Lists pages on momenticmarketing.com from sitemap.xml. Optional section filter: team, case-studies, capabilities, services, blog, seo-news, content-academy, google-updates, blog-categories, careers, about, contact, pricing.
| Name | Required | Description | Default |
|---|---|---|---|
| section | No | Section slug (e.g. "team", "case-studies"). Omit to list all. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description discloses the data source (sitemap.xml) and filtering. However, it omits details like return format, pagination, rate limits, or authentication needs.
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?
Two sentences: first states purpose and source, second explains optional parameter. No redundant words, front-loaded.
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?
For a simple list tool with one optional param and no output schema, the description covers the core functionality and usage. Minor gap: no mention of output structure (e.g., list of URLs).
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?
Single parameter with 100% schema coverage. Description adds example values and clarifies default behavior (omit to list all), complementing the schema's generic description.
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?
Clearly states it lists pages from a specific sitemap URL, with optional section filter. Distinguishes from siblings like get_page (single page) and search (cross-site search).
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?
Explains optional section filter and default behavior (list all). Does not explicitly state when not to use or list alternatives, but the context is clear enough for an agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a clearly distinct purpose: page SEO vs site AI discovery vs bot checks vs graph computation vs link extraction vs brand info vs page fetching vs listing vs entity lookup vs freshness parsing vs search. No overlapping responsibilities.
All tool names follow a consistent verb_noun pattern in lower_snake_case (e.g., analyze_page, check_bots, compute_link_graph). No mixing of conventions.
11 tools is well-scoped for the server's purpose (SEO/web analysis). Each tool earns its place, covering page, site, bot, link graph, entity, and freshness analysis without unnecessary bulk.
The tool surface appears complete for its domain: it covers individual page SEO, site-wide AI discovery, bot accessibility, link graph analysis, entity lookup, and freshness signals. No obvious gaps for the intended analysis workflows.
