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MentionAgent

by ai.mentionagent
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Pitch sites the person already chose

import_sites
Idempotent

Queue sites the person has already vetted and wants a link or mention on. Each entry is a page URL or bare domain, optionally with a contact email, name and a note that reaches the draft. The next runs take these first and skip the agent's own fit check, but still find and verify a contact and still skip sites already emailed or blocked. A very large site (Forbes class) is only pitched to an email given here. A site skipped earlier is queued again when re-imported with an email. Up to 1,000 per call. Sends nothing: the drafts arrive in the normal pending batch.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "workspaceId": "<workspaceId>",
      "sites": "<sites>"
    },
    "name": "import_sites"
  }
}

Input Schema

NameRequiredDescriptionDefault
sitesYesSites to queue.
workspaceIdYesWhich site to act on. Call get_status with no arguments to list them.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.4/5.0
Behavior5/5

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

The description adds substantial behavioral context beyond annotations: it sends nothing, drafts arrive in the normal pending batch, fit checks are skipped, contacts are still verified, already emailed or blocked sites are skipped, large sites require an email, and re-imports can requeue skipped sites. This is exactly the kind of operational detail an agent needs for a mutating import tool.

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 dense but front-loaded, starting with the core action and immediately adding scope and behavior. Every sentence carries operational information, including limits and side effects, with no 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?

For a mutation tool with no output schema, the description covers the important behavior: no sends, pending-draft destination, deduplication, verification, and the 1,000-site cap. It does not describe the return value or error response, but otherwise gives an agent enough to invoke 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?

Schema description coverage is 100%, so the schema already documents url, name, note, email, and workspaceId. The description reinforces what each entry represents and mentions the note reaching the draft, but adds no new syntax or constraints for workspaceId or the site fields beyond the schema.

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 states a specific verb and resource: queue sites the person has vetted for pitching. It is clearly distinct from sibling tools like add_keywords and list_imported_sites, and the title reinforces the exact scope.

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

Usage Guidelines4/5

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

It explains when these sites are used: next runs take them first and skip the agent's own fit check, while still verifying contacts and avoiding already-emailed or blocked sites. It gives important conditions such as re-import behavior and the Forbes-class rule, but does not explicitly name alternatives like list_imported_sites.

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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