find_prospectsSearch the open web for pages that would plausibly link to this site: resource pages, roundups, listicles and directories in its subject. Returns each with the reason it was kept.
| Name | Required | Description | Default |
|---|---|---|---|
| topic | No | Optional. Narrows the search to one theme. | |
| domain | Yes | ||
| audience | No | ||
| keywords | No | ||
| description | No | What the site does. Use read_site if you do not have one. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral burden. It discloses that the tool searches the open web and returns each kept result with a reason, which is useful. However, it does not mention result limits, latency, data-source caveats, or how the plausibility filtering works.
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?
The description is two sentences with no filler. The core action and result format are front-loaded, and every phrase contributes meaning: what it searches, what types of pages it targets, and what it returns.
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?
The tool has five parameters, no annotations, and no output schema, but the description only covers the general purpose and one output behavior. Optional parameter semantics and usage boundaries versus sibling tools are missing, making the definition incomplete for confident invocation beyond the required domain.
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 only 40%, and the description does little to compensate for the undocumented parameters. 'domain' maps to 'this site' and 'subject' loosely relates to topic/audience/keywords, but audience, keywords, and description are not explained at all, leaving their semantics unclear.
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 names a specific verb and resource: 'Search the open web for pages that would plausibly link to this site.' It further specifies the types of pages (resource pages, roundups, listicles, directories), which clearly differentiates it from siblings like discover_competitors or backlink_gap.
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 intended use is implied: use this when you want link-building prospects for a given site. However, there is no explicit when-to-use or when-not-to-use guidance, and no alternative sibling tools are mentioned, so the agent must infer the selection context.
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 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.