown' with a clear description. The tool description adds context about what the audit checks, but it does not enrich the parameter's meaning beyond the schema; the baseline for full schema coverage is 3, and the description does not add syntax or formatting details.

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 audits HTML/Markdown code for SEO, AEO, and GEO compliance, listing specific checks like missing Schema.org tags, broken link risks, and citation gaps. This distinguishes it from sibling audit tools (e.g., audit_performance_bottlenecks, audit_security_vulnerabilities) by its specific focus on search and AI-readiness.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage when you need to assess code for SEO/AEO/GEO compliance, but it does not explicitly mention when to use this tool versus alternatives like generate_seo_aeo_geo_blueprint or other audit tools. There is no 'when not to use' or reference to competing tools, leaving the routing to inference.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Akash1070/Super-Agent-Skill'

If you have feedback or need assistance with the MCP directory API, please join our Discord server