verify_linksCheck a list of domains against your live backlink profile and report which of them now link to you, when the link first appeared, and whether it is still there. A link that was removed shows as a change rather than staying on the scoreboard.
| Name | Required | Description | Default |
|---|---|---|---|
| domain | Yes | Your domain. | |
| pitched | Yes | The domains or URLs you pitched. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full behavioral burden. It explains the live-profile check, the reported fields, and the important nuance that removed links appear as changes rather than remaining on the scoreboard. It does not cover errors, rate limits, or propagation delays, but the core behavior is clearly disclosed.
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 dense sentences with no filler. The main action and output are front-loaded, and the second sentence adds a valuable behavioral detail that prevents misinterpretation of removed links.
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 tool with only two simple parameters and no output schema, the description provides everything an agent needs to invoke it correctly: what to supply, what the report contains, and how removed links are treated. No critical behavioral information is missing.
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%, so both parameters are already fully documented. The description adds only marginal parameter-level context by framing 'pitched' as the domains to check and 'domain' as your own domain, which mostly restates the schema. Baseline 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?
The description states a specific action ('Check a list of domains against your live backlink profile') and clearly defines the output: which domains now link, when the link first appeared, and whether it is still present. It distinguishes itself from backlink-related siblings like backlink_gap by focusing on verifying previously pitched domains rather than finding gaps or prospects.
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 clearly implies its context: verifying whether pitched domains have landed links in the live backlink profile. However, it does not explicitly name alternatives or state when not to use this tool, so it stops short of the highest tier of usage guidance.
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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Each tool targets a distinct resource or action: agents, documents, prospects, competitors, visibility, and link checks are clearly separated. Even the closely related link-building tools are differentiated by whether they find prospects, find competitor gaps, or verify existing links.
Almost every tool follows a clear verb_noun pattern using lowercase snake_case, such as list_agents, run_agent, and verify_links. The one minor deviation is backlink_gap, which reads as a noun phrase rather than an imperative verb, so the pattern is not perfect.
Fourteen tools is within the ideal range and each tool covers a meaningful part of the Mentionry workflow. The count feels justified given the breadth of features: site analysis, competitor discovery, prospecting, link verification, outreach drafting, agent management, document retrieval, and visibility reporting.
The core workflow is well covered: audit a site, find competitors, discover prospects, verify links, draft outreach, run agents, and read results. The main gaps are agent lifecycle management and document management beyond reading, but those may reasonably live in the Mentionry dashboard rather than the MCP surface.